(PDF) Conference Proceeding of the 8th international online Conference on Contemporary Studies in Management (CoSiM), CoSiM Journal No 4, Institut für gemeinnützige Dienstleistungen, Germany

Markus A. Launer

CoSiM Journal No. 4

Conference Proceedings

8th international Conference on Contemporary

Studies in Management (CoSiM)

Institut für gemeinnützige Dienstleistungen gGmbH, Suderburg, Germany

Around the World around the Clock

Markus A. Launer

November 2024

A Publication of the

Institut für gemeinnützige Dienstleistungen gGmbH, Suderburg, Germany

(Non-profit charity organization for Social Projects and Research)

ISSN 2943-9019 DOI: 10.13140/RG.2.2.30179.05920

Editor:

Prof. Dr. Markus A. Launer

Bötzow Str. 12

10407 Berlin

Orcid No. 0000-0001-9384-0807

Prof. Dr. Markus A. Launer is Professor of Business Administration and Service Management at the

a German University of Applied Sciences. Before he was lecturer at the Fresenius University,

Hamburg School of Business Administration (HSBA), and International School of Management

(ISM). He has over 20 years of domestic and international industry experience in large, medium and

small businesses as well as a consultant in investor relations and capital markets communications,

including 9 years in the United States. The last 6 years he was working closely with Universities in

Asia and Latin America. Launer is founder and managing director of the independent Institut für

gemeinnützige Dienstleistungen gGmbH (non-profit, charity organization).

Publisher:

Institut für gemeinnützige Dienstleistungen gGmbH

Hauptstrasse 28

29556 Suderburg, Germany

Launer@InstitutfuerDienstleistungen.com

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Citation example: Launer, M. (2024). CoSiM Conference Proceeding No. 8 / 2024, in: Launer,

M. (ed). Conference Proceeding of 8th international online Conference on Contemporary

Studies in Management (CoSiM), CoSiM Journal No 4, Suderburg, Germany, p. 1-10, Orcid No

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Support

Fatih Çetin, Baskent University, Turkiye and Lukas Alvermann (student)

Markus A. Launer Conference Proceeding CoSiM 2024

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Acknowledgement of Editorial Board, Review Team & Session Chairs

Collaborators and Editorial Board

Prof. Dr. Joanna Paliszkiewicz, Warsaw University of Life Sciences, Poland

Prof. Dr. Fatih Çetin, Baskent University, Turkiye

Prof. Dr. Erik Capistrano, University of the Philippines, Dilliman, Manila, Philippines

Prof. Dr. Dave Marcial, Silliman University, Philippines

Prof. Dr. Kandappan Balasubramanian, Taylor`s University, CRiT Institute, Malaysia

Prof. Dr. Kuanchin Chen, Western Michigan University, USA

Prof. Dr. Bo Aquila Yang, Beijing Open University, China

Prof. Dr. Joeffrey Maddatu Calimag, Kyungsung University, Korea

Prof. Dr. Marja Nesterova, Dragomanov Ukrainian State University, Kiev, Ukraine

Prof. Dr. Mohammad Daud Ali, University of Haripur, Pakistan

Prof. Dr. Frithiof Svenson, Germany

Review Team

Prof. Dr. Fatih Çetin, Baskent University, Turkiye (Head)

Prof. Dr. Erik Capistrano, University of the Philippines, Manila

Prof. Dr. Dave Marcial, Silliman University, Philippines

Prof. Dr. Piotr Pietrzak , Warsaw University of Life Sciences, Poland

Dr. Joanna Rosak-Szyrocka, Czestochowa University of Technology, Poland

Dr. Tamar Dolidze, Batumi State Maritime Academy, Georgia

Dr. Frithiof Svenson, Germany

Session Chairs of the Conference

Ukraine: Prof. Dr. Daria Suprun – National University of Life and Environmental

Sciences of Ukraine, Ukraine

Eastern Europe: Dr. Joanna Rosak-Szyrocka, Czestochowa University of Technology, Poland

Western Europe: Prof. Dr. Markus Launer; Dr. Frithiof Svenson, Germany

Americas: Prof. Simon Zalimben, Universidad Católica Nuestra Senotra de la Asuncion,

Paraguay

North West Asia: Prof. Dr. Joeffrey Maddatu Calimag, Kyungsung University, Korea

South East Asia: Prof. Dr. Dave Marcial, Silliman University, Philippines

India: Dr Shailja Vasudeva, Shaheed Captain Vikram Batra Government College,

India, Dr. Jasveen Kaur, Business School-UBS, Guru Nanak Dev University,

Amritsar-India, India

Pakistan: Prof. Dr. Mohammad Daud Ali, University of Haripur, Pakistan

Middle East: Azra Tajhizi, Azad University of Maragheh, Iran

Markus A. Launer Conference Proceeding CoSiM 2024

III

Acknowledgement of our Key Note Speakers

Prof. Dr. Cihan Cobanoglu (Honorary Chair), University of Southern Florida, USA

Prof. Wing-Keung Wong (Chair Professor), Department of Finance, Asia University, Taiwan, and

China Medical University Hospital, Taiwan Hong Kong Shue Yan University, Hong Kong

Prof. Dr. Kuanchin Chen, Professor of Computer Information Systems, Director of the Center for

Business Analytics, and John W. Snyder Fellow at Western Michigan University, USA

Prof. Dr. Eugene Sadler-Smith, Professor of Organizational Behaviour, University of Surrey, UK.

Dr. Marta Sinclair, Senior Lecturer in the Department of Business Strategy and Innovation, and

member of the Griffith Asia Institute, Australia.

Prof. Dr. Rania Lampou, Greek Ministry of Education, Directorate of Educational Technology and

Innovation, Greece

Prof. Hakki Okan Yeloglu, Başkent University Department of Technology and Management, Turkiye

Dr. Rich Harrill, University of South Carolina, USA

Joachim Delekat, Member of the Uelzen City Parliament and Project Manager at the Independent

Institute for non-profit Services gGmbH (Institut für gemeinnützige Dienstleistungen), Germany.

OStD Stefan Nowatschin, the Vocational School Uelzen (Berufsbildende Schulen 1).

OStR Frank Nierath, Teacher, Vocational School Uelzen (Berufsbildende Schulen 1)

Markus A. Launer Conference Proceeding CoSiM 2024

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Table of Content

Acknowledgement of Editorial Board, Review Team & Session Chairs ....................... II

Acknowledgement of our Key Note Speakers ................................................................ III

Management ....................................................................................................................... 8

Entrepreneurial Mindset in a VUCA World .................................................................................. 8

Laura Noel

Peculiarities of the Human Resources Development in State Authorities of Ukraine ................ 20

Tetiana Balanovska, Oksana Havrysh, Krystyna Dramaretska and Barbara Wyrzykowska

Exploring Workplace Mental Health Amid Digital Transformation: An Overview ....................... 41

Mustapha Ahmimid and Said Balhadj

Exploring the Role of Culture in Leadership Styles and Deviance Credit .................................. 44

Batuhan Özkanlı

The Growth of Indian Aquaculture ............................................................................................ 48

Er. Safaljot Singh and Jasveen Kaur

Algebraic System as Key Concept of Textual Data Analysis of Change Management .............. 52

Averkyna Maryna and Tabur Lauri)

Strategic Imperatives of the national Economies’ Competition .................................................. 56

Mykola Pasichnyi and Anton Nepytaliuk

Digitalization and modern Technologies ....................................................................... 61

The Meta-Analytics of Data Science: An intuitive Perspective .................................................. 61

Sidharta Chatterjee

Investigation of New Generation Restaurants in Gastronomy Digitalization Process ................ 77

Rana Şat, Markus A. Launer, Ercan Karacar and Emre Akmanoglu

Internet and Facebook Addictions among Filipino Students in Higher Education ...................... 81

Dave E. Marcial, Jan Cynth Palama and Jade Montemayor

Confirmation Bias and Trust in Social Media among Filipino Students in Higher Education

Institutions ................................................................................................................................ 84

Dave E. Marcial, Aurielle Lisa Z. Maypa and Cindy Ruth R. Villariza

Markus A. Launer Conference Proceeding CoSiM 2024

V

Digital Citizenship and responsible Use of Social Media amomg Filipino Students in Higher

Education Institutes .................................................................................................................. 87

Dave E. Marcial, Alfie Arcelo and Russel Basiao

Understanding and Practice of "Programming Education in Primary and Secondary education "

as a Liberal Arts Subject ........................................................................................................... 90

Noriko Suzuki, Joji Maeno and Katsuhiko Kakehi

Behaviours and Attitudes of Students Towards AI Technology ................................................. 94

Anna Jasiulewicz, Fatih Çetin and Marzena Lemanowicz

Philipine Farmer`s Digital Assistant: a Web-based Land Preparation and Planting Information

System ..................................................................................................................................... 98

Edgar B. Agos and Dave E. Marcial

Smart City Concept for Small-Town country-side Cities .......................................................... 102

Michael Kindahl, Joachim Delekat and Markus Launer

Sustainability and Corporate Social Responsibility ................................................... 114

Exploring Corporate Social Responsibility Significance, Practices, and Challenges encountered

by the Hotel Industry in Calabarzon, Philippines ..................................................................... 114

Noelah Mae D. Borbon

A Literature Study on the Use of Ancestral Seeds in the Application Kitchens of Universities

within the Scope of Sustainable Gastronomy Practices .......................................................... 117

Ercan Karacar, Rana Şat, Gör. Serkan Seminit, Dilek Karakas and Markus Launer

Strategies On Accelerating Sustainable Development Goals (SDG) Management through AI

Integration .............................................................................................................................. 135

Dimitrios A. Karras

Education and E-Learning ............................................................................................ 155

Meta Discourse ands Appraisal Analysis of Media Perspective on Thai Government`

Performance towards Thai Education ..................................................................................... 155

Sirikarn Thongmak

How Can We Advance Cognitive Skills for Sustainable Careers? Integrating the Inner

Development Goals (IDG) Framework into Business School Classrooms 159

Yuliya Shtaltovna

Markus A. Launer Conference Proceeding CoSiM 2024

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Monitoring and Evaluation of Online Volunteer Tutorial for Alternative Education Students .... 164

Christian Philippine Momongan, Vicente Obejero Jr., George Cadano, Angelika Fae Amado,

Mileni Torres, Janice Diola and Aurelio Vilbar

Intuitive Decision-Making .............................................................................................. 173

Measuring Emotional Intelligence ........................................................................................... 173

Joeffrey Maddatu Calimag and Markus A. Launer

Managing Intuitive and Emotional Intelligence for Digital Wisdom and the Future .................. 196

Marcus Anthony

Rational and Intuitive Decision-Making in the Area of Sustainability: a Review of Literature ... 199

Piotr Pietrzak, Markus A. Launer and Marta Mendel

Speed and Timing of intuitive Decision-Making ...................................................................... 208

Agnieszka Tul-Krzyszczuk, Olena Kulykovets,Barbara Wyrzykowska and Markus Launer

Literature Study on Rational and Intuitive Decision-Making .................................................... 220

Haseeb Khan, Muhammad Nisar Khan, Mohammad Daud Ali and Markus Launer

Latest research on the Human Gut Microbiome and the ENS System .................................... 240

Muhammad Umair, Mohammad Daud Ali and Markus Launer

Literature Study on the Avoidance of Decision-Making ........................................................... 251

Atiq Khattak, Mohammad Daud Ali and Markus Launer

Roles of Uncertainty Avoidance and Long-versus Short-Term Orientation on Decision Making

Style a Literature Study .......................................................................................................... 258

Fatih Çetin, Markus Launer and Burcu Tosun

Developing a Concept of Measuring Rational and Intuitive Decision-Making in China ............ 275

Marcus T Anthony, Bo Aquila Yang and Markus A. Launer

A new Dimension on Research based on Hunches, Pre-cognition and Pre-Monition: a Scale

Development Study based on Literature on Anticipation ......................................................... 280

Mohammad Daud Ali, Natsuko Uchida and Markus Launer

Markus A. Launer Conference Proceeding CoSiM 2024

VII

Diversity and Women Empowerment ........................................................................... 309

Econometric Analysis of Gender Presence and Performance of Women in the Workplace in

Cameroon (Sub-Saharan Africa) ............................................................................................ 309

Jam Jude Ngong and Kristine Joy S. Simpao

Financial Literacy in Investment Decisions of Working Womem ............................................ 324

Jasveen Kaur and Ishma Gupta

Diversity-Equality-Inclusion Practices in Small and Medium-Sized Companies: a Study in 4

Countries ................................................................................................................................ 337

Tauno Kekäle

Women in Digital: A Comparative Analysis of EU and Türkiye ................................................ 340

Özlem Genç, Olcay Ceran Arslan, Batuhan Özkanlı and Özlem Atay

Exploring the Possibilities of Manufacturing in Programming Education for Women ............... 345

Natsumi Kurosawa, Yuna Miyashiro and Natsuko Uchida

Thank you Note by Editor ............................................................................................. 349

Markus A. Launer CoSiM Conference Proceeding (2024)

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Management

Entrepreneurial Mindset in a VUCA World

Laura Noel

Abstract

This research explored the relationship between intuitive decision-making and organizational

growth during the COVID-19 pandemic while examining the moderating effect of

entrepreneurial expertise within a volatile, uncertain, complex, and ambiguous (VUCA)

environment. Utilizing a quantitative methods design and the Rational Heuristic Intuition

Anticipation (RHIA) scale with 148 entrepreneurs, the study found no significant direct effect

of intuitive or analytical decision-making styles on organizational growth nor a moderating effect

of experience. However, specific facets of intuition, namely emotional intuition and anticipation,

were linked with higher organizational growth levels. The discussion of findings, limitations, and

directions for future research were addressed.

Keywords: Intuition, Expertise, Entrepreneurship, VUCA, Decision-Making

Introduction

Entrepreneurial Mindset in a VUCA World

In a world marked by increasing volatility and uncertainty, entrepreneurs face challenges that

demand more than just technical expertise; they require adaptive skills, particularly intuition,

to navigate effectively (Heifetz, 1994). Unlike technical challenges, which can be solved with

existing knowledge, adaptive challenges necessitate new learning and innovation, often

requiring a shift in values or perspectives. Leaders with heightened intuition can make informed

decisions even with incomplete information by drawing on their subconscious experiences.

Johansen (2017) emphasized the importance of developing intuitive competencies in a VUCA

(Volatile, Uncertain, Complex, and Ambiguous) world, where intuition enables leaders to

anticipate changes and adapt to disruptions. The COVID-19 pandemic further highlighted the

value of intuition, as entrepreneurs faced unprecedented challenges that demanded rapid,

intuitive decision-making to ensure business continuity and innovation (Sayegh et al., 2004;

Abraheem, 2023).

This research aims to explore the nuances of decision-making among entrepreneurs during

the pandemic, focusing on the balance between intuitive and analytical processes, and the

role of expertise as a moderating factor in decision-making and organizational growth.

Although decision-making in crises has been studied, the specific connection between intuitive

decision-making and entrepreneurial growth in a VUCA environment remains underexplored.

Markus A. Launer CoSiM Conference Proceeding (2024)

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Dual Process Theory, which distinguishes between fast, intuitive thinking (System 1) and slow,

analytical thinking (System 2), provides a framework for understanding this balance

(Kahneman, 2014). Previous studies, such as Simmons (2015), have highlighted the biases in

management literature that often favor analytical approaches, sidelining intuition. However,

Keller and Sadler-Smith (2019) propose that integrating Paradox Theory with Dual Process

Theory can help leaders leverage the tension between intuition and analysis, potentially

leading to more favorable outcomes.

Intuition plays a crucial role in decision-making, particularly in high-pressure situations where

quick judgments are necessary. It allows individuals to make decisions based on feelings, prior

experiences, or immediate perceptions without relying on conscious reasoning (Dijksterhuis et

al., 2006; Kahneman, 2014). Studies, like those by Pretz et al. (2014) and Polanyi (1958/2012),

highlight the diverse forms of intuition holistic, inferential, and affective—and how they integrate

various sources of tacit knowledge to guide decision-making. In complex environments, this

blend of intuition and analytical reasoning is vital for effective leadership (Keller & Sadler-

Smith, 2019).

Expertise significantly influences the effectiveness of intuitive decision-making. Research

shows that individuals with domain-specific experience, as outlined by Malewska (2019) and

Baldacchino et al. (2022), are more likely to leverage intuition effectively, thanks to their

accumulated knowledge and cognitive versatility. The "10-year rule" proposed by Ericsson &

Towne (2010) underscores the importance of extensive practice in developing world-class

expertise, which in turn enhances intuitive decision-making abilities in complex and uncertain

situations.

Organizational Growth within a VUCA environment is closely linked to the decision-making

style of entrepreneurs. Intuition, particularly strategic intuition, allows leaders to identify and

act on opportunities even amidst uncertainty, as discussed by Abraheem (2023). This research

aims to explore how intuitive decision-making, moderated by expertise, impacts organizational

growth, measured through financial, operational, and intangible metrics. Understanding this

relationship is key to navigating the challenges of a rapidly changing business landscape.

Summary of Hypotheses

For this study, the following hypotheses are proposed:

H1- Intuitive Decision-Making (IDM) will positively predict organizational growth in a VUCA

environment.

H2- Expertise will positively predict IDM.

H3- Expertise will moderate the relationship between IDM and growth in a VUCA environment

such that the relationship will be enhanced when expertise is high.

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Method

Participants

This survey targeted entrepreneurs who have owned a legal business entity recognized by the

country or state in which their company operates, operational since before January 2020.

Eligible participants were adults (18 years and above) working full-time within their business.

The study aimed for a sample size of at least 137 participants to detect a significant moderating

effect with an alpha of .05 and a power of .90, as recommended by Shieh (2009).

The present study included 148 respondents who revealed a diverse age range from 23 to 72

years, with a mean age of approximately 37.15 years and a median age of 35 years. The

participants also displayed a broad spectrum of professional experience, ranging from 1 to 55

years, with a mean experience of approximately 8.03 years and a median experience of 5

years. The demographic details of the 148 valid respondents (Table 1) showed that 64.9%

were male, 34.5% were female, and 0.7% identified as other or non-binary. A significant

number of participants held a bachelor’s degree at 62.8%, followed by 24.3% with a master’s

degree, 6.8% with a high school diploma or equivalent, and smaller percentages held other

academic or professional qualifications. The ethnic makeup was predominantly White or

Caucasian at 70.3%, with Asian or Pacific Islander at 21.6%, Black or African American at

3.4%, and the rest made up of other ethnicities. Industry representation spanned several

sectors, with technology leading at 23%, business services at 20.9%, advertising & marketing

at 8.8%, manufacturing at 8.1%, finance & financial services at 8.1%, retail at 6.8%, consulting

at 4.1%, healthcare at 4.1%, entertainment. & leisure at 3.4%, education at 2.7%, coaching at

2.7%, construction /machinery at 2%, transportation at 2%, network marketing at 1.4%,

hospitality at 1.4%, and others at 0.7%.

Procedure and Design

Participants were recruited through the snowball method of sampling through social media and

email posts with a direct link (see Appendix A) to the survey in Qualtrics. Participants provided

their informed consent (see Appendix B) before participating in the study. Participants were

also recruited through Amazon’s Mechanical Turk (MTurk) platform and compensated $1.00

per completed survey. MTurk participants provided their informed consent before participating

in the study. All participants completed screening questions and, if they were deemed ineligible,

were directed to the disqualification message, thanked for their time, and did not complete the

survey.

This study used a quantitative survey design and was administered through Qualtrics taking

approximately 15 minutes to complete. Participants completed 21 questions measuring

decision-making styles: Rational, Intuitive, Emotional, Spontaneous Heuristical, Slow

Unconscious, and Anticipation, as well as four demographic questions, one question related to

Markus A. Launer CoSiM Conference Proceeding (2024)

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experience, and six organizational growth questions. Participants received an electronic

debriefing and thank you for completing the survey.

Measures

The scale used for this survey was the Rational Heuristic Intuitive Anticipation (RHIA) scale, a

21-question, six-dimension, self-report questionnaire using a 4-point Likert scale ranging from

1 Strongly Disagree to 4 Strongly Agree (Launer & Svenson, 2020). The RHIA was tested for

reliability and was acceptable (α=.87).

Expertise: For this study, expertise was operationalized as the number of years of experience

as a business owner or entrepreneur.

Organizational Growth: For this study, organizational growth was operationalized as a

percentage of gross profits or losses. Other aspects of growth and losses were also

considered, including products or services offered, employees, locations, new clients, and net

profits or losses.

Demographics: Demographics were collected through four questions at the end of the.

Questions included information regarding age, gender, racial category, the highest level of

education, and the industry worked in.

Results

The purpose of this study was to explore the relationship between decision-making style

preference, entrepreneurial experience, and organizational growth from the start of the Covid-

19 pandemic until the present. The relationships among variables were analyzed using linear

regression and moderation analyses. H1 and H2 were tested using linear regression and H3

was tested using moderation. Survey data were downloaded from Qualtrics into IBM SPSS

Statistics (Version 29.0.2.0) and cleaned, including checking for missing data, naming

variables, and reverse-scoring as needed. Scale reliabilities were calculated using Cronbach’s

alpha.

IBM SPSS Statistics (Version 29.0.2.0) software was used to analyze the data to conduct linear

regressions to test the extent to which Decision-Making Style and Experience predict growth

in a perceived VUCA environment. Moderation analysis using PROCESS add-on in SPSS was

used to explore the relationship between IDM and growth as moderated by experience.

Descriptive analyses (e.g., mean, standard deviation, range) were used to analyze the

demographic variables. Finally, post hoc analyses were conducted to gain a deeper

understanding of the data.

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Hypothesis 1

For hypothesis H1, which posited Intuitive Decision-Making (IDM) would positively predict

organizational growth in a VUCA environment. The analysis revealed that IDM did not have a

significant predictive effect on organizational growth (β = 13, p = .12). Linear regression results

did not support H1 and indicated that IDM did not positively predict organizational growth in a

VUCA environment, R2 =.02, F(1,147) = 2.43, p = .12. Results indicated IDM explained 2% of

the variance in growth. In the context of this study, IDM may not directly contribute to

organizational growth in VUCA environments. Regression results may be found in Table 2.

Table 2: Linear Regression for Inductive Decision-Making Predicting Organizational Growth

Outcome variable B SE B

β

R2

Intuition 19.16 12.28 1.56 .02

Hypothesis 2

Similarly, for hypothesis H2, which suggested Expertise would positively predict IDM, the

results indicated a lack of significant relationship between Expertise and IDM (β = -.13, p =.13).

These findings imply that in the sample studied, Expertise did not significantly influence the

level of Intuitive Decision-Making. Linear regression results did not support H2 and indicated

that Experience did not positively predict IDM, R2 =.02, F(1,146) = 2.30, p = .13. Additionally,

results of the linear regression indicated expertise explained 2% of the variance in IDM. This

finding suggests that in the context of this study, entrepreneurial expertise may not directly

contribute to IDM. Regression results may be found in Table 3.

Table 3: Linear Regression for Inductive Decision-Making Predicting Organizational Growth

Outcome variable B SE B

β

R2

Experience −0.009 0.006 −0.13 .02

Hypothesis 3

Expertise will moderate the relationship between Intuitive Decision-Making (IDM) and

organizational growth in a VUCA environment, enhancing the relationship when expertise is

high. Hypothesis 3 was not supported and analysis did not reveal a significant moderating

effect of expertise on the relationship between IDM and organizational growth (β = -.38, p =

.85). This suggests that in the context of this study, expertise did not play a significant role in

Markus A. Launer CoSiM Conference Proceeding (2024)

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strengthening the relationship between IDM and organizational growth within VUCA

environments.

Moderated regression results of the interaction effect on organizational growth are show in

Table 4.

Table 4

Summary of Moderated Regression Results on Organizational Growth

Interaction effect B SE B t

p

Intuition 18.47 12.46 1.48 .14

Experience −0.37 0.87 −0.42 .67

Post Hoc Tests

Comparison of Means

Additional post hoc analysis was conducted to further explore the relationship between

organizational growth and decision-making style by performing a one tailed t-test. An

independent samples t-test was conducted to examine the differences in decision-making

between entrepreneurs who reported growth above the overall mean of organizational growth

and loss and those who scored below the mean (AORBMean). There was no significant

difference between the groups in rational or overall intuitive decision-making which included the

four intuition subscales, nor were there any significant differences between the groups in the

intuitive subscales which include the intuitive, slow unconscious and spontaneous heuristictical

subscales. There were significant findings within the intuitive subscales, emotional intuition and

anticipation & pre-cognition.

On average, the reported level of growth for entrepreneurs who exhibited more of the

emotional intuition (M = 3.2, SD = .60) was significantly higher than the level of emotional

intuition reported by entrepreneurs who experienced growth below the mean (M = 3.0, SD =

.64), t(146) = -1.74, p < .04, and this effect was medium, d = .3. Also, when considering another

output from the one tailed t-test and examining anticipation & pre-cognition, significant findings

were revealed. Entrepreneurs above the overall growth mean (M = 3.31, SD = .90) reported

higher levels of anticipation & pre-cognition intuition when compared to entrepreneurs who on

average earned less than the overall growth mean (M = 3.2, SD = .58), t(146) =1.8, p < .03,

and this effect was medium, d = .3.

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Factor Analysis

Exploratory factor analysis was conducted for the RHIA scale to uncover any underlying

structures within the data and instrument. IBM SPSS Statistics (Version 29.0.2.0) scale

reduction and principal component analysis were used in addition to varimax with Kaiser

normalization as the rotation method. Four factors were revealed, and cross-loaded items with

similar loadings were removed, leaving 15 of the 21 scale items remaining. The new factors

were tested for reliability. Further, the hypotheses were re-tested using regression and

moderation analysis using the new four factor structure and the findings were not significant.

Factor analysis results are shown in Table 6.

Discussion

The purpose of this study was to gain a deeper understanding of decision-making among

entrepreneurs to discern how much they relied on intuitive decision-making versus analytical

decision-making during a time when the world was faced with a collective adaptive challenge,

the COVID-19 pandemic. This research was conducted using a quantitative survey of

entrepreneurs to investigate the connection between decision-making style, organizational

growth, and entrepreneurial experience within an environment many believed to be a volatile,

uncertain, changing, and ambiguous (VUCA) environment. Overall, statistical analysis of the

RHIA scale, organizational growth, and years of entrepreneurial experience revealed findings

that support the connection between organizational growth and two types of intuitive decision-

making; however, the initial three hypotheses were not supported.

Interpretation of Results

It was hypothesized that overall Intuitive Decision-Making (IDM) would positively predict

organization growth in a VUCA environment where entrepreneurs who make decisions more

intuitively would experience a higher percentage of organizational gross profits. The results

showed no significant difference in predicting organizational growth between entrepreneurs

who make intuitive versus analytical decisions. It was also hypothesized that expertise, which

was calculated as years of entrepreneurial experience, would positively predict IDM and this

was also not supported in the analyses. The final hypothesis, which was that expertise will

moderate the relationship between IDM and growth in a VUCA environment such that the

relationship will be enhanced when expertise is high, was also not supported in the data.

Previous work by Malewska (2019) through interviewing 300 managers, found that one of the

determinants of when leaders engage in intuitive decision-making is expertise.

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Table 6 Summary of Exploratory Factor Analysis

Item (original factor) Factor

1 (α = .86) 2 (α = .79) 3 (α = .60) 4 (α = .65)

Anticipation

Precog 2 .74

Anticipation

Precog 4 .73

Anticipation

Precog 1 .72

Emotional Decisions 2 .71

Emotional Decisions 3 .69

Emotional Decisions 1

Quick Heuristic Dec 3

.66

.81

Quick Heuristic Dec 1 .79

Quick Heuristic Dec 2 .65

Rationality Delib 2 .68

Rationality Delib 5 .68

Rationality Delib 4

Slow Uncon Thinking 1

.66

.79

Slow Uncon Thinking 3 .74

Slow Uncon Thinking 2 .65

Abraheem (2023) investigated organizational performance during environmental uncertainty

and the role strategic intuition plays, where leaders leverage accumulated expertise and

insights. These previous studies highlighted leaders within organizations rather than

entrepreneurs. Additionally, expertise is acquired from specialized and quality practice within

a specific domain. Entrepreneurship, in general, may be too broad of a focus, and exploring

industry-specific entrepreneurial expertise is worth considering.

Post hoc analyses explored two distinct groups of entrepreneurs: those whose growth

surpassed the aggregate mean of organizational growth and those who did not. While there

were no significant differences in rational and overall intuitive decision-making styles between

the two groups, a notable difference emerged in two of the four intuitive subscales: emotional

intuition and anticipation & pre-cognition. Entrepreneurs who reported growth above the mean

demonstrated higher emotional and anticipatory intuition levels. Additionally, the average

growth rate for the group above the mean was 81%, whereas for those below the mean, it was

- 1.75%. These findings suggest different facets of intuition may play an essential role in

organizational growth, particularly when dealing with adaptive challenges where creative

Markus A. Launer CoSiM Conference Proceeding (2024)

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thinking and innovation are necessary, as indicated by previous research (Baldacchino et al.,

2022). Also interesting to note is that exploratory factor analysis combined the above-mentioned

intuition subscales into one factor. The results were similarly significant when t-tests were re-

conducted to test between the two growth groups.

Limitations

This study has a few limitations. First, it relied on self-reporting measures to assess gross

organizational growth or losses from January 2021 to the present as an approximate

percentage, which may have been challenging to recall. Also, some entrepreneurs reported a

percentage of growth and loss; a possible limitation could be that they have multiple businesses

and accounted for both losses and gains. Second was the combination of convenience

snowball sampling and entrepreneurs through MTurk who may have taken the survey without

reflecting on the survey questions due to a conflicting motivation of survey completion for

payment versus survey accuracy. The RHIA scale has been tested and validated in previous

studies in the European Union with employees in different industries. It was surprising to

experience a different outcome with the scale when it was deployed with entrepreneurs; this

may be a limitation or an opportunity to explore what differentiates entrepreneurs from

employees in this context to refine further and adapt the scale for entrepreneurs. Other

considerations to keep in mind during this period that may have contributed to growth are the

industry in which the businesses operate, whether or not they received government aid, which

may have helped keep businesses running, and how entrepreneurs experience their sense of

responsibility toward keeping their staff employed.

Future Research

The results of this study offer several possible directions for exploration. First, is further

exploration into the specific dimension of intuition and their role on organizational growth could

offer insights on the cognitive processes that drive success in entrepreneurship. Longitudinal

studies could explore or reveal the growth and evolution of intuitive capacities over time coupled

with the impact on business outcomes. Additionally, future studies could benefit from a much

more narrow scope by investigating industry-specific entrepreneurial expertise. Furthermore,

this research could include entrepreneurs globally, expanding the sample size and potentially

having a more global understanding of entrepreneurship in VUCA conditions. Finally, a

qualitative approach through case studies and interviews could provide an in-depth

understanding of entrepreneurs’ lived experience through VUCA conditions, how they made

decisions, and the outcomes they generated.

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Conclusion

The purpose of this study was to better understand the decision-making style of entrepreneurs

and organization growth outcomes in a VUCA environment. Also examined was the moderating

effect of expertise on the relationship and dynamic between decision-making style and

organizational growth. Further analyses were conducted to understand the data better. As

indicated by this study, there is a meaningful relationship between entrepreneurs who reported

higher levels of growth and those who exhibited higher levels of emotional and anticipatory

intuition. In contrast, those who did not experience growth showed significantly lower emotional

and anticipatory intuitive decision-making levels. This study contributes to the literature on

decision-making, entrepreneurship, and intuition.

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Peculiarities of the Human Resources Development in State Authorities of

Ukraine

Tetiana Balanovska

1)

, Oksana Havrysh

1)

, Krystyna Dramaretska

1)

and

Barbara Wyrzykowska

2)

1) National University of Life and Environmental Sciences of Ukraine, Orcid No. 0000-0001-

6814-5888, 0000-0002-5756-0880, and 0000-0002-9886-1663

2) Warsaw University of Life Science, Orcid No: 0000-0002-7025-0799

Abstract

Purpose. In the context of the implementation of the administrative reform in Ukraine, issues

of modernization of the civil service, a component of which is raising the professional level of

civil servants, are gaining priority. Thus, the purpose of the study is to carry out a

comprehensive analysis of the process of human resources professional development in state

authorities of Ukraine, as well as to determine possible directions for improving the

qualifications of civil servants to acquire the necessary competencies.

Design/methodology/approach. When processing of individual underlying data and formulating

conclusions of the paper were used methods of analysis, synthesis, induction, deduction

comparative and the graphic method.

Findings. The analysis of the indicators of the modern civil service shows that in Ukraine there

is a trend towards the development of professionalism and professional competence of the

civil servants, their work is used rationally, and motivation to study increases.

Practical implications. The research carried out by the authors makes it possible to determine

the peculiarities of the human resources development in state authorities of Ukraine, which will

contribute to the timely systematization of data on the need to improve the qualifications and

professional competencies of civil servants in accordance with modern requirements.

Social implications. The results of the research, which are covered in the paper, provide

information about the importance of continuous professional development of civil servants, and

can also attract the attention of those who plan to hold positions of civil servants in the future.

Originality/value. The authors established that in modern conditions, it is important to use

innovative approaches to the professional development of a civil servant in Ukraine. The article

examines the peculiarities of drawing up and implementing an individual professional

development program of a civil servant, which records individual needs in professional training,

and is a tool for planning the professional development of a civil servant.

Keywords: development, professional development, human resources, state authorities, civil

servants, competence.

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Introduction

In today's conditions of accelerated informatization of society, global innovation processes,

strengthening of the innovative content of work, the professional development of human

resources is becoming more and more important.

The problem of professional development of the personnel of state authorities in Ukraine

became extremely important with the adoption of the Law of Ukraine "On Civil Service" dated

December 10, 2015 No. 889-VIII (Law, 2015), the Law of Ukraine "On Education" dated

September 9, 2017 No. 2145-VIII (Law, 2017), as well as for their implementation, "On

Approval of the Concept for Reforming the System of Professional Training of Civil Servants,

Heads of Local State Administrations, their First Deputies and Deputies, Local Self-

Government Officials and Local Councils Deputies", approved by Ordinance of the Cabinet of

Ministers of Ukraine dated December 1, 2017 No. 974-r (Ordinance, 2017).

It should be noted that in the Strategy for Public Administration Reform in Ukraine for 2022-

2025, approved by Ordinance of the Cabinet of Ministers of Ukraine 21 July 2021 No. 831-r

(Ordinance, 2021), among the tasks regarding human resource management capacity and

organizational culture for the implementation of the "Professional Public Service and Human

Resource Management" direction, the implementation of a program of continuous professional

development for employees of human resource management services regarding modern

practices and management tools is highlighted. In the Strategy (Ordinance, 2021) is also

writing about promoting the formation of effective mechanisms for motivating civil servants to

professional development and continuous education. The formation of a new model of the

system of professional training of civil servants is an integral component of public

administration reform, because the successful implementation of public administration reform

depends on the professionalism of persons authorized to perform the functions of the state or

local self-government, which implies a constant increase in the level of their professional

competence (Aliushyna et al., 2021).

Human resource professional development of state administration authorities of Ukraine is an

important tool for maintaining an effective system of state administration, especially in times of

war. New conditions dictate new challenges, and everyone must learn to respond to them.

Literature Review

Humans are the most valuable resources of modern society. The development and efficiency

of both organizations and the country as a whole depends on them. It is human intelligence,

knowledge and creativity that move technologies, business processes, and social spheres

forward, which confirms the impossibility of effectively using and developing other resources

without qualified specialists (Pham Kien Thi and Dung Bui Xuan, 2022).

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As Yan Yue (2014) notes, "Human resource management is an important constituent part of

enterprise management. Scientific and reasonable management of human resources

concerns implementation of enterprise development strategy, enterprise survival and long-

term development".

According to Gilley J. W. et al. (2002), "Human resource development is understood as the

process of promoting organized learning, improving work performance, and creating changes

through the implementation of management solutions (official and non-official), initiatives and

activities to enhance organizational capacity, performance, competitiveness and innovation".

According to Morozov and Honchar (2017), human resource development is a continuous

process aimed at improving the quality characteristics of employees. This allows not only to

increase the efficiency of the organization in the short and long term, but also contributes to

the harmonious development of the employees themselves. The key aspects of human

resource development are: acquisition of new knowledge and skills necessary for effective

performance of current and prospective tasks, increasing motivation and involvement of

employees in the organization's activities, formation of loyalty and commitment to the

organization. Thus, human resource development is an important strategic direction of human

resources management, which allows to reveal and effectively use the potential of employees

and ensure long-term competitiveness of the organization.

Tkachenko and Marchenko (2014) define the human resource professional development as a

purposeful and systematic influence on employees through the implementation of professional

training during their work in the organization with the aim of achieving high efficiency of

production or services provided, increasing the competitiveness of personnel on the labor

market, ensuring compliance employees of new, more complex tasks based on the maximum

possible use of their abilities and potential. The goal of human resource development of any

organization is to provide it with well-trained employees in accordance with the goals and

development strategy.

Based on the critical analysis and generalization of scientific opinion, scientists (Semykina et

al., 2021) propose to define the essence of the concept of "human resource professional

development" using a dual approach: a) at the organization level – as a set of measures that

ensures continuous updating of professional knowledge and skills of human resources, its

adaptation to growing professional requirements, interest in professional growth in the interests

of intensification of innovative activities and increasing the competitiveness of the enterprise;

b) at the employees level – as a process of continuous development of professional

competences based on a combination of self-development with professional training,

increasing self-motivation to implement innovative goals of the organization (Semykina et al.,

2021).

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Polish authors distinguish various classifications of possible employee development projects.

Taking into account these classifications, it should be stated that they include such elements

as: knowledge, skills, abilities. There are three main groups of employee development

instruments, namely: vocational training and improvement of qualifications; employee

relocations; work structuring (Wyrzykowska & Karbowiak, 2009).

Human resource development is a process that includes: knowledge enrichment – training,

professional development, acquisition of new competencies; development of skills and abilities

– improvement of professional and personal skills of employees; formation of motivation –

creation of conditions that stimulate employees to work effectively and improve themselves;

taking care of physical and mental health – measures to support health, reduce stress,

increase job satisfaction. These components make it possible to increase the human capital

of individual employees, and therefore the value of the human capital of the entire organization.

The main projects aimed at the human resources development can be considered at three

levels: 1. The entire organization; 2. Separate work teams; 3. Individual employees (Król,

2014).

Human resource development is one of the task areas of the personnel function and is of

interest to both employers and employees. Activities in the field of human resource

development should create optimal opportunities for employees' professional development,

corresponding to the goals of the organization, and therefore bring benefits to both parties of

the employment relationship. It can be implemented based on various strategies and using

various tools, including training, employee relocation or career shaping. Human resource

development is often perceived in terms of investment (Oczkowska, 2014).

Human resource development is a process strongly involved in the development and

subsequent use of human knowledge, taking into account the issue of dynamic individual and

organizational changes. Human resource development is a very extensive field of practice and

a relatively young scientific discipline (Swanson, 2023).

Human resource development is the engine that can provide the necessary competencies to

develop teamwork, problem and process analysis, communication and other needed

capabilities (Michael & Viwe, 2009).

McLean and Wang (2007) offer a definition of human resource development as a complex

process that includes: the accumulation of knowledge, skills and abilities of people in society (it

is investment in human capital, which contributes to economic development); preparing people

for active participation in political processes, especially in a democratic society (human

resources development expands the opportunities of citizens); promoting social and cultural

development, which help people to lead a more fulfilling and rich life, less tied to traditions. In

general, the human resource development is a key factor in the modernization of society,

opening up new opportunities for personal and social progress (McLean & Wang, 2007).

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It should be noted that the issue of human resource development, including professional

development is also dedicated the works of Chapman Elizabeth F. et al. (2018); Dreifelde I.

and Zakrizevska Belogrudova M. (2021); Marzec Izabela and Austen Agata. (2021); Poell Rob

F. and Van der Krogt Ferd J. (2014); Bhaskar P. et al. (2021); Goncharuk N. et al. (2021);

Kachan Y. (2019); Bilan Y. et al. (2023).

Scientists note that effective human resource management is key to achieving state goals and

ensuring the well-being of citizens. Human resources management in the public sector should

be based on the principles of openness, accountability and focus on meeting the needs of

citizens (Chapman et al., 2018).

Drucker (2007) draws attention to six factors that influence the productivity of intellectual

workers, particularly in public administration. Key factors include: the employee's

understanding of the essence of the task and the goals that must be achieved (a clear

understanding of the goal and tasks increases the motivation and focus of the employees'

efforts); willingness to participate and make an intellectual contribution to management

processes (involvement of employees in decision-making and policy-making increases their

involvement and initiative); the opportunity to constantly learn and develop (providing

conditions for professional growth and self-realization is an important incentive for intellectual

employees); the choice of quality methods of work evaluation (a fair and transparent system

of evaluation of the work results helps to increase efficiency); working conditions and the

internal culture of the organization (a favorable working environment focused on creativity and

innovation has a positive effect on productivity). It is worth noting that the specifics of public

administration, in particular the limitations and priorities formed by the political and

administrative system, can form certain features in the implementation of these factors. This

is important to consider when developing effective human resource management mechanisms

in the public sector (Andris, 2010).

According to the normative legal acts of Ukraine (Law, 2015) and (Resolution, 2019),

professional development is a continuous, conscious, purposeful process of personal and

professional growth, based on the integration of knowledge, skills and competencies;

professional training – acquisition and improvement of professional knowledge, abilities and

skills, which ensures the appropriate level of professional qualification of a civil servant for his

professional activity.

Research Findings

According to the National Agency of Ukraine on Civil Service (NAUCS) (NAUCS, 2022), in

Ukraine as of June 30, 2023, the actual number of working civil servants was 163 553, of which

41 143 were men and 122 410 were women, 206 civil servants were of category "A", 41 767

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– of category "B" and 121,580 – of category "C" (NAUCS, 2022). The number of civil service

positions according to the staff list as of June 30, 2023 was 206 206 staff units, in particular

category "A" – 283, category "B" – 49 482 and category "C" – 156 441 staff units. 11 108

people are on parental leave, of which 125 are men. The number of people who went abroad

as of June 30, 2023 was 2 691 people (at the end of 2022 – 4 355 people), most of whom are

women – civil servants of category "B". There are 3 946 civil servants serving in the Armed

Forces of Ukraine, of which 3 301 are men and 645 are women (NAUCS, 2022).

Civil servants of the state authorities of Ukraine constantly increase their level of professional

competence during their service.

The reform of the professional training system ensured the introduction of many innovations in

this field and the development of an innovative training model for civil servants, heads of local

state administrations, their first deputies and deputies, local self-government officials and

deputies of local councils, which is aimed at continuity, obligation, planning, practical

orientation, predictability of training and compliance with the needs of its participants (Strategy,

2023).

Table 1: Quantitative and qualitative composition of employees of state authorities of

Ukraine, as of June 30, 2023*

Indicator Categories of positions In total

A B C

The number of positions

according to the staff list

283

49482

156441

206206

The actual number of

employees, persons

206 41767 121580 163553

Occupied positions, % 72.79 84.41 77.72 79.32

Note. *Calculated by: (NAUCS, 2022).

The organizational principles of the professional training system functioning of the public

authorities employees are determined by the Resolution of the Cabinet of Ministers of Ukraine

"On Approval of the Regulation on the System of Professional Training of Civil Servants, Heads

of Local State Administrations, their First Deputies and Deputies, Local Self-Government

Officials and Deputies of Local Councils" dated February 6, 2019 No. 106 (Resolution, 2019).

According to this Resolution, civil servants undergo advanced training at least once every three

years. The need for professional training of a civil servant is determined by his immediate

supervisor and the human resource management service state authority based on the results

of evaluation of official activity.

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Professional training of civil servants is carried out through the system of educational

institutions, agencies, organizations, regardless of the form of ownership, which have the right

to provide relevant educational services, and is carried out at the expense of state and local

budgets, other sources not prohibited by law.

The structure of the professional training system includes: customers of educational services

in the field of professional training; subjects of the provision of educational services in the field

of vocational training (providers) and self-regulatory professional associations (professional

associations, professional networks) of subjects of the provision of educational services in the

field of vocational training (providers) (Resolution, 2019).

Based on the results of professional training, civil servants and local self-government officials

are awarded ECTS credits, which are subject to accounting maintained by human resource

management services. Civil servants within the scope of implementation of individual programs

and officials of local self-government must collect at least one ECTS credit during the calendar

year. Civil servants can exercise their right to professional training through the forms shown in

Fig. 1.

Fig. 1. Forms of professional training of civil servants

Note. Developed by: Resolution, 2019

According to the Resolution of the Cabinet of Ministers of Ukraine (Resolution, 2019), the

amount of self-education among other types of professional training within the scope of the

Forms of professional training of civil servants

Preparation – successful completion by

participants of professional training of

the appropriate educational and

professional program, which is the basis

for awarding a degree of higher

education at the master's level in the

specialties necessary for professional

activity in the civil service and service in

local self-government bodies, in

particular, in the specialty 281 "Public

Management and Administration» field

of knowledge "Public management and

administration"

Improvement of qualifications – acquisition by

participants of professional training of new

and/or improvement of previously acquired

competences within the limits of professional

Internship – acquisition by the participants of

professional training of practical experience in

performing tasks and duties in a professional

Self-education – self-organized acquisition of

certain competencies by participants of

professional training, in particular during

everyday activities related to professional,

social or other activities, leisure

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implementation of an individual program should be at least 10 and no more than 20 percent of

the total number of ECTS credits received according to the results of the program execution.

According to the results of self-education for a civil servant the ECTS credits are accrued in

the prescribed manner of NAUCS.

Professional training of civil servants can be carried out through self-education in the form of

online learning on educational web platforms, participation in conferences, scientific and

practical conferences, professional seminars, trainings, master classes, courses on mastering

practical skills, etc. (Fig. 2).

Fig. 2. Online services for training within the framework of self-education

Note. Developed by: NAUCS, 2023

PROMETHEUS

- Psychology of people during the war:

how to live and work in new realities;

- Information hygiene. How to recognize

lies in social networks, on the Internet and

on television;

- Disinformation: types, tools and

methods of protection;

- Information wars;

- Remote work for public servants.

EDUCATIONAL HUB

- Internet security;

- First aid;

- Modern Ukrainian language;

- Critical thinking and information culture;

- Time-management in public

administration;

- Anti-crisis management in public

administration.

DIGITAL EDUCATION

- Cyber fraudsters;

- Basics of cyber hygiene;

- Cybernetics;

- Personal data;

-

Safety of children on the Internet.

YOUTUBE

- Internal communications in wartime: a lecture

about HR;

- How to motivate and empower a team during

war;

- Psychological assistance during the war;

- How to organize the work of employees during

martial law?

- As increase the effectiveness of remote work;

- Critical thinking during war;

- How to find inner strength during war;

- Emotions of war;

- Home medical assistance in wartime

conditions for civilians;

- A series of webinars "Reality without Illusions"

from the UCU Business School and the UCU

Leadership Center about crisis leadership,

resilience, limited resources, actions of business

and HR specialists in unstable times.

OUM ONLINE

- First psychological aid in emergency and crisis

situations;

- Information security in the digital world;

- Digital security and online communication;

-

Volunteer teams: dream or reality.

ONLINE SERVICES FOR TRAINING WITHIN FRAMEWORK OF SELF-EDUCATION

EDERA (EDUCATIONAL ERA)

- Specialized course for civil servants and

persons who work with personal data;

- Dialogues without anxiety. An online

course on various ways to overcome

anxiety;

- Factcheck: trust-check.

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Blagovesna Yovkova and Roumiana Peytcheva-Forsyth (2023) emphasize that a large-scale

digital transformation of continuous education is observed all over the world, including in state

administration at all levels, through the implementation of various forms of e-learning.

Advanced training of civil servants is carried out according to programs, which are divided into

general and special according to the content of training (Fig. 3).

Fig. 3. General and special programs for improving the qualifications of civil servants

Note. Developed by: Resolution, 2019

According to the Procedure for evaluating the results of official activities of civil servants

(Resolution, 2017), on the basis of the tasks and key indicators defined for the civil servant,

the needs for professional training (if they are determined), as well as based on the results of

the evaluation of the civil servant's official activity (if available), such civil servant together with

the human resource management service draws up an individual promotion program level of

professional competence/individual program of professional development. An individual

program is drawn up within no later than ten working days after defining the tasks and key

indicators for the civil servant (Resolution, 2017). An individual professional development

program is a document that defines the individual needs of a participant in professional

training, the form and types of such training (Resolution, 2019).

Improving the qualifications of civil servants

General professional development programs, the

content of which includes:

-general issues of state administration and local

self-government;

-issues of prevention the corruption;

-changes in legislation on civil service, service in

local self-government bodies;

-issues of European and Euro-Atlantic

integration;

-issues of ensuring equal rights and opportunities

for women and men;

-ensuring cyber security;

-increasing the level of mastery of a foreign

language, which is the official language of the

Council of Europe, the state language;

-other issues determined by relevant state,

regional, local programs and strategies.

Special training programs, the content of

which are:

-covers the issues of the

implementation of tasks, functions and

powers by a separate state authority

(authorities), local self-government

authority (authorities),

-takes into account the peculiarities of

the performance by the participants of

professional training their official duties in

the relevant field of professional activity.

Markus A. Launer CoSiM Conference Proceeding (2024)

Page 29

The normative principles of drawing up an individual professional development program are:

- Law of Ukraine "On Civil Service" (Law, 2015);

- Resolution of the Cabinet of Ministers of Ukraine "On Approval of the Regulation on

the System of Professional Training of Civil Servants, Heads of Local State

Administrations, their First Deputies and Deputies, Local Self-Government Officials and

Deputies of Local Councils" dated February 6, 2019 No. 106 (Resolution, 2019);

- Resolution of the Cabinet of Ministers of Ukraine "On Approval of the Procedure for

Conducting an Evaluation of the Results of Civil Servants Activity" dated August 23,

2017 No. 640 (Resolution, 2017);

- Order of the NAUCS "On the Approval of Methodological Recommendations for

Compiling, Reviewing and Monitoring the Implementation of an Individual Program for

Increasing the Professional Competence Level of a Civil Servant (Individual

Professional Development Program)" dated October 26, 2020 No. 201-20 (Order,

2020);

- Order of the NAUCS "On Amendments to the Methodological Recommendations for

Compiling, Reviewing and Monitoring the Implementation of an Individual Program for

Increasing the Professional Competence Level of a Civil Servant (Individual

Professional Development Program)" dated December 14, 2022 No. 131-22 (Order,

2022).

The individual program is recommended for the purpose of planning the professional

development of a civil servant, aimed at acquiring and improving his professional knowledge,

abilities and skills, which ensure the appropriate level of professional qualification for his

professional activity in the position held in accordance with the established job duties.

Professional training needs are defined in the form of professional competences that must be

acquired or improved by a civil servant.

The individual program is drawn up by the civil servant together with the human resource

management service based on the results of the evaluation the official activity of civil servant

(if available) during the evaluation interview (if conducted) by the civil servant together with the

person who conducts the evaluation interview in accordance with clauses 23, 39 of the

Evaluation Procedure, the needs of professional training for the next year are discussed and

determined, taking into account the results of such civil servant's performance of the approved

tasks and key indicators in the reporting period.

The form of individual professional development program is provided by the annexes to the

Evaluation Procedure.

The individual program of a civil servant who holds a civil service position of category "A" is

approved by the person who determined the tasks and key indicators for such civil servant

(clause 20-1 of the Evaluation Procedure). The individual program of a civil servant who holds

Markus A. Launer CoSiM Conference Proceeding (2024)

Page 30

a civil service position of category "B" or "C" is agreed by the direct manager of such civil

servant and approved by the head of the independent structural unit in which he works (if

available) (clause 34-1 of the Evaluation Procedure) (NAUCS, 2023).

When drawing up the individual program of a civil servant, it is recommended to take into

account the needs of professional training, determined by the results of the evaluation the

official activity of civil servant, tasks and key indicators for the next year and requirements (Fig.

4).

In the Methodological Recommendations for Compiling, Reviewing and Monitoring the

Implementation of an Individual Program for Increasing the Professional Competence Level of

a Civil Servant (Individual Professional Development Program), approved by the order of the

NAUCS dated October 26, 2020 No. 201-20 (Order, 2020) stated that it is recommended to

monitor the implementation of the individual program in order to ensure proper implementation

of the individual program by the civil servant.

Fig. 4. Requirements for drawing up an individual program of professional development of a

civil servant,

Note. Developed by: NAUCS, 2023 & Order, 2020

Requirements that must be taken into account when drawing up an

individual program of professional development of a civil servant

mandatory advanced training for civil servants under general and/or special

professional (certificate) programs: first appointed to a civil service position within a

year from the date of their appointment; who hold civil service positions, at least once

every three years;

mandatory advanced training for civil servants under general and/or special short-term

programs at least once every three years;

the need for a civil servant to collect at least one ECTS credit during the calendar year

within the implementation of an individual program;

setting the share of self-education among other types of professional training within the

implementation of an individual program of 0.1 - 0.2 ECTS credits, unless otherwise

provided by the Regulation on the system of professional training.

In 2023, the share of self-education within the implementation of an individual program

may amount to no more than 0.5 ECTS credit.

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It is recommended to monitor the performance of an individual program by a civil servant of

category "B" or "C" by the immediate head together with the civil servant, with subsequent

informing of the human resource management service about the results of such monitoring.

In the case of direct subordination of a civil servant to the head of the civil service, such

monitoring is recommended to be carried out by the human resource management service the

relevant state authority.

According to the results of the summarization of individual programs, every year no later than

December 20, state bodies send the NAUCS information about the professional training needs

of civil servants who hold civil service positions of categories "B" and "C", and no later than

January 15 – copies of individual programs for improving the level of professional competence

civil servants holding civil service positions of category "A".

In 2023, NAUCS and specialists of the PO "Ukrainian Institute of Social Research named after

Oleksandr Yaremenko " with the assistance of the Norwegian Center for Integrity in the

Defense Sector (CIDS) conducted a study of organizational culture "Public service in Ukraine:

your point of view". The research was implemented using an anonymous online survey, in

which 43 862 public servants participated, including 39 557 civil servants and 4 305 local

government officials, who answered most of the survey questions and provided personal

information about gender, age, seniority and had a contradiction in the declared work

experience and age. The study made it possible to find out how public servants evaluate the

prerequisites for professional growth – personal and of their colleagues. Respondents rate

their own qualifications the highest. Almost all respondents (94.3%) "fully agree" or "agree"

with the assessment thesis that their qualifications, professional training and acquired

education are sufficient for the current job (Fig. 5).

Almost half (42.4%) of the respondents "fully agree" with the thesis that their qualifications and

acquired education are sufficient to perform the current job, and this is a high indicator. On the

one hand, this assessment by public servants of their own professional knowledge and skills

gives rise to optimism about the prospects for their growth as specialists. On the other hand,

excessive self-confidence, overestimation of one's own capabilities can become an obstacle

on the way to self-improvement, restrain the demand for new knowledge.

The sufficiency of the existing qualifications and education for the performance of job duties

was indicated more often (compared to the average indicator) by respondents who have a PhD

degree ("fully agree" or "agree" – 98.1%). A similar indicator is significantly lower than the

average among novice employees with one year of work experience and less (86.3%), among

employees with a bachelor's degree or less (89.4%). In other words, the representatives of the

specified groups show the need for advanced training and additional education.

If the respondents characterize their own qualifications and education very positively, then the

dynamics of professional growth are assessed more modestly. Among all respondents, 78.9%

Markus A. Launer CoSiM Conference Proceeding (2024)

Page 32

"fully agree" or "agree" with the assessment thesis "I grow professionally while working in my

public authority". In comparison, beginning employees with one year of work experience or

less describe their own professional growth at their place of work more positively (85.7%

somewhat agree with the thesis). However, respondents with higher work experience are more

critical of their own progress.

Three quarters (77.5%) of respondents somewhat agree with the assessment that " My public

authority takes care of the professional development of its employees".

At the same time, 7.7% of respondents "do not agree at all" or "disagree" with the evaluation

thesis.

Fig. 5. Distribution of respondents answers to the question: "To what extent do you agree or

disagree with this statement?"

Source: Analytical report NAUCS, 2023

Respondents with a scientific degree are the most critical of how institutions take care of the

professional development of their employees. Among respondents with a candidate of science

degree, 11.5% somewhat disagree with the stated thesis, and among doctors of science –

10.6% of respondents. 80.3% of respondents "fully agree" or "agree" with the thesis "Public

servants feel that training and development are important components of their work". The rest

My qualifications, professional training, acquired

education are sufficient to carry out the current job

I grow professionally while working in my public

authority

Public servants feel that training and development

are important components of their work

My public authority takes care of the professional

development of its employees

The body of public authority promotes the fact that

different structural units exchange experience and

learn from each other, and even involve the best

practices of different organizations

42,4

25,1

23,9

22,4

16,3

51,9

53,8

56,4

55,1

48,7

4,3

14,1

13,6

14,8

22,4

1,2

5,5

4,6

5,5

9,4

0,2

1,5

2,2

3,2

Fully agree Agree Neither agree nor disagree Disagree Do not agree at all

Markus A. Launer CoSiM Conference Proceeding (2024)

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of the respondents are not so sure about this. The awareness of the importance of training is

especially positively assessed by novice employees with less than a year of work experience

(85.8%), as well as employees with a bachelor's degree or lower (86.3%). These respondents

broadcast their own interest (request) in training to their colleagues.

Public servants are the most restrained in their assessment of how experience exchange and

implementation of best practices are carried out at their place of work. Two-thirds (65.0%) of

the respondents somewhat agree with the thesis "The body of public authority promotes the

fact that different structural units exchange experience and learn from each other, and even

involve the best practices of different organizations". A significant share (12.6%) of the

respondents gave negative answers – somewhat disagreed with this assessment. Critical

assessments were most often expressed by young employees aged 20–35, as well as

respondents with a doctor of science degree. Therefore, the implementation of best practices

does not always meet the required level, and the mutual exchange of experience is an urgent

request of public servants.

In 2023 the medium-term forecast indicators of the general needs for professional training of

the participants of professional training (hereinafter – general needs for professional training)

for 2024-2026 have been determined by the NAUCS (Report, 2023).

The generalized needs of civil servants, officials of local self-government, first deputies and

deputy heads of local state administrations in the preparation of masters in the specialty "Public

Management and Administration" for 2024-2026 amount to 8 531 people. The analysis of the

needs for the training of masters in the specialty "Public Management and Administration" for

2024-2026 (see Fig. 6) indicates a decrease in the volume of such needs from 3 347 people

in 2024 to 2 537 people in 2026.

The needs for improving the qualifications of participants in professional training under general

professional (certificate) and short-term programs (hereinafter – general programs) for 2024-

2026 amount to 785 187 people, of which: under general professional (certificate) programs –

166 804 people; under general short-term programs – 618 383 people.

The "top-5" most priority areas of professional development for civil servants and local self-

government officials have been determined by the NAUCS (Fig. 7). The "top-5" priority areas

account for 51.7% of the total volume of civil servants needs for advanced qualifications under

general short-term programs.

Markus A. Launer CoSiM Conference Proceeding (2024)

Page 34

Fig. 6. Needs for the preparation of master's degrees in the specialty "Public management and

administration" for 2024-2026 by categories of professional training participants, persons,

Sourc: Report, 2023

Fig. 7. Top-5 areas of professional development according to the general short-term programs,

persons, Source Report, 2023

2024

2025

2026

509

357

351

1156

1001

983

353

279

282

1293

973

881

36

37

40

Heads of Local State Administrations, their First Deputies and Deputies

Local Self-Government Officials

Civil servants of local state administrations

Civil servants of territorial bodies of state authorities

Civil servants of state authorities

communication and interaction

improving the level of mastery of the state

language

digital literacy

change management

cyber security

75927

71220

65878

55913

50877

2537

person

2647

person

s

3347

person

s

8531

persons

Markus A. Launer CoSiM Conference Proceeding (2024)

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It should be noted that advanced training programs must meet the criteria of modernity,

innovation, be relevant and provide answers to practical requests of participants. Currently,

training programs on behavior in crisis situations and development of leadership qualities are

becoming more relevant.

In the Strategy (Strategy, 2023), approved by the Coordination Council at the National Agency

of Ukraine on Civil Service defined the goals and objectives of the development the system of

professional training of public servants for the period 2024-2027.

Ordinance of the Cabinet of Ministers of Ukraine dated December 27, 2023 No. 1206-r

approved the plan of measures for the development of the system of professional training of

civil servants, heads of local state administrations, their first deputies and deputies, officials of

local self-government and deputies of local councils until 2027 (Ordinance, 2023).

The main focuses of the government ordinance are: digitization of services and management

processes in the field of professional training; increased attention to the quality of professional

development of public servants; ensuring the inclusiveness of the professional training system;

regular assessment of the status of professional training system (according to the system of

management indicators) and monitoring of the quality of professional training; development of

professional competences of public servants in matters of preventing the emergence of threats

and the onset of crisis situations; introduction of mobility programs for the internship of civil

servants abroad; learning foreign languages, in particular summer/winter English-language

schools for civil servants; dialogue meetings with representatives of international and foreign

institutions, organizations, specialists in the field of public service and adult education (Plan,

2024).

The training of public servants should be aimed at acquiring and improving modern

professional competencies necessary for the post-war recovery and development of Ukraine,

building a capable service and digital state.

Conclusions

An important role in ensuring the successful operation of state authorities is played by the

development of human resources, which should be carried out systematically and aimed at

achieving certain goals. As a result of the analysis of the scientific literature, it was established

that the development of human resources is a process that includes a set of measures for

improving the knowledge and behavior of employees related to professional activity, using a

wide range of professional training methods to ensure the goals of the organization, and for

growth professional competencies of employees based on self-development.

Vocational training is a necessary component of human resources development, which helps

civil servants acquire and improve professional knowledge, abilities and skills, which ensures

the appropriate level of their professional qualifications for professional activities. Taking into

Markus A. Launer CoSiM Conference Proceeding (2024)

Page 36

account modern conditions, a special role among the forms of professional training of civil

servants belongs to online services for training within the framework of self-education.

The vast majority of civil servants to some extent positively characterize the prerequisites for

professional growth: having the knowledge and skills necessary for the performance of work,

personal progress in the professional plan at the workplace, awareness of the need for training

by colleagues, the availability of experience sharing practice, creation of conditions in the

organization for professional development as a whole.

Public servants’ high assessment of their own professional knowledge and skills gives rise to

optimism about the prospects for their growth as specialists. At the same time, it is important

to have an objective assessment of the suitability of the knowledge and skills of employees to

the tasks facing the organization. It was determined that the most priority areas of professional

development for civil servants and local self-government officials include: cyber security,

change management, digital literacy, improving the level of mastery of the state language,

communication and interaction.

The experience of developing human resources in the state authorities of other countries, in

particular Poland, can be useful for maintaining the capacity and functionality of the civil service

of Ukraine. The study of the peculiarities of the training of civil servants in developed countries,

the mutual exchange of experience is an urgent request for the development of decisions

regarding the modernization of the professional development of civil servants in Ukraine.

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Economic Bulletin of Donbass, 1 (35), 94–97.

Wang, Shuguang, & Zhao, Shuyang. (2021). Transformation and strategic development of

human resource management in public sector under digital economy. Proceedings of

the 2021 6th international conference on social sciences and economic development

(ICSSED 2021). https://www.atlantis-press.com/proceedings/icssed-21/125955020

Wyrzykowska, B., & Karbowiak, K. (2009). Kierowanie zasobami ludzkimi w organizacji

[Management of human resources in the organization]. Warsaw, SGGW, p 119.

Yue, Yan. (2014). Human resource management under enterprise strategic perspective.

International Conference on Education, Management and Computing Technology

(ICEMCT 2014), 100, 185–189. https://www.atlantis-press.com/proceedings/icemct-11

Zbrytska, T., Savchenko, H., & Tatarevska, M. (2013). Management of human resource

development. Responsible editor Tatarevska, M. Odesa: Atlant.

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Exploring Workplace Mental Health Amid Digital Transformation: A

Management Science Overview

Mustapha Ahmimid and Said Balhadj

Abdelmalek Essaadi University, Morocco, Orcid No. 0000-0002-8523-7415

Extended Abstract

The adoption of digital technology and its effects on mental health have increasingly drawn

attention from researchers worldwide, particularly within the field of management. The

intersection of these two pivotal concepts, digitalization and mental well-being, is the central

theme of this manuscript. In an era marked by rapid technological advancements,

understanding the implications of digital transformation on employee mental health has

become crucial for organizations striving to maintain productivity and a healthy workforce.

Context: This study aims to synthesize both empirical and theoretical research on the

integration of digital technologies in organizational settings and their impact on mental health.

Our goal is to provide an in-depth overview of the current state of knowledge, identify key

trends, and highlight the challenges and opportunities associated with the digitalization of the

workplace. The review focuses specifically on the period between 2010 and 2022,

encompassing 43 manuscripts from Scopus-indexed journals. These studies offer a robust

basis for understanding the complex relationship between digital technology adoption and

employee well-being.

The economic landscape has significantly changed with the rise of digital technologies,

transforming industries and organizations globally. As businesses increasingly adopt digital

tools for communication, work processes, and management, the workforce is confronted with

new challenges related to stress, anxiety, and job demands. While the potential benefits of

digitalization—such as increased efficiency, remote work flexibility, and data-driven decision

making—are undeniable, they also introduce new risks to mental health, particularly in relation

to technostress and burnout. This juxtaposition between the benefits and challenges forms the

critical backdrop for the ongoing conversation about digital transformation and employee well-

being.

Methodology: To address this issue, we conducted a literature review following a rigorous

protocol. Our primary objective was to analyze existing research published in well-regarded,

Scopus-indexed journals. Using a comprehensive search strategy across multiple databases,

including Google Scholar, Science Direct, and Scopus, we applied Boolean operators to

identify relevant studies on the adoption of digital technologies and their impact on mental

health in organizational settings.

The search terms used included:

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 ("digital technology adoption" OR "digital transformation") AND ("mental health" OR

"psychosocial risks") AND ("management" OR "workplace well-being")

 ("digital technology" AND "workplace stress") OR ("technostress" AND "employee well

being") AND ("organization" OR "management science")

 TITLE-ABS-KEY(("digital technology" OR "digital transformation") AND ("mental health"

OR "psychosocial well-being") AND ("management" OR "organizational behavior"))

 The final selection included 43 peer-reviewed articles, which were thoroughly analyzed to

synthesize findings and identify key patterns.

Results: Our analysis revealed several important themes and insights into the relationship

between digital technologies and mental health in organizational settings. A key finding is the

prominent role of mobile applications designed to help employees manage mental health

issues, particularly anxiety and technostress. These digital tools are becoming increasingly

popular for offering real-time support and monitoring, but their effectiveness varies depending

on individual preferences and technological fluency.

Furthermore, we found that the benefits of digital technologies—such as enhanced flexibility,

remote work opportunities, and improved access to information—are tempered by the

challenges they pose to employee well-being. The phenomenon of technostress, or stress

caused by the overuse of technology, has emerged as a significant concern. Employees,

especially those without proper training or support, can experience heightened anxiety and

feelings of overload due to constant connectivity and the pressure to adapt to ever-changing

digital tools.

The study also underscores the importance of organizational strategies for mitigating these

challenges. Companies that implement digital literacy training, provide mental health

resources, and establish boundaries for technology use after working hours are better

equipped to support their employees' well-being. These findings suggest that organizations

must take proactive steps to balance the advantages of digital transformation with the mental

health needs of their workforce.

Conclusion: The adoption of digital technology in the workplace presents both opportunities

and challenges for employee mental health. While these technologies can enhance

productivity and improve work-life balance, they also introduce new risks related to stress,

anxiety, and burnout. Our review highlights the importance of developing comprehensive

strategies to manage these risks, including training, mental health support, and clear

boundaries around technology use. Future research should continue to explore how

organizations can foster a healthy digital work environment that maximizes the benefits of

technology while safeguarding the well-being of employees.

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Key Words: Digital technology, mental health, workplace stress, technostress, digital

transformation, organizational behavior, systematic review.

References

Sun, J., Shen, H., Ibn-ul-Hassan, S., Riaz, A., & Domil, A. E. (2022). The association between

digitalization and mental health: the mediating role of wellbeing at work. Frontiers in

Psychiatry, 13, 934357.

Sanchez-Segura, M. I., Dugarte-Peña, G. L., Medina-Dominguez, F., Amescua Seco, A., &

Menchen Viso, R. (2023). Digital transformation in organizational health and safety to

mitigate Burnout Syndrome. Frontiers in Public Health, 11, 1080620.

Palumbo, R., & Cavallone, M. (2024). Is work digitalization without risk? Unveiling the psycho

social hazards of digitalization in the education and healthcare workplace. Technology

Analysis & Strategic Management, 36(6), 1136-1149.

Trenerry, B., Chng, S., Wang, Y., Suhaila, Z. S., Lim, S. S., Lu, H. Y., & Oh, P. H. (2021).

Preparing workplaces for digital transformation: An integrative review and framework

of multi-level factors. Frontiers in psychology, 12, 620766.

Tan, C. H., Koo, A. C., Rahmat, H., Siew, W. F., Cheang, A. W. O., & Sharji, E. A. (2023).

Workplace wellness, mental health literacy, and usage intention of E-mental health

amongst digital workers during the COVID-19 pandemic. International Journal of

Mental Health Promotion, 25(1), 99-126.

Sharma, S., López-Fernández, A. M., & Sharma, M. (2023). Digital Transformation and

Academicians’ Well-being: A Cross-National Study. Global Business Review,

Mache, S., & Harth, V. (2020). Digital transformation in the world of work and mental health.

Zentralblatt für Arbeitsmedizin, Arbeitsschutz und Ergonomie, 70, 180-184. -

Vázquez, I. G., Curtarelli, M., Anyfantis, I., Brun, E., & Starren, A. (2024).

Digitalisation and

workers wellbeing: The impact of digital technologies on work-related psychosocial

risks (No. 2024-03). Joint Research Centre.

Lee, B. W., Darmadi, D., Gardanova, Z., Kostyrin, E., Gilmanova, N., Kosov, M., & Pozdnyaev,

A. (2024). Impact of Digital Transformation on Mental Healthcare: Opportunities,

Challenges, and Role of AI Chat-bots in Symptom Management. Emerging Science

Journal, 8(4), 1440-1461.

Lee, B. W., Darmadi, D., Gardanova, Z., Kostyrin, E., Gilmanova, N., Kosov, M., & Pozdnyaev,

A. (2024). Impact of Digital Transformation on Mental Healthcare: Opportunities,

Challenges, and Role of AI Chat-bots in Symptom Management. Emerging Science

Journal, 8(4), 1440- 1461.

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Exploring the Role of Culture in Leadership Styles and Deviance Credit

Batuhan Özkanlı

Loughborough University, United Kingdom, Orcid ID: 0009-0006-2262-9039

Purpose

In the 20th Century, Geert Hofstede's Theory of Cultural Dimensions (1984) established a

foundational framework for understanding how culture influences various phenomena,

including leadership. Since then, it has become a crucial tool for cross-cultural research,

especially in areas like management and decision-making, where cultural values significantly

shape organizational behaviour (Gelfand et al. 2017). One key dimension identified by

Hofstede is the distinction between individualism and collectivism, which provides insight into

how people from different cultures prioritize personal versus group goals. Regarding the group

orientation of one culture, assumptions can be made, and conclusions can be drawn about the

characteristics of the society. Fox (2010) argues that there are discrepancies in the dimensions

of caregiving, communication, identity, education, work life, task orientation and many others.

Given the statuses of the societies in these dimensional spectrums, one can assume that this

might be the case for the organizations inside those societies to be governed by similar

principles because they are operated by people whose perspectives on work life and

leadership were influenced by that society since they were born. This study aims to extend our

knowledge by examining the connection between cultural orientation (Individualism vs.

Collectivism) and preferred managerial leadership styles (Autocratic vs. Democratic) in two

distinct countries: the United Kingdom and Türkiye with the nuanced theoretical support of a

recently developed concept called Deviance Credit.

Theoretical Framework

The concept of Deviance Credit, developed by Abrams et al. (2018), introduces a fresh

perspective on how followers perceive and tolerate deviations from expected behaviour by

leaders. It suggests that leaders may accumulate “credit” through their adherence to

workgroup norms with their prototypicality (Accrual) and their right to be supported from the

followers’ perspectives as a leader, which is mainly about how well they can fill the leadership

role (Conferral). In this line of thinking, this perspective is reprised of the leadership status and

stereotypes. These mechanisms of Accrual and Conferral in turn allows them to engage in

actions that might otherwise be viewed as non-conforming, allowing leeway for them when

leaders try to innovate by implementing change or behave transgressive. These levels

increase as the leader become a more model member of the group and is invested to the role.

With the effect of leadership stereotypes members assume that the leader is more competent

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than other members merely due to the occupation of the leadership position. (Lord & Hall,

2003) Demonstrating that these concepts contribute to the leader’s ability to deviate is

particularly important because it helps us comprehend the underpinnings of the thought

processes of members to make change happen. In addition, it builds on the previous

knowledge we have on in-group dynamics and how individuals in groups respond to each other

in cases of deviance thereby, advancing the Social Psychology and Management literatures.

This concept also aligns closely with the theme of intuitive management, as it highlights the

subtle, often unconscious judgments that followers make about their leaders’ behaviour, based

on their cultural expectations and the leadership style in place.

Methodology and Results

This study hypothesizes that the leadership style favoured by a given culture will grant more

deviance credit to leaders practicing that style. Specifically, we explored the relationship

between cultural orientations of individualism (as seen in the UK) and collectivism (as seen in

Türkiye) and the preference and allocation of deviance credit to autocratic versus democratic

leaders which are presented through leadership vignettes created by Kolorov (2018) for

Harvard Business Review. Through surveys which are the Leadership Preference Scale

(Bhushan, 1995) and Deviance Credit Scales (Abrams, 2018) given to participants from both

countries (52 participants each), we found that, regardless of cultural orientation, participants

were more inclined to prefer and grant deviance credit to democratic leaders over autocratic

ones. This challenges the assumption that collectivist cultures, which emphasize group

harmony and authority, would be more tolerant of autocratic leadership. Similarly, participants

from the society with individualistic tendencies showed a clear preference for democratic

leaders, as they valued transparency, shared decision-making, and accountability.

Furthermore, considering those democratic leaders who involve their team in decision-making

processes suited the leadership position better than the autocratic leader according to the

perspective of the individualistic participants, they granted them more deviance credit.

Additionally, in both conditions democratic leaders were evaluated highly both on competency

and willingness to work for the leader.

Discussion and Conclusions

These findings have several implications for intuitive management and decision-making. First,

they suggest that cultural expectations for leadership styles can influence not only explicit

judgments but also more subtle, intuitive assessments of leader behaviour. Managers who

understand and align their leadership style with the preferences of the workgroup they are

leading independent of the cultural predisposition may be granted more leeway in their

decision-making processes, even when deviating from established norms. Second, the

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preference for democratic leadership across both individualistic and collectivistic cultures

points to a shift in global leadership values which gets increasingly visible over the years,

where participative and inclusive decision-making is favoured (Yukl, 2013).

Furthermore, the concept of deviance credit highlights how followers' intuitive judgments can

affect a leader's capacity to implement unconventional or risky decisions. This aligns with

research on intuitive decision-making, which emphasizes how managers rely on tacit

knowledge and culturally grounded assumptions when making choices in uncertain situations

(Hodgkinson & Sadler-Smith, 2018). Leaders who are attuned to the expectations of their

teams may be more successful in navigating complex and dynamic environments, leveraging

their deviance credit to make bold, innovative decisions without facing backlash.

In conclusion, this study contributes to the literature on leadership and cross-cultural

management by exploring the intersection between cultural dimensions and the emerging

concept of deviance credit. The findings suggest that, regardless of cultural orientation,

democratic leadership is increasingly associated with greater tolerance for deviation, providing

leaders with more flexibility in their decision-making processes. This has significant

implications for intuitive management practices, where understanding and leveraging cultural

expectations can enhance leadership effectiveness in diverse organizational settings. Future

research could explore how these dynamics play out in other cultural contexts, dimensions

and examine the long-term impact of deviance credit on leadership success.

Key Words: leadership, leader deviance, leader transgressions, deviance credit, cultural

dimensions, individualism-collectivism, intuitive management, decision-making, innovation,

United Kingdom, Türkiye, cross-cultural management.

References

Abrams, D., Randsley de Moura, G., Travaglino, G. A., & Marques, J. M. (2018). Deviance

credit: Tolerating leaders' (non-)normative behavior depends upon group identification

and social impact. Journal of Experimental Social Psychology, 78, 13-28.

Bhushan, L. L. (1995). Leadership preference as related to age, education, residence and sex.

Indian Journal of Social Work.

Gelfand, M. J., Aycan, Z., Erez, M., & Leung, K. (2017). Cross-cultural industrial organizational

psychology and organizational behavior: A hundred-year journey. Journal of Applied

Psychology, 102(3), 514-529. https://doi.org/10.1037/apl0000186

Hodgkinson, G. P., & Sadler-Smith, E. (2018). The dynamics of intuition and analysis in

managerial and organizational decision making. Academy of Management

Perspectives, 32(3), 473-492.

Hofstede, G. (1984). Culture's Consequences: International Differences in Work-Related

Values. SAGE Publications.

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Kolorov, K. (2018). Recognizing leadership styles. Harvard Business Review.

Lord, R. G., & Hall, R. J. (2003, January 1). Identity, leadership categorization, and leadership

schema. ResearchGate.

Yukl, G. (2013). Leadership in Organizations (8th ed.). Pearson.

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The Growth of Indian Aquaculture

Er. Safaljot Singh

1

and Jasveen Kaur

2

1) Business Development Consultant, India

2) Guru Nanak Dev University, India, Orcid No. 0000-0001-6793-1000

Introduction

India's agricultural and aquaculture sectors have undergone significant transformations

through various revolutions. The Green Revolution of the 1960s increased food grain

production through high-yielding variety seeds and modern farming techniques, ensuring food

security. The White Revolution, initiated in 1970, revolutionized the dairy industry, making India

the largest milk producer globally. Building on these successes, the Blue Revolution, launched

during the Seventh Five-Year Plan (1985-1990), aimed to enhance fish production, and

modernize the fisheries sector through advanced aquaculture techniques, sustainable

practices, and improved infrastructure.

The Indian aquaculture market reached a size of 13.4 million tons in 2023 and is projected to

grow to 26.4 million tons by 2032, with a compound annual growth rate (CAGR) of 7.97%

during 2024-2032. Key regions such as South India, particularly Andhra Pradesh and Tamil

Nadu have emerged as key regions due to favourable climatic conditions and extensive coastal

areas. East India, with states like West Bengal and Odisha, also plays a significant role,

especially in freshwater fish production. Emerging regions include Gujarat and Maharashtra in

the west for brackish water aquaculture, and the Indian Sundarbans, are also being recognized

for their potential in coastal aquaculture.

The Indian aquaculture market is characterized by a diverse range of species, including

shrimp, carp, and catfish. Domestic consumption is driven by increasing health consciousness

and dietary shifts towards protein-rich foods. The market dynamics are influenced by factors

such as consumer preferences, regulatory policies, and technological advancements. The

sector is also witnessing consolidation, with larger players investing in vertically integrated

operations to achieve economies of scale and improve supply chain efficiency.

Methodology

The aquaculture sector in India has emerged as a pivotal component of the nation's economy,

contributing significantly to Food security, Employment, and Exports. This paper aims to

provide a comprehensive analysis of the current state of this Sunrise Sector, focusing on its

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economic impact, sustainability, technological innovations, government subsidiary schemes

and investment opportunities. The data sources include literature review and the opinions of

several academicians/researchers.

Discussion

Economic Impact

Aquaculture in India has shown remarkable growth, becoming a major source of income for

coastal and rural communities. The sector contributes approximately 1% to the national GDP

and provides employment to over 25 million people. The economic benefits extend beyond

direct employment, influencing ancillary industries such as feed production, processing, and

logistics. The multiplier effect of aquaculture on the local economy underscores its importance

in regional development and poverty alleviation.

Today, Norway and China are among the top 3 countries in terms of Aquaculture exports with

India being the 5th largest global exporters of aquaculture products, with shrimp being the

primary export commodity. The export market is buoyed by strong demand from the United

States, European Union, and Southeast Asia. However, the sector faces challenges such as

stringent quality standards, trade barriers, and competition from other exporting countries.

Enhancing export potential requires addressing these challenges through improved quality

control, certification, and compliance with international standards. In 2023, India's aquaculture

exports were valued around 8 billion USD, with shrimp exports accounting for more than half

of the total export value and around 75% export quantity.

Sustainable and Technological Practices

Sustainability in aquaculture is crucial to ensure long-term viability and environmental health.

Indian aquaculture faces challenges such as water pollution, overfishing, and habitat

destruction. However, there has been a significant shift towards adopting sustainable

practices. These include the use of Biofloc Technology (BFT), Integrated Multi-trophic

Aquaculture (IMTA), and organic farming methods. Sustainable practices not only mitigate

environmental impacts but also enhance the quality and marketability of aquaculture products.

As of 2023, approximately 20% of the aquaculture farms in India have integrated BFT into their

operations with productivity and reduction in water consumption being key drivers. The

adoption of IoT in aquaculture is revolutionizing the industry by enabling real-time monitoring

and management of aquaculture operations. IoT devices such as sensors and automated

feeders provide critical data on water quality, temperature, and feed usage. This data-driven

approach enhances productivity, reduces waste, and ensures optimal growing conditions. The

integration of IoT also facilitates traceability and transparency, which are increasingly

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demanded by consumers and regulators. As of 2023, approximately 15% of aquaculture farms

in India have integrated IOT based technologies which has led to enhanced monitoring,

automation and data driven decision making to ultimately improve productivity and

sustainability.

Government Subsidiary Schemes and Investment Opportunities

Following the examples of countries like Saudi Arabia which has directed a large amount of

their Sovereign Fund (PIF) towards the agenda of Food Security as part of Saudi 2030 Vision,

the Indian government has also launched several initiatives to support the growth of the

aquaculture sector. The Pradhan Mantri Matsya Sampada Yojana (PMMSY) is a flagship

scheme with an investment of INR 20,050 crore for the period 2020-2025, aiming to increase

fish production by 7 million metric tons and boost exports to USD 12 billion. Additionally, the

Fisheries and Aquaculture Infrastructure Development Fund (FIDF), with a fund size of INR

7,522.48 crore, provides concessional finance for creating fisheries infrastructure. These

schemes are expected to create 5.5 million additional employment opportunities and

significantly enhance the sector's infrastructure.

Apart from the economic potential, Indian government’s motive to boost aquaculture through

its policies is rooted in supporting many of the sustainability development goals outlined by the

United Nations. Key SDGs outlined is SDG 1 (No poverty), SDG 2 (Zero Hunger), SDG 8

(Decent Work and Economic Growth), SDG 12 (Responsible Consumption and Production),

SDG 14 (Life Below Water) and SDG 15 (Life on Land).

Conclusion & Implications:

The Indian aquaculture sector holds immense potential for growth and development. By

integrating economic impact, sustainable practices, market dynamics, export potential,

advanced technologies like IoT, and government support through subsidiary schemes and

investment opportunities, the industry can achieve sustainable and inclusive growth. Strategic

interventions and policy support are essential to address challenges and harness

opportunities, ensuring that Indian aquaculture continues to thrive in the global market. The

continued evolution from traditional practices to modern, technologically driven approaches

will be key in positioning India as a global leader in this Sunrise Sector.

Keywords: Indian aquaculture market, economic impact, sustainability, technological

innovations, government subsidiary schemes and investment opportunities.

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References:

https://economictimes.indiatimes.com/industry/banking/finance/livestock-aquaculture-

sectors-in-india-need-more-insurance-coverage-swiss-re-

report/articleshow/48774472.cms.

https://economictimes.indiatimes.com/small-biz/sme-sector/blue-economy-focusing-on-

fisheries-sector-for-optimum-growth/articleshow/81043454.cms.

https://inc42.com/resources/how-tech-innovation-is-reshaping-aquaculture-in-india/.

https://link.springer.com/article/10.1007/s43621-024-00457-2.

https://link.springer.com/chapter/10.1007/978-3-030-96519-8_7.

https://link.springer.com/chapter/10.1007/978-3-031-21644-2_24.

https://link.springer.com/content/pdf/10.1007/978-3-031-21644-2_24.pdf?pdf=inline%20link.

https://link.springer.com/referenceworkentry/10.1007/978-3-031-32671-4_20-1.

https://research-portal.st-andrews.ac.uk/en/publications/challenges-and-opportunities-in-

achieving-sustainable-mud-crab-aq.

https://timesofindia.indiatimes.com/india/india-plans-policies-to-boost-blue-economy-and-

explore-arctic-region-for-energy-and-climatic-research/articleshow/81102795.cms.

https://www.business-standard.com/article/economy-policy/livestock-aquaculture-industries-

need-easy-accessible-insurance-services-swiss-re-115090200583_1.html.

https://www.drishtiias.com/daily-updates/daily-news-editorials/india-s-blue-economy-

potential.

https://www.drishtiias.com/daily-updates/daily-news-editorials/maximising-the-benefits-of-

india-s-blue-economy.

https://www.pwc.in/assets/pdfs/grid/agriculture/championing-the-blue-economy-promoting-

sustainable-growth-of-the-fisheries-sector-in-india.pdf.

https://www.pwc.in/ghost-templates/championing-the-blue-economy-promoting-sustainable-

growth-of-the-fisheries-sector-in-india.html.

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Algebraic System as Key Concept of Textual Data Analysis of Change

Management

Averkyna Maryna

1)

and Tabur Lauri

2)

1) Lviv Polytechnic National University, Ukraine, Orcid No. 0000-0002-1517-6434

2) Estonian Academy of Security Sciences, Estonia, Orcid No. 0000-0001-5357-6239

Extended Abstract

Organizations and managers of Ukraine faced to the problems find out clear solution in order

to overcome obstacles under wartime condition. It was observed that managers tried to solve

issues more quickly, but the responses were generally disorganized. These situations have

proved the necessity to have alternative scenarios or a base of precedent decisions for further

future development. The creation base of precedent decisions requires clear information about

potential case solving.

In times of crisis or change, this situational leadership approach becomes paramount. By

actively supporting individuals and facilitating their engagement, managers can mitigate fears

and uncertainties, fostering a conducive environment for change implementation. Such as the

current situation must be described, Lauri Tabur has proposed the next approach (see table

1).

Table 1. The Example Case Solving by a Group of Ukrainians

CASE About a Company and Its Real Situation in Ukraine During The War:

///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

FEAR MITIGATION ACTIVITY

1. ///////////////////////////////////////// 1. /////////////////////////////////////////////

2. //////////////////////////////////////// 2. /////////////////////////////////////////////

3. //////////////////////////////////////// 3. ////////////////////////////////////////////

4. //////////////////////////////////////// 4. ///////////////////////////////////////////

……………………………….. ……………………………………

n. ///////////////////////////////////////// n. ////////////////////////////////////////////

n+1. //////////////////////////////////////// n+1. //////////////////////////////////////////

KEY FIRST STEPS TO TAKE TO SUCCESSFULLY LAUNCH THE CHANGE:

1. ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////.

2. //////////////////////////////////////////////////////////////////////////////////////////////////////////////////.

3. //////////////////////////////////////////////////////////////////////////////////////////////////////////////////.

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……………………………………………………………………………………….

n. ////////////////////////////////////////////////////////////////////////////////////////////////////////////////

n+1. ///////////////////////////////////////////////////////////////////////////////////////////////////////////

It is crucial to highlight the importance of the table proposed by Lauri Tabur for structuring the

process of case resolution. This tool enables participants to comprehend each step and its

sequence, thereby facilitating effective problem-solving. Organizational leaders can adopt this

approach to alleviate employees' fears, particularly in crisis situations characterized by time

constraints. By providing a structured framework, this approach empowers individuals to

contribute their ideas and perspectives to issue resolution, thereby avoiding hasty or irrational

decisions.

Furthermore, this approach is applicable across organizations of varying sizes, from small

businesses to medium-sized enterprises and large corporations. Its versatility lies in its ability

to promote collaboration and systematic problem-solving, irrespective of organizational scale

or complexity.

Many basic concepts, tools and results of the theory of algebraic systems are suitable in order

to form the theoretical basis for supporting decision-making process of change management.

In the theory of algebraic systems, a system is called an ordered pair

A=〈M; Σ〉 (1)

in which on the first place is the set of some selected and fixed element M. We will call the

elements of the set M – the elements of the system under consideration, or in short –

selements. In such a case, the set M itself is often called the basic set or the main set of the

system, instead of which we will use the name selementry below.

in second place is strugementry Σ or the set of instruments necessary for structuring the set of

selementry. In accordance with the above, the instruments necessary for structuring

selementry, or hereinafter – strugements are: pre-selected and fixed properties of the

selements and/or pre-selected and fixed relationships between selements.

We assume that each situation in an organization an algebraic system as ordered pair

〈M; Σ〉 where on the first place must be the selementry or the set (M) of the elements of the

system and on the second – strugementry or the set of the strugements of the system.

Every situation – as a system – of the organization (fears, fears’ mitigation, key first steps to

take to successfully launch the change) is described by numerous statements. We use the

Lorents’ coefficient to assess the similarity of situations as systems. To calculate this

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coefficient, we have to choose which components of one system we want to equalize with

some components of another system (and which we do not). Here we see a significant

difference between the Lorents coefficient and the Jaccard coefficient - the calculation of the

Jaccard coefficient (see Jaccard 1901) is based on the same elements, but in the case of the

Lorents coefficient the equalized elements are used [2]. Once the choice has been made, a

numerical ratio must be found which expresses the proportion of things to be equalized to the

sum of all the components of both systems.

We propose to compare the cases’ statements of one set with similar groups’ statements

another set. It helps us to create the data set of fears’ mitigation during the War. We propose

include coefficient similarity (Sim (P, Q)) in strugementry.

In order to evaluate the descriptive similarity of the descriptions or sets of relevant statements

– that is, the descriptive similarity of some things, situations, developments, etc., we will use

the numerical value defined by Lorents below - the descriptive similarity coefficient:

Sim (P,Q) = E(Com(P,Q)):[E(P) – E (Com(P,Q)) + E (Q)] =

= E(Com (P,Q)):[E(Spec(P)) + E (Com(P,Q)) + E (Spec(Q))] (1)

According to this formula, it is first necessary to make descriptions of both sets, which must

consist of relevant statements. At the next stage, it is necessary to clarify what statements

from one and another description can be considered equivalent. Such a declaration of

equivalence is here in after referred to as equalization, and the corresponding statements are

equalized. There are now three sets of statements:

- P is a set whose elements are statements from the first description;

- Q is a set whose elements are statements from another description;

- E is the number of elements;

- Com(P, Q) is a set of elements that are ordered pairs, where the first position of the

pair has the statements P, the second position has the statement Q, and these

statements have been equalized by each other.

- Spec(P) is a set so-called specific statements that appear in the first description but do

not have equivalent ones in the second description;

- Spec(Q) is a set of so-called specific statements that appear in the second description

but do not have equivalent ones in the first description).

Based on this approach, we will analyse the obtained textual data in order create the basic for

the decision-making process with precedent decisions.

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References

Averkyna, M. (2021). ‘Theoretical Aspects of the Local Government’s Decision-Making

Process’. In: Ahram, T.Z., Karwowski, W., Kalra, J. (eds) Advances in Artificial

Intelligence, Software and Systems Engineering. AHFE 2021. Lecture Notes in

Networks and Systems, vol 271. pp. 107−115. Springer, Cham.

https://doi.org/10.1007/978-3-030-80624-8_14

Averkyna, M. (2023). ‘Situation similarity calculus-based modelling of decision-making

processes in Urban transportation management’. Doctoral Thesis in Management,

Estonian Business School, Tallinn, 2023.

Lorents, P.; Averkyna, M. (2019). ‘Some Mathematical and Practical Aspects of Decision-

Making based on similarity’. In: Stephanidis C. (eds) HCI International 2019 – Late

Breaking Papers. HCII 2019. Lecture Notes in Computer Science, Vol 11786. Springer,

Cham., https://doi.org/10.1007/978-3-030-30033-3_13, 2019.

Maltsev, A.I. (1970). Algebraic systems. Science. Moscow, 1970.

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Strategic Imperatives of the national Economies’ Competition

Mykola Pasichnyi and Anton Nepytaliuk

State University of Trade and Economics, Ukraine

Abstract

The purpose of this work is to assess the interdependencies between economic growth,

competition, and innovation and to conceptualize the complex measures for stimulating

innovative development.

Theoretical Framework

As economic phenomena, both competition and innovation determine and shape the business

entities' modus operandi. Theoretically, in the long run, market competition could be and

should be capable of maximizing the respective economic agents' benefits. Meanwhile, the

aforementioned agents' anti-competitive intentions and unfair practices prompt respective

institutional counteractions. In the most radical cases, competition forces authorities to impose

anti-monopoly policies (aimed to ensure general fairness and optimal economic performance

as well). Thus, the competition's ontological aspects form an essential object for investigation.

Moreover, its initial idea derives from the architectonics of public production and innovation par

excellence. Innovation is commonly considered as a trigger for both market competition and

sustainable development. However, the exact model of strategic interconnection between

competition and innovation depends on the national economy's institutional peculiarities and

is determined historically.

Regarding the period from 2007 to 2022, we considered the sample of Central European

countries and the Baltic states. The interdependencies between macroeconomic dynamics

and a set of competition and innovation indicators have been assessed.

Methodology

We focused on a sample of national economies that made their transition from centralized

planning to the market in the 1990s. The national economies of Bulgaria, Croatia, the Czech

Republic, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, Slovakia, Slovenia,

and Ukraine were investigated.

According to the Wicksell / Cobb–Douglas productive function, labor (as a proxy to human

capital) and physical capital are imperfect substitutes. That fact could be roughly described by

the system (1):

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















,

1

0

1

0











KLAY

(1)

where Y – annual total production; L – annual labor input; K – annual capital input; A – total

factor productivity; α and β – the output elasticities of capital and labor, respectively.

Due to the classical explanation, both α and β values are the constants and has been

determined by the modern technological paradigm. Meanwhile, in social and economic

systems, synergy matters essentially. Pasichnyi & Nepytaliuk (2021) pointed out that not only

positive, but also the other (negative and neutral) synergistic effect should be considered while

preparing strategic public regulation measures. The above effect derives from the

interconnections emerging between the basic public production elements. To determine total

factor productivity, we applied a function of the above interconnection’ arithmetic sum

(model 2):

,

1

















n

i

EP

f

A (2)

where EPi – emergent potential of the i-th interconnection between the basic public production

elements.

Regarding the scientific investigations addressing the problem, the system elements

interconnection’s emergent potential (model 3) derives from respective innovation and

competition potentials:





,, CP

IP

f

EP i

ii  (3)

where IPi and CPi – innovation and competition potentials of the investigated macroeconomic

system elements’ interconnection, respectively.

In this study, we decomposed the system elements interconnection’s emergent potential and

refined the economic growth-friendly public policy mix.

Results

We compared the real GDP per capita growth rates in the sampled countries and the structure

of public production (Figure 1).

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Figure 1. The average proportion of medium and high-tech industry value added in the total

value added of manufacturing and the average economic growth rates in Central Europe and

the Baltic states in 2007–2022. (Source: the authors’ own calculation based on the World Bank

and the International Monetary Fund data)

Regarding the real GDP per capita growth rates, the entire sample could be divided into three

sub-samples. Firstly, the sub-sample of the countries with a low indicator ranged from –0.55%

in Ukraine to 1.87% in Estonia (the group included the Czech Republic and Slovenia).

Secondly, the sub-sample of the countries with a medium indicator ranged from 2.12% in

Croatia to 2.73% in Slovakia (the group included Hungary and Latvia). Finally, the sub-sample

of the countries with a high indicator ranged from 3.38% in Bulgaria to 3.91% in Poland (the

group included Lithuania, Moldova, and Romania). The global financial instability and the

COVID–19 pandemic affected the sample, provoking a decline that has been equaled to 7.63%

and 3.67% of real GDP per capita in 2009 and 2020, respectively.

The case of Ukraine has been unique for the entire sample. In addition to the Great Recession

and the COVID–19 global pandemic consequences, hybrid and eventually conventional war

affected the Ukrainian economy in 2014 and 2022, respectively. Due to the Great Recession’s

impact, the aforementioned indicator’s annual decline equaled to 14.76% of real GDP per

capita. Meanwhile, due to the full-scale military invasion, the growth rates decreased by

17.13% of real GDP per capita. In the post-war period, theoretically, innovation and constant

search for competitive advantages in co-operation with the other sampled economies could

ameliorate the Ukrainian economy’s performance and contribute to a substantial increase in

public welfare.

Regarding the entire period, Poland was the only sampled country with constantly growing

economy. An insufficient decline (equaled to 1.85% of real GDP per capita in 2020) appeared

to be episodic and derived from the COVID–19 global pandemic. Moreover, during the Great

Bulgaria

Croatia

Czech Republic

Estonia

Hungary

Latvia

Lithuania

Moldova Poland

Romania

Slovakia

Slovenia

Ukraine

-1,50

-0,50

0,50

1,50

2,50

3,50

4,50

10,00 15,00 20,00 25,00 30,00 35,00 40,00 45,00 50,00 55,00 60,00

GDP per capita growth (annual %)

Medium and high-tech manufacturing value added (% manufacturing value added)

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Recession, the Polish economy has been rising by 4.19% and 2.76% of real GDP per capita

in 2008 and 2009, respectively. The observed phenomenon has been due to an effective policy

mix (applied by the Government of Poland) and to innovation (provided by the business

entities).

The stochastic interrelation between the above two indicators was rather ambiguous. The

average proportion of medium and high-tech industry value added in the total value added of

manufacturing varied significantly from 14.80% in Moldova to 54.87% in Hungary. Moreover,

considering the entire time interval, the average economic growth rate in Moldova equaled to

3.62% and has been significantly higher than in Hungary (with the indicator equaled to 1.87%).

Thus, the investigated proportion was quite important, yet not the ultimate criterion for ensuring

high economic growth rates and sustainable development.

Discussion and conclusion

Despite the results obtained by García-Sánchez et al. (2018, 2021), regarding the sample, the

relationship between innovation, competition and prosperity has been rather ambiguous than

statistically robust. Even though innovation contributed to economic development and global

competition, its overall effect should be investigated properly. The idea of Hermundsdottir &

Aspelund (2021, 2022) that sustainability innovations might create win-win situations for a firm

could be considered regarding the national economy as well. At the last case, a growth-friendly

fiscal policy mix should be applied to promote sustainable growth.

In terms of human intellectual capital formation, it is important to apply a new recognition

approach to non-formal professional and vocational education. The business community

should initiate, form and develop innovation and technology clusters, taking both national

economy's regional structure peculiarities and fiscal jurisdictions' profile into account. The

other crucial task for the economies under study is associated with the investment and

innovation ambassadors' concept implementation. Compiling the rules of fair competition, such

economic agents could catalyze regional development processes and actively affect the labor

market.

Businesses, institutions of higher education, and scientific centers should co-operate

intensively to create a new growth-friendly economic paradigm. The aforementioned

cooperation could include support of scientific and pedagogical personnel participation in

international conferences and symposia, direct business financing of applied studies and co-

financing of fundamental research. In addition, the practices of registration, promotion,

protection, and support of intellectual property rights (e.g., patents, copyrights, trademarks,

brands, etc.) should be enriched. Theoretically, the above policy mix could be able to ensure

sustainable economic growth both in the medium term and in the strategic perspective.

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Keywords: competition, economic growth, high-tech economy, innovation, investment,

sustainable development, taxes, research and development expenditures.

References

García-Sánchez, A., Siles, D., & de Mar Vázquez-Méndez, M. (2021). Competitiveness and

innovation: effects on prosperity. In Tourism Research in Ibero-America (pp. 35–48).

Routledge. http://dx.doi.org/10.17265/2328-2185/2018.05.006.

García-Sánchez, A., Siles, D., & de Mar Vázquez-Méndez, M. (2018). Innovation,

competitiveness and prosperity: A factor analysis of innovation indicators in Spain.

Management, 6(5), 375–383. https://doi.org/10.17265/2328-2185/2018.05.006.

Hermundsdottir, F., & Aspelund, A. (2021). Sustainability innovations and firm

competitiveness: A review. Journal of Cleaner Production, 280, 124715.

https://doi.org/10.1016/j.jclepro.2020.124715.

Hermundsdottir, F., & Aspelund, A. (2022). Competitive sustainable manufacturing-

Sustainability strategies, environmental and social innovations, and their effects on firm

performance. Journal of Cleaner Production, 370, 133474.

https://doi.org/10.1016/j.jclepro.2022.133474.

Pasichnyi, M., & Nepytaliuk, A. (2021). The Contributions of Demographic Factors to

Economic Growth. Problemy Ekorozwoju – Problems of Sustainable Development,

16(1), 219–229. https://doi.org/10.35784/pe.2021.1.24.

The International Monetary Fund Data. https://www.imf.org/en/Data.

The World Bank Open Data. https://data.worldbank.org/.

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Digitalization and modern Technologies

The Meta-Analytics of Data Science: An intuitive Perspective

Sidharta Chatterjee

Andhra University, India

Abstract

This paper is dedicated toward understanding the meta-analytics of data science. Data

science—being now an independent domain—demands a greater expertise and skilful

ability on the part of data analysts who perform analysis of data. Beyond analytic

acumen and technical expertise, however, the involvement of noetic elements—what

we may call the intuitive aspects, have become necessary for successful interpretation

of the results of data analysis. This I call the meta-analytic perspective of data analysis.

In this paper, I attempt to underline the foundational processes based on which meta-

analytic and the epistemological perspectives could be grounded in relation to the

science of data analysis. Knowing how to perform data analysis is as important as

understanding the principles upon which the domain rests.

Keywords: Big data, ChatGPT, Data analysis, Data science, SMART criteria, Meta-

analytics of data science, data epistemology, philosophy of data science.

Introduction

Data science has evolved more rapidly than most other scientific domains within the past few

decades. It has found its usefulness and utility in almost every domain of inquiry and

understanding, including psychology, sociology, marketing, business analysis, sales, scientific

research, hospital and tourism industry, healthcare, among others. Moreover, this is the age

of big data where corporates and organisations deal with large-scale data for seeking answers

to rapidly evolving problems (Albright and Winston, 2020; Canali, 2016).

Data analytics, which is analysis of data, is a skilful activity in which information collected as

data in a quantified manner which when measured, tells stories i.e., stories that numbers tell.

Data science is not difficult to master, but it often becomes challenging to analysts when they

deal with big data (Geiseb and Ndinelago, 2023). The analytic part of the analysis of data

necessitate incredibly sharp intuition to interpret the findings of a data analysis. However, the

entire aspect of data analytics is procedural in nature. It follows methodological steps that

employ models to help dive deep inside the data to drawn insights. Understanding contexts

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and intuition, therefore, provides the necessary guidance that is essential in data analysis, for

it drives decision-making across sectors and industries.

It shall be noted that most ancient societies made decisions based on their observation and

intuition. Very little means of collecting data, understanding its importance, and putting it to

good use were around in ancient times. They used to deal with data in their own way. However,

in the past, understanding of patterns have always been crucial for human survival, progress,

and evolution. Today, data provides a richer context to research and analysis, as its

importance in society has increased manifold owing to the insights that one could draw from

the analysis of data. Data generates insights, and the unfolding of ideas from the analysis of

data supports general assumptions just as examples do. Intuition, too, does play a significant

part in data science and data analytics, fuelling our enthusiasm when it is supported by deep

insights, wherein excitement is generated at the depth of analysis, which fuels further curiosity.

Data is some sort of concrete evidence since it helps in the matters of investigation and inquiry.

One must utilise the spirit of curiosity to dive deep into data using different means as tools and

techniques (statistical models) to penetrate and identify patterns hidden within data—i.e., those

that are not visible to an undiscerning, naked eye. Hence, we must also understand the

sources offering data. However, the real problem in handling data is the sheer volume and

variety of (big) data—a challenge that, according to the experts working on data science,

(Venkatram & Geetha, 2017, Geiseb & Ndinelago, 2023, and Boyd & Crawford, 2012), needs

to be overcome by industry analysts and practitioners, if it has to prove itself useful and worthy.

Data is nothing but information obtained as “practical evidence” as it has always been applied

to support or refute theories and assumption, propositions and hypothesis. That is to say,

‘prove your point with evidence.’

The main objectives of this research, thus, revolve around these issues that we can categorise

as the metaphysics of data analysis. While at the same time, it is also necessary to understand

the role played by intuition in providing the meta-analytic perspectives of data science. It is

beyond the capacity of this paper to provide a detailed perspective concerning a historical

analysis of data practices in major sectors of the economy (Venkatram & Geetha, 2017), as

this paper is not evolutionary in nature. However, by exploring a different dimension, it

discusses the progression of data analytics today. The research being ‘review’ in nature, it

concerns the fundamentals only: It discusses the unique challenges and benefits of data

analytics that analysts need to deal while performing analysis of data. In such spirit of enquiry,

the research integrates both scientific and philosophical perspectives of data analytics, always

being eager to contribute to new knowledge, or add new perspectives to the already existing,

by providing a novel dimension concerning its meta-analytics aspects. If we closely compare

the realms of data science with a mountain peak, we may notice the similitude between them:

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a peak gives some novel insight to the data, whereas a trough may constitute a challenge to

be navigated.

The Progress of Data Analytics: A Literature Review

Data analytics has progressed with the advancement of technologies. Since data is king in this

age of digital technology, most marketing, communications, media houses, and PR agencies use

data as an effective marketing tool. Moreover, as the age of big data is already in place, there is

a need for scalable Big data technologies that have evolved over time, leading to industry

practitioners leveraging them to achieve success and fight competition (Venkatram & Geetha,

2017; Geiseb & Ndinelago, 2023). Indeed, the era of Big data has begun (Boyd & Crawford,

2012), as it has made data-driven research possible (Canali, 2016), but causal knowledge cannot

be ignored as well, and it should become a part of the Big data science. Moreover, it needs to be

seen how far it is able to help ease human communications, or provide better services, as critical

questions concerning the applicability and usefulness of Big data still emerge (Boyd & Crawford,

2012). Given all this, it must be acknowledged that Data Science has now become a scientific

domain in its own right. In social research, too, the methods of gathering or collecting data are

crucial for doing a meaningful analysis.

Science refuses to respect illusions whereas facts refute them. Truth is

established by facts, and facts influence to change people’s opinions.

What do you do with data? How do you want to use the data? Do you estimate parameters or

predict and compute probability distributions? These are the questions that data analysts and

data scientists constantly have to deal with (Albright and Winston, 2020). Data can be used to

challenge findings, refute conclusions, test assumptions, or prove hypotheses. Data is a

resource—an asset—that can be leveraged to build expectations around it, derive meaning

from it, and obtain information from it. Any set of data contains “elements” that provide us with

information.

Data is used to predict the outcome of an effect, say (x), by using one or more independent or

predictor variables (y). During data analysis, the analyst attempts to determine the best

predictors of an effect—say, ‘x’. There may exist many predictors (y) of something that may or

may not help determine, say, a behavior in (x). Data may contain patterns that may indicate a

prevalence, trait, trend, or effect. Data can be used to answer a question, define an effect, or

determine an underlying cause using variable(s) that indicate attributes in a data set. Statistical

models are designed and employed that serve the purpose of data analysis. Without data,

there’s no statistical analysis ever possible. A model is used to determine a characteristic that

best predicts something. It is the distinguishing feature (y)—a trait or an attribute is what

determines the nature of a thing (x).

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The goal of this paper is to discuss and understand the meta-analytics of data science. Meta-

analytics refers to the analysis of something at a higher plane or order—an advanced level

beyond the given. Data science begins with collecting data. Data is generally collected in a

methodical manner if it is to be of any useful value. The collection of data comprises several

steps that are important for the integrity and preciseness of the collected data. Once collected,

the data undergoes categorisation and sorting. Its significance lies in its efficient storage. One

can collect data by various means, e.g., performing a literature search, doing field work, from

interviews, surveys, questionnaires, observing events closely, or from experiments. These are

the primary data collection methods. Secondary data are obtained from databases, collected

from past research results, or by someone else other than the primary user, from primary

sources that are distributed, shared, or primary data hosted by third party sources (Vartanian,

2010). Deriving information from experts is also a source of data. Data can be obtained from

questioning, as it involves gathering facts about a question. But before that, one must

understand the characteristics of a good question. Along with it, one must identify the question

that needs an answer.

Data Modelling and Methodology: How to Identify a Question?

The primary task that a data analyst is responsible for beyond handling and analysing data is

“to identify a question”. A formidable and robust question leads to an effective inquiry. All

inquiries are conducted to obtain information. Here, the researcher’s job is to collect data

based on a question that would most likely provide her with answers (information) contained

within the data. But before one asks questions, one must identify and select a topic. According

to (Peng & Matsui, 2015), questions need to be asked to develop expectations. The

development of expectations is linked to the formulation of hypotheses (Popper, 1999).

Following this, one engages in the collection of information to see if it matches the prospects

related to the expectations built upon the question. If not, it is advisable to refine and revise

the question, or identify a better question on the same topic that suits the data. A precise

formulation of the question leads to better analysis as it increases one’s analytic acumen,

which enables one to work with data confidently.

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Fig. 1 HOW TO IDENTIFY A QUESTION?

Good questions lead to good data, for instance, a question that aims to inquire about a practical

problem (see Fig. 1). It starts with collecting information about questions, events, and things.

A question that seeks more information about a topic yields rich data. It’s a question that

reaches the depths and seeks to find what lies at the core—the bottom of things. Successful

data analysis follows effective data collection. In this paper, the meta-analytics of these

aspects are considered in detail, which sheds new light on the effectiveness of data collection

methodologies and the role of efficient processes in data analysis. The meta-analytics of data

science in a modern context must also involve the inclusive role of advanced computer

technologies, machine intelligence, and AI generative language models (i.e., ChatGPT and

others) that aid in searching and analysing the data and constitute effective machine tools that

can be leveraged by analysts for conducting successful data analysis (Simske, 2019; Hassani

& Silva, 2023). Besides, ChatGPT and other AI tools enhance the data science workflows that

increase the productivity and accuracy of data analysts. These advanced generative

intelligence tools not only help augment the field of data science, but they are better organiser

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of data and information that helps improve the decision-making process (Hassani & Silva,

2023). In a simple sense, artificial intelligence-based tools improve the collection, analysis,

and interpretation of data to extract meaning and derive insights from them, which addresses

the demand for data-driven decisions and insights that lead to decisions with superior

outcomes. However, it remains to be seen how ChatGPT and similar AI-based tools could

really help data analysts make their tasks of analysing data faster and more accurate in the

long run. The success of data analysis depends on the analytic acumen and skills of the

analyst; machine tools just help them do better.

Characteristics of Successful Data Analysis

Successful data analysis begins with efficient data collection that attempts to answer the

question(s) asked. The first thing that analysts should take care of concerning the data before

analysing it is to understand the nature of the data. What data is needed? Does the data

collected match the question? Two possibilities must be considered before one begins to

analyse a set of data. Does the data match or override the prospects, and then, should one

revise her expectations concerning the prospects? A set of data has several dimensions; i.e.,

the magnitude of the data collected, and the key indicators that specify and characterise the

data thus obtained. Those who are expert data analysts have a definite eye for details, as they

have developed expertise in data science and analysis. They can perceive errors in the data

collected and quickly match the data to their expectations.

It must be understood that the data is not only used for supporting or refuting certain arguments

or statements, but it is also employed to detect and solve problems. In the words of Karl Popper

(1999),

“All science starts from problems.”

That all science starts with problems is a notion that has its origins in Greek (Aristotelian)

thinking. We solve problems using methods of trial and error, or finding specific solutions for

them. Refinement in methods leads to the design of better and more effective solutions. Not

to forget that the advancement in sciences and technologies is mostly dependent upon the

refinement of techniques and tools of experimentation, observation, and interpretation

(Lundberg, 1942). Data originates from experimentation and, more importantly, from

observations. In fact, data makes us learn from observations (Galeano & Peña, 2019). John

Dewey believed that results are chiefly correlative to the means and methods employed to

achieve them (Dewey, 1904). It is the principles that define the methods to help determine the

efficiency of a research endeavor. Not all research generates data, however. The theoretical

ones, in particular, do not generate data. In empirical research, the results generate “data,”

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which is meant to be interpreted and consumed. The data thus generated becomes a primary

(original) source of information that can be stored for future consumption. Hence, the data

becomes a commodity.

Successful data analysis depends on the methods employed in figuring out what it says, and

how the interpretive results could be employed in trying out solutions to the problems. New

problems require innovative solutions, and the solutions arise from our attempts to solve

particular problems. It is here that data is required to understand the framing of a decision or

solution aimed at solving problems.

“In simple words, data is central to a problem and its solution; it comes ‘between’ a problem

and the solution.” (Popper, 1999).

Now, it is true that something very specific can be verified with data, as data are facts that

either help prove or disprove a prior theory or hypothesis. For example, marketing managers

use data to assess the size and potentialities of a market for a product that is to be launched.

For them, and for the business executives, data science for business have important

implications (Medeiros, Hoppen and Maçada, 2020). They ask questions: How big is the

market? Who are the prime competitors and market leaders in the segment? Answers can

come in both numbers and characters, requiring both qualitative and quantitative analyses.

The practical aspects could be explained with qualitative data analysis (Charmaz, 2006), and

this could be grounded on theory based on the facts obtained from such analyses of data.

Nevertheless, guided by these questions, they gather data and feed it into the system for

analysis. When required, they meticulously “fix” the data according to their expectations. The

next thing they do is gather feedback from data analysts about their own perspectives, since

they are the ones who do the analyses, deal with data, and are aware of the “methods of

analysis” that best suit the data. With this information, marketers are able to predict the

prospective size of a market for products in the future. Analysis also brings new questions to

the forefront, and reveals the strengths and weaknesses of the sample size and quality of the

data being analysed. This is what characterises the primary steps in successful data analysis.

The secondary steps in data analysis involve the application of complex and intricate models

to the data, in order to go more into detail. The choice of models, and their proper design

involve expertise and acumen. The analyst must have prior knowledge of the models and

methods of analysing data to chart out a clear conception of the problem at hand. Using

common sense in applying models to a specific set of data tells a lot about an analyst’s critical

aptitude for a problem situation.

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Building (Statistical) Models that Fit the Data

In data analysis, each variable is accorded a “space” whose importance is determined in order

to reflect the attention it deserves. The space that each of the elements in a data set occupies

constitutes the arrays, arranged in rows and columns. No two elements of a variable occupy

the same space, and no space lodges more than a single unit of datum (singular of data). As

in science, no two causes are exactly identical, or have identical effects, so it is in data science,

too. Each datum is accorded its own singular space. A collection of arrays of data constitutes

a set of data. Following analysis, the data will reveal what it is, what it means, and what it

represents. To conduct an investigation on the collected data, we need models. These are

statistical models so designed that they are based on pre-defined mathematical formulae.

Robust models work well and fit the data. Some errors in data collection may remain, i.e.,

missing data (Newgard &Lewis, 2019), where missing elements might constrain the power of

the model, but in general, given a small sample size, one can use statistical models, both

descriptive and exploratory, to analyse and examine a given set of data.

For example, based upon a certain degree of correlation found between two or more predictor

variables, one can conclude by deduction whether any two objects co-move or fall apart, are

related or unrelated, similar or distinct, etc. Based on the results thus obtained from analyses,

one can construct a theory to generalise an event, and so on. As a matter of fact, results from

data analysis provide us with the necessary direction to think and take actions, to link causality

to an effect, to establish connections, identify trends, etc. Thus, it would be appropriate to state

that data guides our social, business, political, and economic/financial decisions. Guided by

the outcome where results are obtained after rigorous analysis of data, we make the choices

necessary to create a new path, or to adopt a given course of action that takes us to the future

offering new prospects and opportunities. Such an endeavor generates new knowledge, which

could be effectively utilised to make future decisions. Consider the following scenarios where

data analysis often provides a direction for one’s thought, action, decision, or research:

This is particularly helpful in situations concerning clinical trials and pharmaceutical research

on new products (drugs). Data analyses revealing positive results help the pharmaceutical

companies promote with confidence their newly designed drugs to effectively treat specific

diseases in a particular group of patients.

A company wishing to launch a new product first undertakes market analysis based on

collected data to find out whether there is a potential market for it. The results so obtained will

be further analysed by the business analytics team to generate reports concerning such

prospects, based on which managers would decide on strategic actions concerning new

product launches, product modifications, pricing, product recalls, discontinuations, etc.

(Albright & Winston, 2020).

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Therefore, data in the service of business and human welfare can be of great help to

organizations that rely on the results and outcome of data analysis to make their decisions

grounded on facts and robust reasons. As a helpful reminder, it would be wise to keep in mind

that each product or service is tied to its organisation’s goals and objectives, expectations,

prospects, perceptions, and limitations. Data fights limitations, revises expectations, and

highlights prospects, for it provides the requisite truths (facts) based on which business

decisions could be made.

Now, just as knowledge plays a role on the limits of expertise, so does the data, for one can

obtain the data from the past or present, but not from the future. One uses the data just to

predict the future with a high degree of probability and uncertainty. Statistical models here play

the most significant part in conducting the analyses on the data. To draw inferences from

statistical outputs interpreted as results, visualised and rendered comprehensible to the

average eye, the models themselves must be powerful and robust. The real magic lies in

conducting the analyses with the right tools of statistics, i.e., the models.

Bringing Metaphysical Thinking into Data Science

One of the focal aims of this short, narrative research commentary is to bring metaphysical as

well as philosophical thinking into data science. Not that it has been attempted before, one can

refer to the work done by Desai et al., (2022), who have explored the epistemological

foundations of data science. What it requires is a strong love for the subject and a belief in the

discipline of data science. One needs to have a deep intellectual interest in all things connected

to data science. A good data analyst should be able to detect and identify patterns in data and

correlate them with the world around her. This will prove the deftness of a skilled data analyst.

And, beyond that, to introduce metaphysical thinking into it, one must have trust in real-time

logic; so what will it require? It will require deep thinking and deliberation. And to give it a

scientific foundation to boost interest among the new entrants attracted to the field of data

science, they will need to do more project work related to this domain. Also, doing more

research as a basis for new knowledge development in data science will go a long way towards

giving it a solid metaphysical foundation. But what kind of metaphysical thinking should be

infused into data science?

First, one must set a high standard of thinking related to data science. This one can be easily

deliberated upon, in order to implement it in practice. Attempts must be made to provide a

robust scientific foundation for data science, and only then could one think about giving it a

metaphysical underpinning. The starting point of data science is not analysis, but to collect

data concerning a given problem, and to get a better understanding of the problem itself. Then

one can think about what to do with and how to handle the data. The logic of data science is

simple: identify the problem statement, understand it with clarity, get the data, organize it,

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design a model, feed it with the data, and run the analyses to perform tests on it. Finally, all

these steps lead to the interpretation of results from data analyses. The most usual response

to such an approach to Big data and data science is that one should have a critical attitude

towards solving a problem using data (Venkatram and Geetha, 2017). Some argue that it is a

better option than using only common sense in critical problem situation (Popper, 1999).

But what about infusing metaphysical thinking into data science? What about being so

philosophical and conceptual about data science (Desai et al, 2022; Fattahi, 2022)? These

relate to higher-order analyses of the data using more sophisticated and complex models to

yield more abstract results. Because today’s problems are complex, so must be the methods

and processes that lead to solutions. But sometimes, this is not the case. Although most

attempts do not lead to concrete solutions, those that do evolve over time that lead us to learn

and know about successful solutions to specific problems. But how do you know what’s

important in data science research and analysis? How would one know what’s important to

learn, and discard what’s useless? This will result from a search for relevant knowledge on the

deeper aspects of the subject, and it is where metaphysical foundations are called into action.

As circumstances change, such changes produce new environments, which create “new data”

as reference points. We can say in a similar vein that as problems evolve, so do their solutions,

too.

Confidence on Data

Should all data be treated with suspicion, particularly those generated by artificial algorithm -

based predictions (Berman, 2019)? This is still debatable, but most unlikely would be so. Data

originating from credible institutional research activities and those hosted by authentic,

trustworthy organizations could be relied upon to be valid. However, caution must be observed

while accepting anything at face value. What is thought by an analyst concerning the data may

not be readily perceived by others, unless proved otherwise by explanatory means that explain

things and events using facts and truths, trends and possibilities, etc. Data can be used as a

resource to garner power, as it becomes essential to influence, produce, and impact others.

As such, validation of the authenticity of the sources from which the data is obtained remains

a crucial aspect before conducting any research or analysis involving the data.

Most organizations and industries use data as a means to strengthen their businesses, fortify

their decision-making abilities, streamline their operations, and bring efficiency in their

performances. Information obtained from data analysis is highly valued to push corporate

business agendas. Findings from marketing data analytics greatly aid managers in making

marketing decisions, based upon clear understanding of customer, choices, behaviors and

their consumption patterns. Findings from data analysis also empower production channels,

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as it help strengthen the assembly lines where efficiency and precision are brought together

to streamline operations.

Fig. 2 Data Usage in Manufacturing and Production

Data improves productivity and increases productive efficiency of businesses (see Fig. 2).

Businesses are able to make “informed decisions” based on data. The results of effective data

analysis are employed in assessing quality control issues in manufacturing and production,

and in dealing with issues related to the detection of errors on the manufacturing, production,

and operational frontiers (Shivajee, Singh & Rastogi, 2019). When businesses face problems,

they rely upon data, which informs them with much needed strategic insights. Solving practical

problems using data analysis have become the norm in almost every sector and industry in

the modern economy.

One must acknowledge the usefulness and importance of data in modern, contemporary

society. We use data to detect hidden patterns and trends that may help solve practical

problems. In the financial sector, data analytics is heavily relied upon for making trading

decisions, buying, holding, and selling assets in the securities markets, and identifying trends

for making investment decisions. Forecasting is one of the most important applications where

past historical data is used to predict future trends in the financial markets. Therefore, in every

aspect of economic and social decision-making, the role played by data and data analytics is

fundamental.

Making decisions based upon the results from data analysis would seem far better than making

decisions based on intuitions alone, although, sometimes, intuitions lead the way in solving

problems, but not always does it so. And when intuition is guided by information and facts, our

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confidence in our decisions increases manifold (Liebowitz, Paliszkiewicz & Gołuchowski, 2017;

Svenson, Pietrzak, & Launer, (2023). We must not forget that facts and information have the

power to influence opinions, thoughts, and sentiments. It is for this reason that data speaks

with more confidence than expectations do. Expectations and intuitions can often go wrong,

although they are based on the prior knowledge and expertise of the intuitionist. However,

conclusions that are based on data, facts, and information are better accepted to be true than

those based on instincts and intuitions alone.

Fundamental Principles of the Meta-analytics of Data Analysis

Metadata is the data about data—data that describes data, for example, a library catalogue

that describes publications held in a library. Meta-analytics of data, however, is an analogous

idea, yet it is conceptually dissimilar—as it describes the processes of data analytics at a higher

level. It transcends the analytics of data by discussing the fundamental principles that govern

analysis, and the design of novel tools of analytics for examining the data at a higher level,

incorporating other cross-disciplines, AI tools, data linguistics, and network analysis.

Therefore, it goes beyond the nominalist and discreet approaches to statistical analysis of data,

into the theoretical domain, which engages with the ideation and design of more advanced,

higher level methods of analysing data. Its aim is to bring a high level of efficiency to data

analysis. It is a path towards the principality of the fundamental norms that bind data with

analytic processes. As a clue leads one to the evidence to solve a problem, so do the

fundamental principles that lead data scientists to the forefront of discovery—the discovery of

what lies beyond the core and the periphery of the data (See Heidegger, 1996). If we pay

attention to the cues and clues, we shall be doing better to see within the data, but of course,

using specialised tools for analysis and visualisation. This is to say that our understanding of

the content of data depends largely on how we understand and pay attention to the cues we’re

following. The materials for data analysis are—in essence, the predesigned tools and models,

and the methods that determine the principles of reasoning in data analytics.

As a business or marketing analyst, you must know how to analyse data efficiently, if

you know nothing else.

Methods help us delve deeper into the data. Refinement in methods and the design of more

efficient models increase the power of analyses. The knowledge of how things show up

following analysis will lead us to the information that can be obtained from data. Conversely, it

is also important to explore what knowledge can be obtained from data, and how the data can

inform us. Besides, it is also essential to understand what data can be acquired from

knowledge. The usual principle of flow of information may be represented as follows:

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Data, Information, and Knowledge

However, it is necessary to pay attention to what can be known (or not known) from analysing

a set of data. We search for a reason, and if the cause is unascertainable from the effects that

actions produce, then we will need to get back to the basics and start thinking again. We will

need to get to the bottom of what is being encountered as a set of “data.” And we will need to

get to the bottom of data analysis and try every means using all possible methods and models

that fit the data to discover what it means to us.

Data helps us turn to facts.

Facts inform us about the truth and give us the confidence to form polished opinions. If we

closely reflect on the principles of data analysis, we will notice that good things are found at

the core. To get to the core, we must know the how—the principle of knowhow. Because, within

the deepest core of the data, are to be found the hidden patterns that can only be uncovered

using specific tools and techniques of analysis. That is to say, the answer to a specific problem

is concealed in the principles of analysis. We must understand what the principle says. This

makes sense, for what is without reason is lacking in understanding. Data must make sense

in order to be understood, and it is the principles of analysis that make it more sensible to the

eye of an analyst.

The Knowledge of Data Analytics

When we analyse data, we embody useful effort in it. Effort manifests itself in the value of

analysis performed. The ability to see into the data is dependent on the expertise of the analyst

in handling and examining the content of the data, i.e., factors that determine the “analytic

power” and “acumen” of the data scientist. The ability and intuition vary among different

individuals, and so does the expertise that varies, too, among the data scientists. But since

they are trained and equipped with industry-standard, state-of-the-art programmes, they gain

the required expertise to handle Big data. Therefore, today, one may observe that the practice

of data science is homogenised, which is reliant on the acquired abilities and skillsets of the

analyst (Hughes & Ball, 2020). Data analysts are trained with a special aim—alike other

professions, which demand advanced skills and aptitude. This creates the value of training

programs that empower people with the necessary dynamic skillsets to render them capable

of handling big data. Now, it corresponds to the expenditure of ‘energy’ with a special aim. The

value is connected to one’s efficiency and productive power, hence, the more efficient and

capable the data analysts are, the better they become accustomed to handling and performing

data analysis by getting into the core content of the data in question. However, data science

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is not unfailing; it has limitations. It is not always directly feasible to observe from the data or

predict the probability that a particular event will succeed or fail (Foster, Rzhetsky and Evans,

2015).

In the manufacturing sector, for example, producers are most concerned with different kinds

of data and information: i.e., production time and cost analytics, process management data

analytics, quality control and assessment data analytics, etc. The meticulous collection of such

data and their rigorous analyses produce insights that have a direct effect on workforce

productivity and productive efficiencies (Crandall, 1991; Saxena, 2014; Areiqat and Al-Qaruty,

2023). Now, in order to make data an effective source of knowledge, and an instrument of

productivity for managers and decision makers, it is necessary to have a dedicated data

analytics team that conducts rigorous analysis using robust models. For this to happen, data

analysts must acquire a higher level of proficiency and expertise in the science of data

analytics.

Conclusion:

Data has become a capital resource in this era of digital capitalism (Sadowski, 2019). There is

a tangible value attached to data analysis, as it is one of the most sought-after careers today

and promises great prospects for the data scientists entering this domain. The value of

something becomes tangible when it turns into a product. However, its utility may not be

immediately apparent, though a product is developed with a definite purpose in mind. Data—

in its strictest sense—is a product that has marketable value, and the skilful art and science of

data analysis is a value-embedded profession today. Mass production and consumption of

goods create a huge amount of data at the point of sale—the marketplace. This data relates

to the consumption patterns of consumers, individual choices and preferences, and their

purchasing patterns, all of which become important “data” for producers and marketers.

Consumers—now, too, are becoming conscious of the data as they are gradually turning into

“informed customers.” However, current research fails to indicate that they are more concerned

with market data—let alone data in the first place, when they make purchasing decisions.

Nevertheless, when they become sellers, they develop a perception of the markets, and to

them the “data” becomes an important guide to marketing and selling products (Ichihashi &

Smolin, 2022)—online or offline.

Acknowledgements:

The author expresses his gratitude to the Andhra University, Central Library, Visakhapatnam.

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Investigation of New Generation Restaurants in Gastronomy Digitalization

Process

Rana Şat

1)

, Markus A. Launer

2)

, Ercan Karacar

3)

and Emre Akmanoglu

3)

1) Balıkesir University Institute of Social Sciences, Turkiye, Orcid No. 0000-0003-0519-5524

2) Ostfalia University of Applied Sciences and Institut für Dienstleistungen (non-profit-

organiaztion), Germany, Orcid No. 0000-0001-9384-0807

3) Sinop University, Turkiye, Orcid No. 0000-0002-1124-9667 and 0000-0003-2224-0980

Extended Abstract

As a result of technological developments in the world, new developments have occurred in

the preferences of individuals and in the service sector offered to individuals. It is seen that the

field of gastronomy is also included in this process and innovations are made for both

consumers and producers. In recent years, restaurants that have adopted sustainable and

environmentalist approaches around the world have started to draw attention to the measures

taken within the scope of sustainable and environmentalist practices with the rapid growth of

environmental problems worldwide with the development of technology. In this context, it is

thought that the environmentally friendly restaurant concept of new generation restaurants will

become more widespread in the coming years. For this reason, it is foreseen that the guests

who receive service from environmentally friendly new generation restaurants will provide

theoretical and practical benefits together with examinations in the category of consumers'

satisfaction and complaints. It is seen that there are a limited number of studies revealing the

importance and benefits of technology and environmental practices in new generation

restaurants. In this context, it is seen in the literature that the guests develop consumption

habits by thinking that the applications within the scope of green practices contribute to the

environment. Thus, it is possible to mention that the related environmental practices provide

an emotional benefit for consumers (Park, 2020). In addition to green practices in new

generation restaurants, technology 4.0 applications can positively affect the sustainability of

natural environments (Dutta, 2008), reduce the costs and workload of food and beverage

businesses. It can also improve the corporate image of food and beverage businesses.

Schubert (2010) states in his study that new generation restaurants have a great impact on

the decision process of consumers as a potential niche market. For this reason, gastronomy

4.0 practices of new generation restaurants are effective in strengthening brand and customer

loyalty and gaining new guests (Perramon, 2014). Differentiation is achieved through the

innovative development of new generation restaurants (Tan, 2019). The adoption of

gastronomy 4.0 practices in restaurants is seen as an incentive to improve the market success

of restaurants and the performance of food and beverage businesses (Perramon, 2014). The

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technology initiative in next-generation restaurants can provide a positive financial benefit as

well as financial incentives that can be collected from the guests of the restaurants (Schubert,

2010). It is seen that there are few studies on new generation restaurants as a research field,

but there have been developments in related studies in recent years (Arun, 2021). The

establishment of food and beverage businesses requires less capital and knowledge than

other tourism businesses (accommodation businesses, travel agencies, etc.), which creates

an intense competitive environment in the sector (Akyürek & Kızılcık, 2018). In this context, it

is seen that some technological applications are being adopted to increase the

competitiveness of restaurants. It is possible to mention that these practices can adopt some

environmental practices that increase competitiveness. In this way, it is possible to mention

that costs can be reduced and some competitive advantages can be achieved in the long term

by providing financial and operational contributions (Ma & Ghiselli, 2016). When we look at the

main characteristics that distinguish new generation restaurants from other restaurants; it

makes a difference in terms of their progress towards reducing unsustainable products, giving

importance to the reuse of products, using recyclable materials, saving energy and increasing

efficiency (Gilg, 2005). For this reason, new generation restaurants should be restaurants that

focus on the three R's (reduce-reuse-recycle, reduce-reuse-recycle) and the two E's (energy

and efficiency) (Lita, 2014).

It is seen that the internet of things, three-dimensional foods, cloud computing technologies,

big data, augmented reality, robot systems, imaging systems, automation, cyber power

security measures and robot service technologies are included in Gastronomy 4.0, which is

presented by the gastronomy 4.0 revolution in the technology used by businesses in the food

sector to improve their products and processes and to improve the supply process in order to

reach the highest level of products and services offered to consumers. It is possible to mention

that these technologies are frequently used today. It is very important to determine the extent

to which these extremely important technologies are used by new generation restaurants. The

main purpose of this study is to examine the possible impact of the digitalization process in

gastronomy on new generation restaurants. In addition, it is aimed to reveal the opinions of

faculty members and students studying in the field of Gastronomy and Culinary Arts and

restaurant business employees on this issue. In this direction, interview technique, one of the

qualitative research methods, was utilized in the research. The data were obtained from new

generation restaurants operating in Ankara and Istanbul, faculty members and students of

gastronomy and culinary arts department. It is seen that online comments on new generation

and green restaurants have been focused on before (Dalgıç, Taştan, & Kızılcık, 2017; Erdem

& Yay, 2017; Şengül, 2018; Yaşar, 2019; Şahin Perçin & Yiğit, 2020). In this context, in this

research, one-on-one interviews were conducted with experts in the field and guests. In this

research, two large metropolitan cities were selected and evaluations were tried to be made

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regarding the use of gastronomy 4.0 applications by new generation restaurants. In line with

the data obtained, it has been observed that augmented reality, cloud computing technologies

and robot service technologies have recently started to be used by restaurants, QR code

menus are frequently used, and contactless payment NFC method is frequently preferred by

consumers because it provides ease of payment. In addition, it is seen that new generation

technological applications have a positive effect on consumers' choice of restaurants.

In line with the research results, a number of recommendations for local and centralized

methods for new generation restaurant entrepreneurs and operators are presented. These

recommendations are categorized as follows. New generation restaurant operators and

entrepreneurs should employ qualified personnel in sustainability and new generation

technologies in their management processes. Businesses that offer delicious food and

businesses that attach importance to rich gastronomic experience should be more intertwined

with technology. In order to reduce the complaints and dissatisfaction of guests in new

generation restaurants, first of all, situations such as not offering high pricing, not having

qualified chefs and service staff in the restaurant and not visiting tables should be prevented.

It should be emphasized that any problems that may occur during the reservation and service

process should be solved at that time by working in integration with new generation mobile

applications. In addition, guest comments shared on online platforms should be responded to

immediately.

Keywords: Digitalization in Gastronomy, New Generation Restaurants, Gastronomy 4.0

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15(8), 1087-1099.

Ma, J. ve Ghiselli, R. (2016). Measuring, monitoring, and managing the green practices in mid-

sized restaurants in China. Journal of Foodservice Business Research, 19(1), 64-76.

Yaşar, Z. (2019). Kastamonu’da yöresel yiyecek içecek hizmeti sunan restoranlara ilişkin

tüketici şikâyetlerinin değerlendirilmesi: Tripadvisor örneği. Safran Kültür ve Turizm

Araştırmaları Dergisi, 2(2), 241-250.

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Internet and Facebook Addictions among Filipino Students in Higher

Education

Dave E. Marcial, Jan Cynth Palama and Jade Montemayor

Silliman University, Philippines, Orcid No. 0000-0003-0006-8841

Extended Abstract

The Internet, particularly through platforms like Facebook, offers significant advantages in

communication, information access, and leisure. Launched in 2004, Facebook has grown into

a dominant social networking site with over a billion users, and its influence continues to

expand, especially in developing countries. In the Philippines, social networking is deeply

integrated into the culture, playing roles in education, campaigns, and even criminal

investigations.

However, there are challenges associated with social media use. Research highlights issues

such as data privacy, echo chambers, and misinformation, which affect the quality of discourse

and critical thinking. Additionally, Internet addiction has become a growing concern, with

excessive use leading to psychological and social issues. In academic contexts, Facebook

addiction is linked to poor academic performance, anxiety, and low self-esteem. On the other

hand, the Internet can provide positive social support that improves mental health, though its

overuse is associated with procrastination and declining grades.

This study explores the prevalence of internet and Facebook addictions among students in

higher education institutions in the Philippines. Specifically, it presents the levels of addiction

of Internet and Facebook addiction. It also shows the significant relationship between internet

addiction and sex, type of institution, level of familiarity, operations and tools, and social

technologic ladder. On the same manner, the paper also explores the significant relationship

between facebook addiction and sex, type of institution, level of familiarity, operations and

tools, and social technologic ladder.

The study utilized datasets from an open online course titled "Fighting Information Disorder on

Social Media" (Marcial, 2023), which is free and available to a wide range of learners, including

teachers, researchers, and students. The course, designed in an asynchronous format with a

duration of 54 hours, aimed to equip participants with the skills to combat misinformation,

disinformation, and mal-information on social media. Using micro-learning, gamification, and

self-paced activities via the ourSOUL Learning Management System, the course covers six

modules on topics like fact-checking, the role of echo chambers, and the ethical use of digital

tools. For this study, 109 respondents were selected from an initial 136 participants to analyze

data on Internet and Facebook addiction. The Internet Addiction Test (Young & Nabuco de

Abreu, 2010) was used to measure internet addiction, consisting of 20 statements rated on a

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5-point Likert scale. Similarly, Facebook addiction was measured using a 5-point Likert scale

across six statements. Both tools assessed participants' usage patterns and the level of

addiction to these platforms.

The results of the Internet Addiction survey indicate that respondents generally experienced

internet addiction at a low level, with an overall mean score of 2.64, categorized as "rarely."

Some of the more frequent behaviors included staying online longer than intended, with a

mean score of 3.48, and often delaying other tasks with the intention of staying online for "just

a few more minutes" (mean: 3.13). However, internet use rarely interfered with significant

aspects of life, such as household chores (mean: 2.48), school performance (mean: 1.88), and

job productivity (mean: 2.13). Occasionally, respondents feared that life without the internet

would feel boring or empty (mean: 3.03) and anticipated their next opportunity to go online

(mean: 2.85). Defensiveness about online behavior and negative emotions when offline were

infrequent, with scores of 2.39 and 2.40, respectively. Overall, the results suggest that while

some respondents exhibit occasional signs of problematic internet use, the majority experience

low levels of addiction-related behaviors.

The results of the Facebook Addiction survey reveal that participants exhibited occasional

signs of addiction, with an overall mean score of 2.93, categorized as "sometimes."

Respondents frequently thought about Facebook or planned its use (mean: 3.17) and felt an

increasing urge to use the platform (mean: 3.16). Additionally, Facebook was sometimes used

as a coping mechanism to forget personal problems (mean: 3.16), and some respondents had

unsuccessfully attempted to reduce their usage (mean: 2.90). Although participants

occasionally felt that Facebook negatively impacted their studies (mean: 2.67), they rarely

became restless or troubled when restricted from using the platform (mean: 2.54). These

findings suggest that while Facebook use was prevalent among respondents, the majority

exhibited moderate levels of addiction-related behaviors, with some signs of problematic

usage.

The analysis of the relationship between Internet addiction and various factors reveals mixed

results. No significant relationship was found between Internet addiction and sex (χ² = 1.95, p

= 0.74) or type of institution (χ² = 1.87, p = 0.76). Similarly, there was no significant correlation

between Internet addiction and the social technologic ladder (χ² = 22.43, p = 0.55). However,

a significant relationship was identified between Internet addiction and the level of familiarity

with technology, operations, and tools (χ² = 30.90, p = 0.00). This suggests that individuals

with higher familiarity with technology are more likely to exhibit signs of Internet addiction.

The analysis of the relationship between Facebook addiction and various factors also shows

mixed results. No significant relationship was found between Facebook addiction and sex (χ²

= 3.89, p = 0.42), type of institution (χ² = 1.01, p = 0.91), or familiarity with technology,

operations, and tools (χ² = 13.62, p = 0.09). However, there was a significant relationship

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between Facebook addiction and the social technologic ladder (χ² = 55.23, p = 0.00). This

suggests that an individual's position on the social technologic ladder is significantly associated

with their level of Facebook addiction.

In conclusion, the study suggests that increased familiarity with technology and higher

engagement in social technologies may elevate the risk of addiction, while demographic

factors like sex and institution type have little influence. These findings highlight the need for

targeted interventions to address the habits of individuals who are more deeply embedded in

the digital landscape to reduce the risk of addiction.

Keywords: eLearning, responsible use of technology, technology addiction

Reference:

Young, K. S., & Nabuco de Abreu, C. (Eds.). (2010). Internet addiction: A handbook and

guide to evaluation and treatment. John Wiley & Sons.

https://doi.org/10.1002/9780470557645

Keles, B., McCrae, N., & Grealish, A. (2020). A systematic review: The influence of social

media on depression, anxiety, and psychological distress in adolescents. PLOS ONE,

15(4), e0231924.

https://www.tandfonline.com/doi/pdf/10.1080/02673843.2019.1590851

Pew Research Center. (2015). Psychological stress and social media use. Retrieved from

https://www.pewresearch.org/internet/2015/01/15/psychological-stress-and-social-

media-use-2/

Kandemir, M. (2014). Predictors of procrastination: Personality traits, academic self-efficacy,

and academic procrastination. University of Alabama Institutional Repository.

Retrieved from https://ir.ua.edu/bitstreams/d650046e-dedc-4143-8a42-

dae90080461a/download

Young, K. S., & Nabuco de Abreu, C. (Eds.). (2010). Internet addiction: A handbook and

guide to evaluation and treatment. John Wiley & Sons.

https://doi.org/10.1002/9780470557645

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Confirmation Bias and Trust in Social media among Filipino Students in

Higher Education Institutions

Dave E. Marcial, Aurielle Lisa Z. Maypa and Cindy Ruth R. Villariza

Silliman University, Philippines, Orcid No. 0000-0003-0006-8841, 0000-0002-2797-2657

and 0000-0002-8270-4866

Extended Abstract

In today’s higher education landscape, social media plays a key role in how Filipino students

access information, often serving as their primary news source (Calosa et al., 2023). This

makes it vital to explore how confirmation bias and trust influence their consumption of

information. Confirmation bias, where individuals favor information that aligns with their beliefs

(Nickerson, 1998), is especially powerful on social media, impacting decision-making and

critical thinking (Prakash et al., 2023). Trust in the reliability of information also shapes how

students engage with content (Majerczak & Strzelecki, 2022), affecting the quality of their

academic discussions. Understanding the interaction between confirmation bias and trust is

essential for fostering a more discerning academic community. Investigating these factors

among Filipino students is crucial as they influence academic performance, critical thinking,

and decision-making skills. This paper investigated the prevalence of confirmation bias and

the level of trust in social media among Filipino students in higher education. It also presents

the significant relationships between confirmation bias and trust on social media and profiles.

This study, conducted between June and November 2023, involved 143 participants, including

teachers, college students, and librarians. Respondents completed activity surveys from

module 1 of a six-module open online course and a registration survey. Confirmation bias and

trust in social media were evaluated using an adapted questionnaire with a 3-point Likert scale,

where 1 indicated "disagree," 2 "slightly agree," and 3 "highly agree."

The demographic profile reveals a significant gender imbalance, with 81.82% female and

18.18% male respondents. Most participants (91.61%) are from public institutions, reflecting

the perspectives of public-school students. In terms of concept familiarity, most respondents

rated themselves as "Good" (34.97%) or "Fair" (28.67%), with smaller numbers indicating

"Very Good" (19.58%) or "Poor" (9.79%), and only 6.99% achieving an "Excellent" rating. For

social media engagement, the largest groups were "Joiners" and "Spectators" (30.07% each),

indicating passive use, while smaller numbers were "Conversationalists" (14.69%) and

"Creators" (9.79%). The results show that respondents tend to "slightly agree" (mean = 1.90)

with sharing, liking, and believing posts that align with their views. They are more likely to

engage with posts from friends using the "react" button (mean = 2.36, "highly agree"), though

sharing (mean = 2.13) and liking (mean = 2.15) fall into the "slightly agree" category.

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Engagement with posts from unknown individuals or organizations is lower, with mean scores

ranging from 1.80 to 1.92, all rated as "slightly agree."

Trust in social media content shows relatively low scores. Respondents are more inclined to

believe posts from friends (mean = 1.72) or respected figures (mean = 2.02) but show less

trust in posts from political parties (mean = 1.59) or people they do not know (mean = 1.48),

all rated as "slightly agree." This indicates a general tendency to trust familiar sources more

than unknown or political sources, though even trust in familiar sources remains relatively

cautious.

The chi-square analysis explores the relationship between confirmation bias and trust levels

on social media and various socio-demographic and technological factors. The findings

indicate no statistically significant relationships across all variables. Specifically, gender does

not significantly influence confirmation bias or trust levels, as reflected by a chi-square value

of 0.255 and a p-value of 0.880. Similarly, the type of institution (public vs. private) shows no

significant effect, with a chi-square value of 2.679 and a p-value of 0.102. Familiarity with

technology, operations, and tools also has no significant impact, as indicated by a chi-square

value of 3.913 and a p-value of 0.865. Finally, different levels of social media engagement,

represented by the social technographic ladder, show no significant relationship with

confirmation bias or trust (chi-square value of 10.016, p-value of 0.615). The results suggest

that no socio-demographic or technological factors examined significantly affect the

respondents' confirmation bias and trust levels on social media.

The multiple regression analysis explores the relationship between confirmation bias, trust

levels, and the respondents' profiles. The results show that most of the variables do not have

a significant impact on confirmation bias and trust. Specifically, sex has a negative coefficient

(-0.082) but is not statistically significant (p-value = 0.38), indicating that gender does not

significantly affect trust levels. Similarly, the concept mean level, which reflects familiarity with

key concepts, shows a positive coefficient (0.020) but is also insignificant (p-value = 0.56).

However, the type of institution is found to have a significant negative effect on trust levels,

with a coefficient of -0.349 and a p-value of 0.01. This suggests that students from private

institutions tend to have lower trust levels than those from public institutions. Lastly, the social

technographic ladder, which measures social media engagement, has a small negative

coefficient (-0.023) but is not significant (p-value = 0.21), indicating that levels of social media

activity do not significantly influence confirmation bias or trust.

In conclusion, this study provides important insights into the prevalence of confirmation bias

and trust in social media among Filipino students in higher education. The findings suggest

that while students generally exhibit a moderate level of trust in familiar sources such as friends

or respected figures, their trust in unfamiliar individuals or political entities remains relatively

low. Moreover, respondents tend to engage more with content that aligns with their pre-existing

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beliefs, reinforcing the presence of confirmation bias in their social media interactions. It is

recommended that educational interventions promote critical thinking and media literacy to

help students become more discerning consumers of information on social media. Addressing

confirmation bias and fostering trust in reliable sources is essential for improving decision-

making, enhancing academic discourse, and cultivating a more informed and analytical student

community.

Keywords: digital trust, responsible use of technology, social media

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Digital Citizenship and responsible Use of Social Media amomg Filipino

Students in Higher Education Institutes

Dave E. Marcial, Alfie Arcelo and Russel Basiao

Silliman University, Philippines, Orcid No. 0000-0003-0006-8841, 0000-0002-6927-5657

and 0009-0004-7758-7142

Extended Abstract

Digital citizenship and responsible social media use are critical in today’s world, with the

number of social media users projected to grow from 3.6 billion in 2020 to 4.41 billion by 2025.

Filipino students, particularly in Luzon, Visayas, Mindanao, and Negros Oriental, rely heavily

on platforms like Facebook and Messenger for academic communication. This study explores

digital citizenship practices among these students, focusing on etiquette, responsibility, well-

being, and security alongside their responsible use of social media. These practices are

essential for academic success, fostering critical thinking, ethical decision-making, and

cultivating a positive digital presence, which benefits personal development and societal well-

being.

Conducted between June and November 2023, this study involved teachers, college students,

and librarians, with 111 survey responses analyzed. Respondents completed activity surveys

from module 5 of a six-module open online course and a registration survey. Digital citizenship

practices were measured on a 5-point Likert scale, with responses ranging from 1 (never) to 5

(all the time). A similar scale assessed respondents' familiarity with technology, tools, and

operations, ranging from 1 (poor) to 5 (excellent).

The study utilized statistical tools to analyze demographic profiles, technological expertise,

and responsible social media use. Frequency and percentage were used to describe the

demographic breakdown and respondents' engagement with technology. The mean values

evaluated respondents' familiarity with technology, while the mean of means determined their

digital citizenship practices. A chi-square test assessed significant relationships between

variables.

Of 111 participants, 87.39% were female and 12.61% were male. All respondents were from

public institutions. Regarding technological engagement, the largest groups were "Spectators"

(33.33%) and "Joiners" (29.73%), followed by "Creators" and "Conversationalists" (each

11.71%). A smaller number identified as "Critics," "Collectors," and "Inactives." Overall,

respondents demonstrated a "GOOD" level of familiarity with technology, averaging a mean of

2.86. They showed the highest familiarity with "Social Media" (mean = 3.68) and "Becoming a

Responsible Social Media User" (mean = 3.54). In contrast, their familiarity with topics like

"Trolls" and "Deep Fake Technology" was rated as "FAIR."

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The results indicate that respondents engage in digital citizenship practices "Frequently"

(mean = 3.88). In terms of etiquette, they often avoid online conflicts, follow school mobile

phone rules, and are mindful of others' feelings online. However, they sometimes lose their

temper or engage in trolling (mean = 3.89). Regarding responsibility, respondents are

frequently aware of copyright infringement and acceptable use policies, though some admit to

occasionally downloading digital content without paying or submitting copied schoolwork

(mean = 4.03). In mental wellness and physical health, respondents practice good posture

while using computers but sometimes regret their posts or feel misunderstood online (mean =

3.77). For commerce, respondents are diligent when shopping online, reviewing transaction

details, and securing receipts (mean = 4.14). In security, they frequently update their browsers

and antivirus software, although some engage in risky behaviors like pretending to be

someone else online (mean = 3.55).

The study presented scenarios about a first-time Facebook user to assess respondents'

decision-making in digital contexts. In the first scenario, where the user was advised to create

a Facebook account for a class, 65.77% of respondents provided correct advice, while 34.23%

gave incorrect suggestions. In the second scenario, 77.48% of respondents correctly

recommended how to help a friend venting about a teacher online. In a third situation involving

a suspected theft, 69.37% suggested appropriate actions, while 81.98% identified responsible

social media practices based on the scenario.

The chi-square test revealed no significant relationship between digital citizenship practices

and responsible social media use (Χ² = 2.569, p = 0.63). However, a significant relationship

was found between digital citizenship practices and gender (Χ² = 19.958, p = 0.00017), while

no significant relationships were observed for the type of institution, technological familiarity,

or technologic ladder.

Similarly, no significant relationships were found between responsible social media use and

any socio-demographic variables, including gender, type of institution, technological familiarity,

and technological ladder, with p-values exceeding the 0.05 threshold in all cases.

In conclusion, this study highlights that Filipino students demonstrate strong digital citizenship

practices, particularly in etiquette, responsibility, and online commerce. However, there are still

areas for improvement, especially in mental wellness and security. While gender influences

digital citizenship practices, other socio-demographic factors, such as institution type and

technological familiarity, show no significant effects. The lack of a significant relationship

between digital citizenship practices and responsible social media use suggests these are

related but distinct aspects of digital engagement.

To enhance digital citizenship and responsible social media use, institutions should implement

targeted educational programs that address these areas as complementary aspects of student

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development. Fostering responsible digital behavior and informed social media practices is

essential for students’ academic success, personal growth, and readiness for the digital

professional landscape. Institutions must prioritize comprehensive digital literacy programs

emphasizing ethical and responsible engagement in the digital world and enhancing

technological skills.

Keywords: digital citizenship, responsible use of technology, netiquette,

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Understanding and Practice of "Programming Education in Primary and

Secondary education " as a Liberal Arts Subject

Noriko Suzuki

1)

Joji Maeno

1)

and Katsuhiko Kakehi

2)

1) Tokyo Online University, Japan

2) Waseda University, Japan

Introduction

Information and information technology have become the foundation of modern society, and

their importance is expected to continue to grow. As a result, many countries around the world

have begun to focus on education in these areas (information education) throughout primary

and secondary education.

In Japan, while this has not necessarily been implemented systematically or comprehensively

until now, programming education has been made compulsory in elementary schools from the

2020 academic year and in junior high schools from the 2021 academic year.

With this change in education policy, higher education institutions also need to respond to the

needs of a new generation of learners.

Tokyo Online University is a distance learning university that opened in April 2018. It is

basically composed of video distribution (media classes) and practical classes and operates

on a four-term system. The university consists of two faculties: the Faculty of Information

Management and the Faculty of Human Welfare. While the majority of students were in their

30s and 40s when the university first opened, by the 2023 academic year, about 60% of new

entrants were in their teens and 20s (Figure1).

Figure1.Age Composition of Students at Admission (All Faculties)

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Course Design

Course Overview

"Programming Education A" focuses on understanding the purpose and content of

programming education, rather than acquiring programming skills. Students learn about the

purpose of introducing programming education in elementary and junior high schools and the

content of instruction, and through the practice of block programming, etc., they reflect on

systematic information education throughout the primary and secondary stages, and consider

the possibilities of programming and the structure of modern information society.

Course Objectives

The main objectives of this course are as follows:

- Understand the purpose of introducing programming education

- Grasp the content of programming instruction in elementary and junior high schools

- Learn the basics of programming

- Consider future social visions

Course Content

The course consists of the following main topics:

- History of programming and its education

- The concept of "information utilization ability"

- Programming in scripting languages (JavaScript)

- Block programming (e.g., micro:bit)

- Basics of computational thinking

- Information ethics and security

Teaching Materials and Practical Exercises

The course utilizes the following materials and exercises:

- Block programming environments such as Scratch and Blockly Games

- Learning the relationship between HTML files and websites

- Learning basic programming concepts using JavaScript (sequential processing, iterative

processing, branching, etc.)

- Learning the concepts of variables and random numbers using micro:bit

Promoting Self-Learning

This course actively utilizes external free materials and is designed to allow students to engage

in computational thinking and introductory programming even after the course ends, according

to their interests.

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Comparison with Previous Research

Current online programming education is offered in various formats such as game-based or

video-based learning, primarily focusing on practical skill acquisition through coding. In

contrast, this course adopts a unique approach that combines understanding of programming

education with basic practical application.

In distance learning universities, automated grading systems are often implemented. Cyber

University, for instance, conducts classes using Goorm IDE developed by codigm and Sharif-

Judge created by Mohammad Javad Naderi.

Tokyo Online University provides an automated grading system called "coderoom" that

supports C, Java, Python, SQL, and Blockly. Coderoom is a type of integrated development

environment equipped with features such as file management, text editing, program

compilation and execution, and grading.

Coderoom emphasizes communication, enabling not only Q&A sessions with instructors but

also peer code reviews among students

Results and Discussion

The number of students enrolled in this course has maintained a consistently high level from

the 2022 academic year to the 2024 academic year (2022: 1,008 students, 2023: 621 students,

2024: 904 students). In the post-course surveys, many positive comments were received, such

as "My understanding of computational thinking has deepened." However, students with

limited programming or computer knowledge expressed a desire for more detailed

explanations. To address these challenges, we are considering enhancing self-study

guidelines and supplementary materials to promote independent learning.

Conclusion

"Programming Education A" has achieved certain results as a liberal arts subject that provides

an understanding of programming education in elementary and junior high schools and basic

programming experience[1]. In the future, we plan to conduct follow-up surveys of students to

evaluate the effectiveness of this course in more detaii..

References

Kuno, Y.; Tsutomu, W. & Yasuichi, N. (2024). Systematic ICT Education Throughout Primary

and Secondary Schools: Necessity and Curriculum Proposal [初等中等段階を通した情

報教育の必要性とカリキュラム体系の提案]. IPSJ Transactions on Computers and

Education, 1(3), 48-61. (2015).

Markus A. Launer CoSiM Conference Proceeding (2024)

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Ministry of Education, Culture, Sports, Science and Technology-Japan. Guide to Programming

Education in Elementary Schools (3rd ed., 2024) [小学校プログラミング教育の手引（

第三版）],2020,https://www.mext.go.jp/content/20200218-

mxt_jogai02100003171_002.pdf. Accessed 15 Oct. 2024.

Yusuke, N. (2017). Practical Environment for Programming Education at a Fully Online

University [フルオンライン大学におけるプログラミング系教育の演習環境]. E-

learning Studies, vol. 6, 2017, pp. 33-38. https://www.cyber-

u.ac.jp/about/e_learning/6.html. Accessed 15 Oct. 2024.

Yorito, T, (2017). Design of a Programming Exercise Environment Combining Block-Based

Materials and Online Judge [ブロック型教材とオンラインジャッジの結合によるプロ

グラミング演習環境の設計]. E-learning Studies, vol. 6, 2017, pp. 39-44.

https://www.cyber-u.ac.jp/about/e_learning/6.html. Accessed 15 Oct. 2024.

Maeno, j.; Kakehi, K., Suzuki, N. & Nakamura, S. (2023). Programming Education at Tokyo

Online University. Modern Management,Dijitalization,Sustainabiliity&Social Science

7th international Conference (CoSiM). 204-210

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Behaviours and Attitudes of Students Towards AI Technology

Anna Jasiulewicz

1)

, Fatih Çetin

2)

and Marzena Lemanowicz

1)

1) Warsaw University of Life Sciences

2) Baskent University

Abstract

The overall objective is to present the results of a quantitative study examining students'

behaviors and attitudes toward AI technology.

Theoretical Background

Although artificial intelligence (AI) has appeared on the market relatively recently, it already

has many applications. It is used in medicine, industry, marketing, finance, and science and

cannot be excluded from education (Salas-Pilco & Yang, 2022; Zhai et al., 2021). Currently,

there is no single definition of AI. The European Parliament has defined it as the ability of

machines to exhibit human skills such as reasoning, learning, planning, and creativity. To some

extent, AI can adapt its behavior by analyzing the effects of previous actions (European

Parliament 2020). AI is bringing revolutionary changes to higher education, involving new ways

of learning and acquiring knowledge (Walczak & Cellary, 2023). Therefore, it is essential to

analyze students' attitudes and behaviors toward AI, and universities should provide instruction

to students to increase student awareness of the benefits and risks of using AI-based tools

(Katsantonis & Katsantonis, 2024), as well as develop regulations to determine to what extent

the technology can be used in education.

Methods, Results, and Discussion

The CAWI method was used to conduct the research. The tool was an online survey. The

study was conducted among 400 students from various Polish universities with multiple

profiles.

Results show that students use AI most for homework (39%) and language translation (38%).

One-third of them use AI to create presentations (33%), one-fifth to organize work (22%) and

write term papers (20%). Quite a significant percentage (28%) of students declared that they

do not use AI for any activities related to functioning at the university. However, in response to

the question about the future use of AI, only 18% do not intend to use it. Similarly, according

to Niescior et al. (2024), students use ChatGPT and other AI-based tools for various

educational purposes: 78% declared using AI to solve tasks/assignments, 53% to help write

essays/thesis/compositions, 51% to search for information, and 45% to translate text into

another language.

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Students have no clear opinion on whether AI technologies are more operative than other

digital technologies (45%). Only 32% agreed that AI technologies characterized by human-like

intelligence work more effectively than other digital technologies such as the Internet, IOT,

Cloud, Big Data, and Blockchain.

Students assessed their competencies in the area of using artificial intelligence technologies.

About half of them indicate that learning to use AI technologies is easy for them (47%) and

that such technologies are simple to use (50%). As Venkatesh et al. (2023) state, students'

perceived knowledge, skills, and attitudes affect the intention to use AI.

Half of the students believe that AI technologies have a lot of knowledge to be used, and 44%

consider that these technologies can perfectly cope with the tasks given to them. Half of the

students think that AI technologies have extensive knowledge regarding the required scope of

their work. Also, nearly half state that they are well-specialized, which can increase their

efficiency (45%). A significant proportion of students consider using AI technology as a

pleasant and smart approach to performing tasks (51%). Some believe that AI technologies

are distinguished by their diagnosis precision (40%). Many assume that AI technologies are

characterized by a wealth of knowledge and information organization (51%) and support the

formulation of suggestions (57%).

Many students have a positive (47%) or neutral (32%) attitude toward AI technology, and 42%

would like to develop their competencies in using artificial intelligence as part of their university

classes. These results confirm previous findings (i.e., Samukul et al., 2022; Haryanto, 2019;

Muñoz et al. 2023). According to research by the Chalmers University of Technology, Swedish

students have a positive attitude towards artificial intelligence. When describing AI chatbots,

which are a source of knowledge and inspiration for them, they often refer to them as their

tutors, teachers, mentors, or peers (PARP, 2023). Delcker et al. (2024) suggest that a positive

attitude has a positive influence on the intention of use of AI-tools

Students maintain a neutral attitude towards trust in artificial intelligence and its honesty. Only

a quarter believe that AI technologies are trustworthy in their actions, and 29% of students

indicate that AI does not abuse the information and its advantage over its users. The most

common response was "neither yes nor no" to statements regarding AI fairness. Twenty-six

percent of students have a lot of confidence in AI technology skills, while 32% do not trust

them, and 42% have no opinion. Likewise, Students are divided on the perception of AI safety.

Thirty-two percent of respondents trust that their personal data is protected from potential

misuse when using AI technology, but 33% do not show such confidence. In addition, 38% do

not trust that the authorities exercise effective control over organizations and companies

providing AI technologies, while 29% do. Over a third of students do not believe their privacy

is effectively protected when using AI technology. Also, according to Amoozadeh et al. (2024)

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students have various levels of trust in AI. Alzyoud et al. (2024) indicate that perceived trust

significantly affects the willingness to accept AI in education.

Conclusions

The results showed that students use AI technologies for various study-related activities, and

they plan to use them in the future. This may suggest that AI technology is already accepted

mainly among this group and that there is a growing interest in it as a tool supporting effective

management of duties. About one-third of students are convinced that using AI technology

increases their capabilities in the surrounding environment, possibly due to positive

experiences related to using this technology. Students believe they can easily acquire skills in

using AI technology, which suggests that there is potential for increasing competence in this

area. Such perception can contribute to expanded efficiency in performing tasks. Results

indicate that beneficial experiences associated with using AI may significantly influence the

perception of this technology in the future.

Students do not show a clear position on the issue of trust in artificial intelligence, its honesty,

safety, and data protection while using it. The majority of surveyed students are cautious about

using AI technology. This may be due to concerns about its operation, decisions, or lack of

transparency.

Due to the non-representative nature of the research sample, the presented data is illustrative.

However, it contributes to the existing literature and it can serve as a guide for stakeholders

who want to encourage students to use AI in the future.

References

Alzyoud, M., Al-Shanableh, N., Alomar, S., AsadAlnaser, A., Mustafad, A., Al-Momani, A., &

Al-Hawary, S. (2024). Artificial intelligence in Jordanian education: Assessing

acceptance via perceived cybersecurity, novelty value, and perceived trust.

International Journal of Data and Network Science, 8(2), 823-834.

Amoozadeh, M., Daniels, D., Nam, D., Kumar, A., Chen, S., Hilton, M. & Alipour, M. A. (2024).

Trust in Generative AI among students: An exploratory study. Proceedings of the 55th

ACM Technical Symposium on Computer Science Education, 1, 67-73.

Delcker, J., Heil, J., Ifenthaler, D. Seufert, S., & Spirgi, L. (2024) First-year students AI-

competence as a predictor for intended and de facto use of AI-tools for supporting

learning processes in higher education. Int J Educ Technol High Educ, 21, 18

https://doi.org/10.1186/s41239-024-00452-7

European Parliament (2020). Sztuczna inteligencja: co to jest i jakie ma zastosowania?

https://www.europarl.europa.eu/news/pl/headlines/society/20200827STO85804

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Haryanto, E. (2019). Students' attitudes towards the use of Artificial Intelligence Siri in EFL

learning at one public university. International Seminar and Annual Meeting BKS-PTN

Wilayah Barat, 190–195.

Katsantonis, A., & Katsantonis, IG. (2024). University Students' Attitudes toward Artificial

Intelligence: An Exploratory Study of the Cognitive, Emotional, and Behavioural

Dimensions of AI Attitudes. Educ. Sci.14, 988.

https://doi.org/10.3390/educsci14090988

Muñoz, S., Gayoso G., Huambo A., Tapia R., Incaluque J., Aguila O., Cajamarca J., Acevedo

J., Rivera H., & Arias-Gonzáles J. (2023), Examining the Impacts of Chat GPT on

Student Motivation and Engagement, Social Space, 23

Nieścior, J., Radziszewska, K., Wróbel, D., & Szydło, J. (2024). Wpływ rozwoju technologii AI

na zaangażowanie w proces edukacyjny studentów Wydziału Inżynierii Zarządzania

Politechniki Białostockiej, Akademia Zarządzania, 8 (3), 348-372, DOI:10.24427/az-

2024-0052

PARP (2023) Wykorzystanie sztucznej inteligencji w edukacji. Rynek pracy, edukacja,

kompetencje. Aktualne trendy i wyniki badań, wydanie specjalne, 10.2024

Salas-Pilco, S.Z., & Yang, Y. (2022). Artificial Intelligence Applications in Latin American

Higher Education: A Systematic Review. Int. J. Educ. Technol. High. Educ. 2022, 19,

21

Sumakul, D.T.Y.G., Hamied, F.A., & Sukyadi, D. (2022). Advances in Social Science,

Education and Humanities Research, volume 624, 52-57

Venkatesh, M., & DavisDavis, G. B. F. D. (2003). User acceptance of information technology:

Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540

Walczak, K., & Cellary, W. (2023). Challenges for Higher Education in the Era of Widespread

Access to Generative AI. EBR 2023, 9, 71–100

Zhai, X., Chu, X., Chai, C.S., Jong, M.S.Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li,

Y. (2021). A Review of Artificial Intelligence (Ai) in Education from 2010 to

2020. Complexity 2021, 2021, 8812542.

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Philipine Farmer`s Digital Assistant: a Web-based Land Preparation and

Planting Information System

Edgar B. Agos

1)

and Dave E. Marcial

2)

1) Zamboanga del Sur Provincial Government College, Philippines

2) Silliman University, Philippines, Orcid No. 0000-0003-0006-8841

Abstract

Philippines' agriculture is critical in sustaining livelihoods, particularly in rural communities

(Food and Agriculture Organization (FAO). Despite the sector's importance, many farmers still

rely on traditional methods, limiting productivity and resource efficiency. Integrating information

technology (IT) into agricultural practices offers a significant opportunity to modernize farming,

boost productivity, and promote sustainable practices (Babar, Akan, 2024). The Zamboanga

del Sur Provincial Government College (ZSPGC), situated in Mindanao, has recognized this

need, initiating a project to digitize land preparation and planting management for local farmers

through a web-based system called the Farmer's Digital Assistant.

Keywords: Agricultural technology, Web-based systems, Sustainable agriculture, IT

integration in farming, Farming Data management, Agricultural innovation.

Keywords:

Background and Problem Identification

The ZSPGC supports local farmers through initiatives such as the "plant now, pay later"

program, which promotes organic farming. The program provides essential resources,

including free equipment, seeds, organic fertilizers, and sustainable practices training. The

College focuses on organic agriculture to improve soil health, ensure proper land preparation,

and increase crop yields. However, despite these efforts, the current system for managing

farmer information and resources remains inefficient. It relies on a combination of manual and

basic computerized processes, making data management cumbersome and prone to errors.

Farmers receive training on organic methods, including seed distribution and fertilization

schedules, and the College assists with purchasing crops and organizing harvest schedules.

Despite having computers, the College primarily uses them for basic tasks like desktop

publishing, with records stored in spreadsheets and Word documents. The lack of an

integrated digital system makes it difficult to manage large volumes of data effectively, track

resources, and provide timely recommendations to farmers.

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Project Objective

The Farmer's Digital Assistant was developed to address the inefficiencies in the College’s

current system and improve agricultural operations. The project's primary objective is to create

a web-based platform that streamlines land preparation, planting, and resource management.

The system automates key processes such as ordering seeds and farming equipment, tracking

crop progress, managing farmer records, and providing real-time recommendations. Doing so

aims to enhance communication between the College and farmers, improve data

management, and support more sustainable farming practices.

Method

The study employed both descriptive and software development methodologies. Data were

collected through questionnaires and interviews with farmers and the College’s agriculture

department staff. The farming methods and guidelines from departmental documents were

analyzed to inform the system's design. The development followed the waterfall model, which

involved distinct phases, including requirements gathering, system design, implementation,

testing, and deployment.

The system was developed using PHP for web development, MySQL for database

management, and Lucidchart for creating diagrams. It was designed to automate tasks such

as calculating seed and fertilizer requirements based on planting area, generating crop

monitoring reports, and providing tailored recommendations to farmers. The input-process-

output framework was used to structure the system, ensuring that each function—such as

registration, monitoring, and ordering—worked efficiently and delivered the expected

outcomes.

Results and Discussion

The Farmer’s Digital Assistant significantly improves the existing manual system at ZSPGC by

automating various agricultural processes. Key modules of the system include:

1. Ordering and Reservation Module: Farmers can easily order seeds and farming

equipment. The system tracks availability and allows farmers to reserve equipment,

improving the management of resources.

2. Monitoring Module: This module tracks real-time crop growth and borrowed equipment.

Farmers can input data on crop status, and the system provides updates and

recommendations on crop management, improving decision-making and resource

allocation.

3. Harvest Calculator: The system automatically calculates the optimal number of seeds,

fertilizers, and pesticides needed based on the size of the planting area. It also

estimates harvest dates, allowing farmers to plan labor and resources more effectively.

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4. Analytics and Visualization Tools: The system provides real-time insights into farm

productivity, crop status, and resource utilization through graphical reports. These tools

help farmers and administrators identify trends and make informed decisions to

optimize farming practices.

5. Notification Module: Farmers receive timely notifications about their orders, crop health,

and recommendations. This ensures that they stay informed and can address issues

as they arise.

6. Sales Module: This module records sales transactions, providing a centralized platform

for managing sales data. It enables seamless communication between farmers and the

College, ensuring accurate tracking of harvested crops and revenue.

Testing of the system with both administrators and farmers demonstrated its effectiveness.

Administrators noted that the system streamlined processes, particularly data management

and communication with farmers. Farmers found the system user-friendly and reported that it

simplified tasks such as ordering equipment and monitoring crop health. Test results showed

high satisfaction in key areas such as registration, monitoring, and ordering, with strong

feedback supporting the system’s user-friendly interface and functionality.

Conclusion

Implementing the Farmer’s Digital Assistant offers a promising opportunity to enhance

agricultural practices in the Philippines. The system provides farmers with actionable insights

on land preparation, crop management, and resource use, fostering more sustainable and

productive farming methods. By integrating IT into agricultural operations, the College can help

farmers improve yields, reduce environmental impact, and strengthen their livelihoods.

The system’s modules—ordering and reservation, monitoring, harvest calculator, analytics,

and sales—modernize agricultural operations, improving resource management and decision-

making. The ability to track crop status, receive real-time recommendations, and manage

transactions through a centralized platform enhances efficiency and communication between

farmers and the College.

Recommendations

It is strongly recommended that the ZDSPGC College of Agriculture implement the Farmer’s

Digital Assistant as soon as possible, ideally at the beginning of the new year. This timing

would allow for a smooth transition, enabling the College to start fresh with record-keeping and

conduct thorough testing. Delaying implementation could diminish pilot users' enthusiasm and

slow the system's adoption.

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Furthermore, the College should implement a training program for staff to ensure they are

proficient in using the system. A parallel run of the manual and digital systems for at least one

month is recommended to identify any challenges and refine processes. Future projects should

follow a prototyping model, as hands-on experience with the system during development leads

to better-defined requirements. By adopting this web-based system, ZDSPGC can greatly

enhance its support to farmers, improve agricultural efficiency, and contribute to the

sustainability and prosperity of farming communities in the Philippines.

References:

Food and Agriculture Organization (FAO). (n.d.). FAO in Philippines: Philippines at a glance.

Retrieved from https://www.fao.org/philippines/fao-in-philippines/philippines-at-a-

glance/en/

Babar, A. Z., & Akan, O. B. (2024). Sustainable and precision agriculture with the Internet of

Everything (IoE). arXiv preprint arXiv:2404.06341. Retrieved from

https://arxiv.org/abs/2404.06341

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Smart City Concept for Small-Town country-side Cities

Michael Kindahl

1)

Joachim Delekat

2)

and Markus Launer

3)

1) AS Company, Sweden

2) Member of the City Parliament of Uelzen, Germany

3) Ostfalia University of Applied Sciences and unabhängiges Institut für gemeinnützige

Dienstleistungen (non-profit Organization), Orcid No. 0000-0001-9384-0807

Abstract

This literature paper is a non-systematic literature review on smart cities, e.g. for small town

and country-side cities. The aim is to give an overview on the latest research. It is the basis for

discussion with representatives in the city of Uelzen, Germany.

Introduction

Smart city initiatives are being implemented worldwide to tackle long-term urban challenges

and enhance residents' quality of life (Camero, A.& Alba, E., 2019). Cities are also expected

to address global challenges like sustainability, decarbonization, and resilience (Yigitcanlar et

al., 2019). These initiatives span various fields, including sustainable infrastructure

development, new mobility solutions, smart urbanism, citizen participation, city governance,

and sustainability efforts (Voytenko et al,. 2016). While their goals, technologies, and priorities

may vary, they all share a common belief in the transformative potential of digital technologies

as a key driver for positive and sustainable urban development (José & Rodrigues, 2024).

Lately we recognize a drastical change in small countryside cites due to rapid urbanization.

Millions of people joining urban and small town areas each year, cities are expected to

dominate the planet by the second half of this century (Grayman et al. 2012). Researchers at

MIT Media Lab estimate that by 2050, up to 80% of the global population will live in cities,

which will account for 90% of population growth, 80% of economic output, and 60% of total

energy consumption (Larson et al. 2012; (Portmann & Finger, 2015).

Providing services in Smart Cities demands new governance and strategies. The rise of Smart

Cities stems from their increasing societal importance and the availability of technologies that

enable both new and traditional ideas (Townsend 2014). By combining ubiquitous computing

(sensor technologies and analytics) with modern governance models, data-driven approaches

can improve city planning and management (Manville et al. 2014). Ubiquitous computing,

supported by the Internet of Things (IoT), helps people without being disruptive (Portmann &

Finger, 2015).

Cities are complex, nonlinear systems that grow unpredictably. Designing Smart Cities with a

rigid economic approach focused on equilibrium is ineffective (Sennett 2012). Instead,

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leveraging new technologies through open, adaptive systems emphasizes coordination over

strict regulations. The Internet, as the backbone of Smart Cities, supports this coordination,

with the Internet/Web of Things acting as a crucial component (Townsend 2014).

Connecting stakeholders like residents, businesses, politicians, and NGOs through the

Internet and Web offers a way to manage the complexity of cities, which is shaped by

emergence, nonlinearity, and self-organization. The Internet enables new forms of

collaboration and interaction (Portmann & Finger, 2015).

Collective intelligence is crucial to Smart Cities, driven by the Internet/Web creating an

interconnected environment for stakeholders. This expands online connections, often blending

into the physical world (Caine and Caine 2011). Enhanced collective intelligence emerges from

the synergy between humans and computers (Portmann, 2013), where intelligence is viewed

as a group phenomenon involving people, computers, or both.

Internet and web technologies are transforming cities into Smart Cities (also called Digital,

Intelligent, or Ubiquitous Cities). This shift requires collaboration across various fields such as

architecture, urban planning, computer science, politics, and sociology. A holistic approach

that integrates these disciplines is vital for the cities we will live in.

Definition of Smart City

In a recent study by Hajek et al. (2022), over 100 articles on smart city assessments were

analyzed, revealing three main approaches: (i) cities shaped by technology, (ii) cities that

emphasize people, and (iii) cities that integrate both technology and a human-centered

approach. Over time, the focus has shifted towards human-centered and "soft" infrastructure,

such as institutions, citizen engagement, and social innovation (Sharifi, 2019).

According to the literature, smart cities are defined across six key dimensions: economy,

people, governance, mobility, environment, and living (Concilio et al., 2013; Hajek et al., 2022;

Koca et al., 2021; Lazaroiu & Roscia, 2012). These dimensions cover areas such as

entrepreneurship, equality, participation in public life, transparent governance, sustainable

transportation, resource management, and quality of life. Smart cities rely on information and

communication technologies (ICT) to enhance these dimensions and create more efficient,

sustainable urban environments.

Information and communication technologies (ICTs) are central to the smart city concept,

facilitating integration across city dimensions by creating connected platforms for stakeholders

(Airaksinen et al., 2018). ICT enhances city operations' efficiency, competitiveness, and

capacity, providing new insights and services (Angelakoglou et al., 2019). Smart cities use ICT

to promote sustainable development and improve quality of life (Hajduk, 2020).

The main objectives of smart cities include solving urban challenges like energy consumption,

environmental protection, and quality of life (Angelakoglou et al., 2019; Patrão et al., 2020).

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According to Sharifi (2019), smart city projects help cities remain competitive, attract talent,

address sustainability issues, transition to a low-carbon society, improve urban management

transparency, and tackle socio-economic challenges (Karal & Soyer, 2024).

Characteristics of a Smart City

A city becomes smarter by gathering and utilizing high-quality data (Hurwitz et al. 2015).

Internet- and web-based services analyze urban data, or Big Data, making it accessible to

stakeholders. Machine learning helps process unstructured data, while sensors monitor city

conditions, enabling Ubiquitous Computing, where AI is integrated into the physical

environment (Portmann & Finger, 2015):

Smart Cities require more than just technology. To address rapid urbanization, new strategies

are needed to manage complexity, boost efficiency, lower costs, and enhance quality of life

(Razaghi and Finger 2015).In the following, we will briefly outline the individual characteristics,

which will be discussed in more detail in the subsequent articles of this issue.

Smart Place is a location (e.g., building, space, or event) that facilitates and promotes

interaction and connectivity between people, places, and the web through communication,

multimedia, and technology. This human-place-web triangle will increasingly shape our lives,

with Ubiquitous Computing technologies defining how we interact within self- or externally

defined spaces

Smart Living involves housing concepts that leverage connected devices to offer new

possibilities. These concepts often align with the sharing economy, contributing to the

implementation of Shareable Cities.

Smart Work refers to future work environments that are planned intelligently using Big Data.

This can lead to economically motivated sharing concepts, provided they respect individual

privacy (Smart Privacy).

Smart Mobility encompasses intelligent public and private transportation, rooted in the sharing

economy but including additional public transport services. Holistic concepts address both

individual and public transportation.

Smart Logistics focuses on flexible storage and delivery. In the future, logistics will become

highly personalized, with deliveries reaching stakeholders wherever they are, thanks to

Ubiquitous Computing services.

Smart Traffic Management uses dynamic information and complex event processing to enable

self-regulating traffic systems, such as traffic lights that adjust green and red times

autonomously.

Smart Environment is based on Ubiquitous Computing, connecting networks with the physical

world. This concept enables services that help address aging populations, such as supporting

independent living for seniors or those with dementia (Smart Healthcare).

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Smart Energy involves the intelligent production and distribution of energy, with models

encouraging stakeholder participation. Future energy grids will use Big Data to automatically

adapt, improving efficiency, reliability, and sustainability.

Smart Democracy relies on transparency, a key principle that can be enhanced through the

intelligent use of internet and web technologies, such as systems that provide smart voting

recommendations.

Smart Community uses internet and web technologies to shape urban life and work,

emphasizing local engagement and stakeholder collaboration.

Other key features include Smart People, who navigate the online environment freely and have

access to continuous education (Manville et al. 2014), making them vital for Smart Cities. The

Smart Environment concept also includes Smart Healthcare, which focuses on intelligent

services to improve health and well-being (Hurwitz et al. 2015). Smart Work addresses Smart

Privacy, ensuring both physical and digital privacy (Kelly and Ham 2013). Smart Security

covers both physical and digital protection, while integrating water and waste management

with web technologies fosters sustainable urban governance (Manville et al. 2014).

Challenges of Smart Cities

The pace of innovation in Smart Cities appears to lag behind the rapid and disruptive

transformations driven by digital innovation in other sectors. While other domains have

experienced swift changes, the development of Smart Cities seems to be moving at a slower

rate, possibly due to the complexity of urban systems, regulatory challenges, and the need for

broad stakeholder coordination (José & Rodrigues, 2024). The connection between major

smart city challenges and the essential properties of digital innovation needs to be analyzed.

José & Rodrigues (2024) describe five key challenges for innovations for smart city: Strategic

vision; Organizational Capabilities and Agility; Technology Domestication; Ecosystem

Development; and Transboundary Innovation.

Strategic Vision

A strong strategic vision is crucial for smart city initiatives. Sánchez-Corcuera et al. argue that

relying solely on isolated initiatives won't achieve long-term goals or foster collaboration.

However, the ambiguity, technological uncertainties, and disruptive impacts of this shift make

it challenging for cities to gather the necessary drive, knowledge, and support for a cohesive

digital transition. Despite differing views on what a smart city should be, the vision must reflect

community priorities, demonstrate strong leadership, and be deeply rooted in local

understanding (Ben Letaifa, 2015). The complexity and uncertainties, coupled with limited

proven models, require bold decisions in a rapidly changing environment (José & Rodrigues,

2024).

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Organizational Capabilities and Agility

The digital transition marks a major shift in city management, requiring new analytical,

administrative, and political capabilities, along with more transparent infrastructure governance

across sectors and scales. Even with a strong strategic vision in place, cities must significantly

adapt their governance processes to align with this new reality. Often, challenges such as

organizational misalignments, resistance, and unmet expectations are underestimated,

complicating the path forward (Ramaswami et al, 2015).

Technology Domestication

The central idea of smart cities is that ICT will play a key role in city operations and various

aspects of urban life. However, the specific ways these technologies will create value for cities

are often vague or misunderstood. Too much emphasis is placed on the technology itself,

rather than on how it integrates into the city's structure. The real challenge lies in balancing

technological potential with the actual value derived from its practical application (José &

Rodrigues, 2024; Rogers, 2003).

Ecosystem Development

A common approach in smart city initiatives is building a local innovation ecosystem. This helps

local governments access financial resources, innovators, skilled workers, and shared

knowledge. By promoting collaboration between stakeholders, such ecosystems foster

innovation and generate value from connections between research, communities, businesses,

and technology. However, while their importance is widely acknowledged, no ecosystem can

fully solve all the challenges of smart city development (Gupta, Mejia & Kajikawa, 2019).

Additionally, creating and maintaining such ecosystems presents its own challenges, which

can be grouped into four key areas: collaborative innovation, governance models, business

models, and citizen engagement (Ferraris, Santoro & Pellicelli, 2020; José & Rodrigues, 2024).

Transboundary Innovation

The previous section highlighted the importance of local ecosystems in turning smart city

concepts into concrete policies (Komninos et al, 2022). However, survey results indicate that

an overemphasis on local innovation can lead to a fragmented urban innovation landscape

(Wang, 2019). This fragmentation, with isolated ecosystems independently addressing similar

challenges, creates inefficiencies and limits the collective impact. The key challenge for smart

city initiatives is finding ways to foster collaboration, enabling combinatorial innovation and

shared learning to consolidate successful practices and accelerate progress (José &

Rodrigues, 2024; Yoo et al., 2012))

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Performance Indicators for Smart Cities

Karal & Soyer (2024) analyzed and evaluated studies on smart cities, offering a framework for

measuring the smartness of urban areas. Measurability, availability, completeness, relevance,

independence, reliability, currency, responsiveness, simplicity, representativeness, cost-

effectiveness, consistency, comparability, and consensus were among the criteria identified

from the literature set to distinguish performance indicators. Data quality emerged as a primary

concern in selecting performance indicators. Indicators were chosen based on whether their

data was measurable by various methods, easily accessible, trustworthy, verified, and current

(Karal & Soyer, 2024). The most commonly cited criteria for selecting indicators in the literature

were measurability, availability, reliability, and representativeness. Standards from credible

organizations like ISO, OECD, and the European Environment Agency, along with previous

literature, were utilized to create reliable performance measurement systems. Two commonly

used models were the ISO 37120 standard, with 104 indicators across 19 dimensions, and the

"Smart Cities: Ranking of European Medium-Sized Cities" report by Giffinger et al. (2007),

which includes 74 indicators across 6 dimensions. The construction of measurement systems

for evaluating smart sustainable city performance can vary depending on the city, available

data, or the decision-makers' approach. Most studies have used an expert-led approach,

drawing on indicators from existing literature on smart and sustainable city performance. This

highlights the need for more citizen-led and globally-focused approaches to performance

measurement systems (Karal & Soyer, 2024).

Smart Cities and Sustainable Development

In 2015, the United Nations launched the Sustainable Development Goals (SDGs) to tackle

growing global socio-economic and environmental challenges and promote more sustainable

pathways for future generations (Habitat, 2021). Despite extensive research on smart cities,

there is a lack of studies exploring the connections between smart cities and the Sustainable

Development Goals (SDGs). Specifically, limited research exists on how smart city solutions

can generate co-benefits or trade-offs in achieving SDGs. A systematic literature review by

Sharifi et al. (2024) aimed to address that gap. A systematic literature review was conducted

to address this gap. The findings indicate that the responsible development and

implementation of smart city solutions and technologies can contribute to progress toward

achieving the SDGs. However, they focused on SDG 11 (Sustainable Cities and

Communities), SDG 12 (Responsible Consumption and Production), SDG 7 (Affordable and

Clean Energy), and SDG 6 (Clean Water and Sanitation). The review revealed a bias toward

highlighting the benefits of smart cities, such as boosting economic growth, enhancing

efficiency, fostering innovation, and raising citizen awareness. These advantages suggest that

smart cities could drive sustainable development and help address climate change. However,

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to fully realize these benefits, it is essential to address trade-offs, including privacy and

cybersecurity concerns, infrastructure costs, rebound effects from efficiency gains, biased

decision-making, social inequalities, the digital divide, AI misuse, and insufficient legal

frameworks (Sharifi et al., 2024).

The growing focus on urban transformation as a key factor in achieving the SDGs has spurred

significant research, emphasizing the pivotal role cities play in driving global change. A report

by the OECD (2022) highlights that many cities have developed policies and frameworks to

guide sectors such as water, housing, climate change, and transport, all of which are critical

to the SDGs. Cities are often more flexible and innovative than central governments, making

them better positioned to implement transformative sustainability actions (Masuda et al., 2022).

Additionally, local governments are seen as ideal candidates for achieving the SDGs due to

their ability to learn from peers and develop tailored policies for local challenges (Leavesley,

Trundle, & Oke, 2022).

Despite these advantages, implementing SDGs at the city level remains challenging, as they

are primarily designed for national adoption. Several studies have pointed out the limitations

of existing indicators for measuring SDG progress in cities, particularly for SDG 11, which

focuses on sustainable cities (Berisha, Caprioli, & Cotella, 2022; Koch & Krellenberg, 2018).

Therefore, further research is needed to identify effective planning models that align with past

agendas, like the Brundtland report (1987), and support SDG achievement at the urban level.

One promising model is the Smart City, which leverages smart technologies for city planning,

management, and operations. Evolving from earlier concepts like digital and knowledge cities,

smart cities now encompass a broader scope. While initially technology-focused, non-

technological aspects such as social innovation and institutional frameworks are increasingly

recognized as essential to enhancing quality of life, addressing global challenges, and driving

sustainable development (Sharifi, 2019).

Sustainability and smartness are closely connected. A comprehensive analysis of city labels

shows that "sustainable city" and "smart city" frequently co-occur (Schraven, Joss, & de Jong,

2021). While some smart city policies may not always align with sustainability goals, such as

reducing CO2 emissions (Yigitcanlar & Kamruzzaman, 2018), other studies highlight how

smart cities can support achieving the SDGs (Schraven et al., 2021).

However, failing to link sustainability with smartness in urban development can lead to risks,

including short-term priorities, elitism, and commercialization overshadowing environmental

concerns (Yigitcanlar et al., 2019). Given this, the potential of smart cities to contribute to SDGs

has gained growing recognition (Deloitte, 2020). Some researchers, like Visvizi and del Hoyo

(2021), suggest that smart cities' technological features enable real-time monitoring of SDG

indicators, supporting targeted program implementation. Additionally, tech-enabled

governance in smart cities enhances citizen participation, crucial for achieving SDGs.

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Smart cities also promote resource efficiency, such as alternative mobility solutions to reduce

fossil fuel dependence and the use of sensors and smart devices to optimize water and energy

consumption through smart metering (Talari et al., 2017; Sharifi et al., 2024)

The Example China

China is a leading country in researching the evaluation of smart and sustainable cities. This

is driven by factors such as the communist regime (Sustainable Development Goals

Knowledge Platform, 2021), an increasingly unstable economy in the past (Roach, 2019), and

challenges from rapid urbanization (Wang et al., 2020; Yi et al., 2022). Additionally, China's

commitment to the 2030 Agenda's economic, environmental, and social goals plays a key role.

With a holistic approach, China funds sustainable development actions, implements integrated

strategies, and promotes public participation and innovation through various projects and

programs (Jiang, 2020).

Conclusion

The article shows a summary of the latest research on smart cities.

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Sustainability and Corporate Social Responsibility

Exploring Corporate Social Responsibility Significance, Practices, and

Challenges encountered by the Hotel Industry in Calabarzon, Philippines

Noelah Mae D. Borbon

National University, Philippines, Orcid No. 0000-0002-4834-6313

Extended Abstract

The hospitality industry plays a crucial role in supporting the tourism sector and local

economies, particularly in popular tourist destinations (Gador, 2019). Corporate social

responsibility initiatives undertaken by hotel establishments can have a significant impact on

the sustainability of the industry and the communities they operate in (Borbon, 2020).

This study aimed to propose a framework of commitment for enhancing corporate social

responsibility (CSR) in the hotel industry in the CALABARZON region. The research

specifically sought to: (1) present the profile of the hotel industry in terms of accommodation

classification, location accessibility, and years of operation; (2) describe the significance of

CSR in terms of economic, legal, ethical, and philanthropic aspects; (3) identify the CSR

practices of hotels concerning environmental efforts, philanthropic activities, social

engagement, and ethical labor practices; and (4) examine the challenges faced by

accommodation establishments in complying with CSR, including political, economic, and

social issues. Additionally, the study tested differences in CSR significance, practices, and

challenges based on the hotel profiles, examined the relationship between the significance

and practices of CSR, and explored the link between CSR practices and the problems

encountered.

A descriptive research design was utilized, with the respondents being employees from

Department of Tourism (DOT) accredited hotels, resorts, and tourist inns in CALABARZON.

Out of 76 accredited establishments, 45 (59.2%) participated in the study, representing various

classifications of accommodations such as hotels, resorts, hotel resorts, and tourist inns. A

total of 130 respondents from these 45 establishments provided data through surveys,

interviews, and focus group discussions.

The research used an adopted questionnaire divided into two parts: one profiling the

respondents, including accommodation classification, accessibility, number of employees,

years in operation, and guest volume; the second assessing the CSR significance, practices,

and problems encountered. The questionnaire was adapted from studies grounded in Carroll’s

CSR framework (Carroll, 2016) and underwent reliability testing, yielding strong internal

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consistency with Cronbach’s alpha values of 0.960 for CSR significance, 0.929 for CSR

practices, and 0.898 for CSR challenges.

Key findings revealed that most hotel establishments were located in coastal areas of

Batangas and had been in operation for 6-10 years. Employees perceived CSR, especially in

its philanthropic aspects, as highly significant, while environmental-related efforts ranked

highest among CSR practices. Economic issues, particularly climate change and population

growth, were the most commonly encountered problems, aligning to the previous study of

Akhouri & Chaudhary, (2019); Simmou et al., (2022); Aminudin, (2013). Resorts showed

significantly higher views on the legal aspects of CSR and higher levels of CSR practices

compared to tourist inns. Furthermore, establishments in operation for 6-10 years had fewer

social issues compared to others. The study also highlighted that a higher perception of CSR

significance, particularly in ethical and philanthropic aspects, corresponded to a higher level of

CSR practices. However, higher CSR practices were also linked to increased economic

challenges, aligning to the previous study of Zheng & Siddik, (2022). Based on these findings,

a framework of commitment was proposed to guide the continuous improvement of CSR in the

hotel industry.

The study recommends appointing a CSR officer within the public relations or human

resources departments to monitor CSR activities and assess their economic impacts. It also

suggests implementing points and reward programs to encourage employees to actively

participate in community CSR initiatives. To further strengthen CSR efforts, universities in

CALABARZON should enhance their CSR programs and integrate these into their curricula to

expand students' commitment to CSR principles. Additionally, the hotel industry should focus

on climate change and pollution by developing awareness programs aimed at protecting the

environment. The study also proposes that CSR implementation be considered as an

additional requirement for DOT accreditation of hotels, resorts, and tourist inns. The proposed

CSR framework should be submitted to the Department of Tourism - CALABARZON for

dissemination and distribution to hotel industry respondents to ensure continuous

improvement of CSR efforts. Lastly, it recommends future research to explore the level of

employee participation in CSR activities and its impact on community development.

This study contributes to the body of knowledge by providing a structured approach to

improving CSR in the hotel industry and offers practical recommendations for stakeholders in

CALABARZON. Further studies are recommended to explore broader aspects of employee

involvement and the long-term impact of CSR initiatives on community and environmental

sustainability.

Keywords: Corporate Social Responsibility, Hotel Industry, Environmental Efforts,

Philanthropy, Calabarzon, CSR Practices, CSR Challenges, Hospitality Industry.

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References

Akhouri, A., & Chaudhary, R. (2019). Employee perspective on CSR: A review of the

literature and research agenda. Journal of Global Responsibility, 10(4), 355-381.

https://doi.org/10.1108/jgr-11-2018-0057

Aminudin, N. (2013). Corporate social responsibility and employee retention of

‘green’hotels. Procedia-Social and Behavioral Sciences, 105, 763-771.

https://doi.org/10.1016/j.sbspro.2013.11.079

Borbon, N M D. (2020, July 14). Evaluation on corporate social responsibility issues in the

view of hotel business in CALABARZON region, Philippines. International Journal of

Research Studies in Education, 9(5). https://doi.org/10.5861/ijrse.2020.5818

Carroll, A. B. (2016). Carroll’s pyramid of CSR: taking another look. International journal of

corporate social responsibility, 1, 1-8. https://doi.org/10.1186/s40991-016-0004-6

Gador, J. E. (2019). Unveiling the Quality of Service, Influences, and Challenges of the

Hospitality Industry in the Local Tourists’ Destination Site in Cebu, Philippines. Journal

of Tourism and Hospitality Management, 7(1), 36-48.

https://doi.org/10.15640/jthm.v7n1a4

Simmou, W., Govindan, K., Sameer, I., Hussainey, K., & Simmou, S. (2023). Doing good to

be green and live clean! Linking corporate social responsibility strategy, green

innovation, and environmental performance: Evidence from Maldivian and Moroccan

small and medium-sized enterprises. Journal of Cleaner Production, 384, 135265.

https://doi.org/10.1016/j.jclepro.2022.135265

Guang-Wen, Z., & Siddik, A. B. (2022). Do corporate social responsibility practices and green

finance dimensions determine environmental performance? An Empirical Study on

Bangladeshi Banking Institutions. Frontiers in Environmental Science, 10, 890096.

https://doi.org/10.3389/fenvs.2022.890096

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A Literature Study on the Use of Ancestral Seeds in the Application Kitchens

of Universities within the Scope of Sustainable Gastronomy Practices

Ercan Karacar

1)

, Rana Şat

2)

, Gör. Serkan Seminit

2)

Dilek Karakas

2)

and Markus Launer

3)

1) Sinop University, Turkiye, Orcid No. 0000-0002-1124-9667

2) Balıkesir University Institute of Social Sciences, Turkiye, Orcid No. 0000-0003-0519-5524

3) Ostfalia University of Applied Sciences and Institut für gemeinnützige Dienmstleistungen

gGmbH (independent non-profit organization), Germany, Orcid No. 0000-0001-9384-0807

Abstract

Due to the inequitable distribution of food in the world and the overuse of resources, it is

predicted that the ability of future generations to consume healthy and organic products may

become a major problem. As the needs of individuals are unlimited and natural resources are

limited, there is a gradual decline in natural resources. Due to the rapid increase in economic

growth and global population, the demand for resources to meet societal needs is increasing

day by day. The supply of organic and healthy food in the world is becoming a problem on a

global scale. Ensuring the sustainability of organic products in the food and beverage

production process is of great importance in terms of transferring the material, spiritual and

cultural gains of the society to future generations. It is seen that the formation process of

organic products multiplies through seeds as in all living things. While preserving the genes of

the past, where seeds are a time capsule, they also play a major role in transferring them to

the future. The loss of seeds means the loss of both our food culture and our future. For this

reason, the protection and reproduction of seeds is one of the rights that we are responsible

for our future generations. Ancestral seeds, which are of great importance for the sustainability

of organic products from the past to the present, are one of the heritage that should be valued

today in terms of the sustainability of the products inherited from our ancestors. Thanks to

ancestral seeds, it is seen that the sustainable development approach has come to the agenda

and as a result of the developments experienced, an institutionalized and culturally established

scope and structuring has been achieved. In this process, it is seen that the effects and results

of concrete practices at local, regional and national level can be observed in the organic

product production process. In this context, the main purpose of this study is to raise

awareness about sustainability, organic nutrition, organic food, local production and local

product production, local dishes, cultural heritage-oriented courses in the education process

of gastronomy and culinary arts, cookery, agricultural engineering fields and to reveal why the

issue of sustainability is so important. In addition, it is aimed to reveal whether this awareness

is gained in the kitchens and courses of the relevant departments of universities, what the

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opinions are, and in which areas it is used. In addition, in this study, the curriculum information

of associate, undergraduate and graduate programs in the departments of Gastronomy and

Culinary Arts, Cookery, Agricultural Engineering in faculties and colleges in Turkey and in

Berlin, Florida, Germany were examined and the faculties and colleges with course content on

sustainability were included in the study. For this purpose, in the 2024-2025 academic year,

academicians and students who received education in associate, undergraduate and graduate

programs within the faculties were reached.

Keywords: Sustainability, Gastronomy Practices, Agriculture, Ancestral Seeds, Gastronomy

and Culinary Arts

Introduction

Global warming, increasing population growth, unconscious and excessive consumption, and

the danger of depletion of natural resources are among the biggest problems today. For this

reason, organic production, organic nutrition and ancestor seeds are on the agenda today.

Due to the decrease in food resources as a result of overconsumption and the resulting

increase in prices, it has become a problem that concerns individuals as well as businesses

and individuals trained in the field of food and beverage. For this reason, the preservation of

ancestor seeds for organic and healthy nutrition and their use in the product production

process will positively affect the costs of both food resources, businesses and individuals

receiving education in the food production process (Ozcicek Dolekoglu, 2017). It is necessary

to support the production of ancestral seeds in order to prevent and reduce negative impacts

on food resources.

It is considered as a need in the perspective of sustainability that institutions providing

education in the field of gastronomy and culinary arts provide rich information in order to

contribute to the sustainability of natural and environmental resources. The concept of

sustainability, which has been emphasized in a global framework especially in the late 20th

century, has become a basic requirement for meeting the individual needs of future

generations. In this context, it is important in terms of sustainable food production by ensuring

long-term and optimum productivity in order to maintain the balance of resources and needs.

In this context, it is possible to mention that there is an increasing interest in issues related to

sustainability in the capacity of future generations to provide access to the same resources

while meeting the needs of the current generation with the use of ancestor seed in sustainable

culinary practices. When the researches on sustainability in the field of gastronomy are

examined, it is possible to mention that studies on issues such as eco-gastronomy,

geographical marking, waste management and waste reduction, supply chain, green

restaurants and green practices, slow food and local food stand out (Yurtseven & Kaya, 2011;

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Durlu, 2013; Cekal & Dogan, 2022; Baran & Karaca, 2021; Güngör & Alperen, 2021; Serkan

& Kılıç, 2022; Ertaş, 2022; Yüceer, 2019; Keskekci & Gençer, 2023; Bilgin & Akoglu, 2018;

Demir, 2021). In this context, it is seen that providing production and product supply with

ancestral seeds is of great importance in terms of reducing the negative environmental impacts

of the sector in order to ensure the sustainable use of natural resources and the effective use

of ancestral seeds for individuals who study and receive education in the fields of gastronomy

and culinary arts, cookery and agricultural engineering (Axelos, 2018).

The strategic adoption of environmental sustainability practices in culinary practices in the food

sector will contribute to more effective management of natural resources and minimization of

negative environmental impacts. In line with this information, the aim of the study is to increase

the importance and value of ancestral seeds in culinary practices and research in the relevant

departments of universities where the use of ancestral seeds in sustainable gastronomy will

be expanded. For this reason, a questionnaire form was applied to learn the attitudes and

perspectives of faculty members and students in the relevant departments of universities in

Turkey and abroad.

Conceptual Framework

The Concept of Sustainability

Sustainability is defined as the ability of a process to conserve natural resources while meeting

the needs of the current generation and leaving a healthy environment for future generations

(Collin, 2004; Meneguel, 2019; Kuşat, 2013). This concept, which has been addressed in a

multifaceted manner in the fields of development, applied science, environment and

international politics in international environmental debates since the 1980s, has gained more

importance and become a focal point today. However, there is still little consensus on the

implications of development strategies or the meaning and definition of sustainability

(Carvalho, 2001). Another definition defines sustainability as the capacity of a society,

ecosystem or any system to continue to function into the indefinite future without depleting or

overloading its basic resources (Gilman, 1992). This definition emphasizes the balanced use

of natural resources in order for systems to continue their existence in a sustainable manner.

The concept of sustainability is generally shaped on three basic building blocks: environmental,

economic and social sustainability (McKeown et al., 2002). Environmental sustainability is

concerned with the conservation of natural resources and the continued healthy functioning of

ecosystems, while economic sustainability argues that development should be economically

sustainable, meaning that economic growth should take place without harming long-term

sustainable development goals. Social sustainability aims to sustain the well-being of societies

over the long term, based on social equity and justice. These three building blocks draw

attention to the fact that sustainability should be addressed by taking into account not only

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environmental but also social and economic dimensions. These interconnected elements show

that sustainable development has profound impacts not only on ecosystems and natural

resources, but also on social and economic structures. Therefore, these three dimensions

need to be considered in a balanced manner when formulating sustainability strategies

(Lehtinen, 2012; Bagheri et al., 2008; Kuhlman and Farrington, 2010). Providing these three

elements in a balanced manner will contribute to the sustainable use of resources, poverty

reduction and the protection of ecosystems (Harris, 2000; Collin, 2004).

Although the concept of “sustainability” first emerged in the 1970s, it was officially defined in

1987 in the “Our Common Future” report published by the United Nations-sponsored World

Commission on Environment and Development (WCED). In this report, sustainability was

defined as “development that meets the needs of the present without compromising the ability

of future generations to meet their own needs”. In the report, the goals for sustainable

development are listed as follows (WCED, 1987):

 The concept of sustainability aims to re-evaluate major environmental and

development problems and to make realistic proposals to address them.

 In this framework, it is important to establish international cooperation methods to

contribute to the development of policies that can make the necessary adjustments to

solve the problems. It is also necessary to increase the interest of voluntary

organizations, individuals, businesses, institutes and governments in sustainability.

 This approach seeks to protect the future and enhance existing values in order to

ensure that human needs are met and that the current needs of residents and tourists

are met.

Sustainable development policies focus on assessing the possible consequences of current

decisions by considering the needs of future generations and are based on the principle of

sustainability. The understanding of sustainability aims to preserve the environmental balance

by minimizing the consumption of natural resources, to ensure fair and equitable economic

development and to increase social welfare. Therefore, sustainable development emphasizes

the need to develop a comprehensive and holistic approach to respond to today's complex

challenges. It aims to build a better future for humanity, taking into account not only

environmental but also social and economic dimensions. In this context, sustainability

assumes the responsibility of both meeting the needs of current generations and leaving a

healthy and balanced world for future generations (Damtoft et al., 2008; Mebratu, 1998). In

addition, the sustainable use of natural resources, namely water, minerals, forests and energy

resources, and long-term investments in these resources make an important contribution to

sustainability (Lovins, 2007). Sustainability is basically addressed in three stages. These are

sustainability in production, sustainability in consumption and post-consumption sustainability

(Veleva, 2021). Considering these three stages together is essential for achieving sustainable

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development, and the integration of all these elements contributes to both protecting the

natural environment and increasing social and economic welfare (Lemanowicz, 2020).

The Relationship between Sustainability and Gastronomy Practices

Today, sustainability practices are an innovative approach in gastronomy and food applications

(Pereira, 2019). It is seen that many chefs around the world prefer materials and products with

sustainability features, pay attention to organic farming and organic product production, pay

attention to the use of micro sprouts, consume products produced from ancestor seeds and

find it valuable to benefit from the product preparation process. For this reason, it is seen that

they generally pay attention to using local and organic ingredients or products that reflect

regional traditional culture (Pereira, 2019; Zaneti, 2017). The connection between gastronomy

practices and sustainability, how to prepare the dishes to be prepared, where and under what

conditions the ingredients will be produced, what to pay attention to in the process of preparing

sustainable products and how to provide products to culinary students in the field of

gastronomy and culinary arts, It includes many issues such as whether meals are prepared

with products consisting of ancestral seeds in applied courses, how much organic and local

products are preferred, what are the environmental impacts in the process of supplying organic

and healthy products regionally, and the level of employment in the process of producing

ancestral seeds and organic products (Pereira, 2023). Sustainable gastronomy practices are

basically based on the sustainable sourcing of ingredients and attention to their processing in

application kitchens (Un, 2024). In this context, sustainability in the process of organic

agriculture and organic product production should include policies and practices that contribute

to the production of local and local, ancestral seeds and products that contribute to fairer and

environmentally friendly local development (Lopes, 2019). In this way, it should be aimed to

ensure the sustainability of these policies in the trainings given in the field of gastronomy,

cookery and agriculture. Under the leadership of the Food and Agriculture Organization of the

United Nations (FAO), within the scope of “Sustainable Gastronomy Day”, based on culinary

practices that do not harm the health of consumers and the local and local universe, those who

provide education in this field and chefs working in the sector should address how the

ingredients are obtained, where they come from, how they are grown, how they should be

grown, the importance of the ancestor seed, how they can spread to the international market

by having a say in the niche market, and ultimately how they reach from soil to table in the

trainings and events they carry out on the sustainability of gastronomy (Sternadt, 2021).

Consumption and production of organic and healthy products form the basis of sustainable

culinary practices. It is important for those who will operate in this field to utilize the Ancestor

seed in the process of supplying healthy products from soil to table (Hall and Sharples, 2024).

Local and regional food consumption, which is an important attraction point for consumers,

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has a significant economic contribution in the tourism sector (Kim, 2012). It is thought that the

use of ancestor seeds in these foods will help to create a sustainable touristic product that

increases tourist spending regionally and extends the tourism season (Everett & Aitchison,

2008). Research shows that tourists allocate a significant budget for food and beverage

expenditures in their travel choices (Okumuş & Çetin, 2018; Kim, 2020). With the increase in

competition in the field of gastronomy and agricultural engineering in the global sense, it is

thought that the use of ancestor seeds in the process of preparing organic products and local

dishes will have a positive effect on the visitor attraction strategies among the destination

choices of tourists in the tourism sector in the region (Dedeoğlu, 2020; Mariani, 2021; Soltani,

2021). In this context, it is thought that individuals who receive education in the field of

gastronomy, cookery and agricultural engineering will be effective in developing various

strategies in order to increase their preference for ancestor seeds in the process of organic

product and local healthy food production and to increase the number of visitors to the region.

The development of sustainable gastronomy and sustainable gastronomy tourism has

multidimensional effects. Increased demand for local food and increased healthy and organic

consumption indirectly increases interest in local raw materials and ancestral seeds, thus

providing more employment opportunities for local people (Torres, 2002). Both the provision

of local food products and the use of ancestral seeds in the production process of local food

and organic food are important for the provision of local resources. In addition, the awareness

of the students who receive education in the field about local food consumption reduces the

carbon footprint as an environmental result by setting an example worldwide in terms of the

services they will provide (Boniface, 2003; Sims, 2009). Raising a generation that is sensitive

to socio-environmental issues will be able to promote actions that support local and local

products, support family farming, local and local production, strengthen the ties between rural

and urban areas, and increase the use of ancestor seeds, contributing to the increase of the

organic product production process (Niederle & Schubert, 2020; Pereira, 2019).

Sustainable Agriculture

Sustainable agriculture is an approach that aims to make more effective and efficient use of

available biophysical and human resources. The main challenge to achieve this goal is to

minimize the use of external inputs and optimize internal resource use. This ensures the

effective use of available resources and minimizes dependency on external systems. This

allows for continuous improvements to be sustained, supporting the conservation of natural

resources while reducing the pressure of agriculture on the ecosystem (Maynard et al., 2020).

Moreover, natural processes are increasingly replacing external inputs, contributing to reduced

environmental impacts (Pretty et al., 1996).

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The fact that policies to ensure food security support productivity in the agricultural sector

offers a great opportunity for these countries to realize their economic development in a

sustainable manner. In this context, the integration of agricultural policies and technological

innovations is important to create a more equitable and efficient agricultural system. Therefore,

sustainable agriculture means different things for different countries. While undeveloped

countries are generally unable to implement sustainable agriculture practices due to

inadequate education and economic conditions, developing countries adopt sustainable

agriculture with the objectives of ensuring food security, preventing environmental problems,

providing healthier living conditions and preventing negative situations in rural areas (Adenle

et al., 2012; Balcı Akova and Tapan, 2022). In this context, each country needs to develop

sustainable agriculture strategies in line with its specific needs and conditions (Mohanty, 2017).

In these countries, efforts to reduce environmental pollution, create a clean environment and

protect human health are at the forefront. Inadequate education and limited economic

resources make it difficult to adopt sustainable agricultural models in these countries, which

negatively affects the effectiveness of agriculture. On the other hand, in developed countries,

sustainable agriculture is more concerned with environmental quality and the negative impacts

of resources on human health (Gafsi et al., 2006). Integrating new agricultural technologies in

these countries would be a critical step to optimize production processes, increase food

security and ensure agricultural sustainability. For example, innovations in water management,

soil improvement methods, crop protection technologies and sustainable fertilization practices

have the potential to increase both the quantity and quality of production. Making agricultural

practices sustainable is necessary both to improve food security and to support economic

development (Crucefix, 1998).

Restaurants, which have a significant economic potential in the food sector, have a great

importance in terms of sustainability in terms of various aspects of the food they serve. Factors

such as the proportion of food used in restaurants, where these foods are sourced, under what

conditions they are produced and how they are served are critical factors to be considered in

the context of sustainability. Restaurants have the opportunity to reduce environmental impact

and fulfill social responsibilities at every stage of the supply chain (Ilbery and Maye, 2005). For

example, organic and seasonal produce sourced from local farmers not only provides a fresh

and nutritious menu, but also demonstrates an environmentally responsible approach by

reducing the carbon footprint of transportation. Furthermore, the sustainability of food

production methods contributes to both protecting ecosystems and supporting agricultural

biodiversity. Factors such as reducing food waste, recycling practices and energy efficiency

are part of restaurants' sustainability efforts. The potential of policies developed to ensure food

security to increase productivity in the agricultural sector is highly effective in helping countries

achieve their sustainable development goals (Higgins et al., 2019; Kim and Hall, 2021).

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Increasing productivity in agriculture is not only limited to increasing production, but also

contributes to raising the incomes of individuals working in the agricultural sector and

improving income distribution in a more equitable way. This situation necessitates the adoption

of sustainable agricultural policies and new agricultural technologies to both increase

agricultural employment and achieve high-yield agricultural production targets (Sims, 2009).

Nature has a limited capacity to resist all kinds of external interventions and to regenerate itself

against the damages it is exposed to. This limited regeneration capability further increases the

importance of maintaining environmental balance. Therefore, protecting the environment and

natural resources at every stage of the development process is one of the primary social

responsibilities of people. The concept of sustainable development emphasizes that natural

resources should be used responsibly (Daly, 2006). Human activities can lead to a range of

impacts that threaten the balance of nature, resulting in reduced biodiversity, degradation of

ecosystems and climate change (Bansal, 2005). Therefore, the principles of environmental

sustainability should be taken into account when formulating and implementing development

policies. Moreover, the conservation of natural resources is not only of environmental but also

of economic and social importance. Rational use of natural resources is a critical step to meet

the needs of future generations. In this context, developing environmentally sensitive policies,

raising social awareness and supporting environmental protection efforts will help people fulfill

their responsibilities in this regard. As a result, respecting the limited regenerative capacity of

nature and taking care not to exceed these limits is essential for a sustainable future (Boz et

al., 2013).

The Importance of Ancestral Seed and Soil in Gastronomy Education

Soil is considered an indispensable living space that is home to many living things. It generally

sheds light on history by providing important data in terms of understanding the processes that

living things and humanity have gone through. Gastronomy, which belongs to the field of social

sciences, can explain some of the information on the history of human nutrition by utilizing the

information obtained as a result of anthropological studies. In addition, data on the biological

processes of soil is a field that should be indirectly associated with gastronomy science. It is

seen that the field of gastronomy focuses more on food, cuisine, tourism and the search for

new flavors. Therefore, it can be thought that there is no need for information about soil and

ancestor seeds in gastronomy and cookery education. However, ensuring that the importance

of the soil and the ancestral seed, which constitute the source of food, is sufficiently understood

is seen as a major deficiency in terms of establishing a healthy relationship between

sustainable food and sustainable culinary practices, which are perhaps among the most

mentioned issues today. According to Cemaloğlu (2021), similarly, the basis of the mistakes

carried out in the practices carried out in the field of food and environment stems from the lack

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of understanding of the importance of soil and organic agriculture science. The fact that this

subject is not included in general education curricula in our country is seen as the main reason

why this deficiency is not eliminated.

Studies in which the concepts of cuisine and ancestor seeds are evaluated together with soil

and blended in application kitchens have been important for a long time in other countries

besides Turkey. Pehlivan and Yavaş (2022) state that such studies in sustainable gastronomy

practices are given much more importance especially abroad and in this context, it is stated

that in some universities, students in gastronomy education carry out studies intertwined with

concepts such as agroecology and permaculture, which include methods for sustainable

agricultural practices. As a result of the knowledge gained by students in these trainings, it is

seen that they are offered the opportunity to experience organic agriculture and organic

products by creating one-to-one hobby gardens in farms and various application areas.

Sustainable gastronomy culinary practices have a very broad perspective in this respect. For

this reason, it is foreseen that multifaceted steps should be taken. In European countries, it is

possible to mention that it is possible to make edible landscape designs in urban areas to be

used in case of a possible global warming and disaster, balcony and roof gardening, organic

hobby gardening and permaculture parks are not approached as a new subject, and that such

applications are more prone and widespread compared to Turkey. For example; in

permaculture parks, it is seen that the people living around the park produce their own organic

food and provide the opportunity to protect the soil and transfer it to future generations by

increasing the amount of organic matter in the soil and climate change by obtaining compost.

In school gardens with edible landscapes for school children in Leith, USA, it was emphasized

that school gardens with low carbon emissions, healthy and organic food production,

emphasizing the importance of biodiversity in sustainable food production, can be passed on

to future generations through transfer to students. He also states that providing trainings in the

garden environment (referring to plants, pollination and composting, etc.) can be realized more

easily even in this age group compared to the classroom environment (dos Santos, 2020). It

has been observed that edible plants found locally in Brazil - despite their high nutritional value

- are not sufficiently utilized in the kitchen. It is aimed to include these plants in the national

food and nutrition to protect the country's biodiversity, in the development of organic

agriculture, and to increase adaptation and resilience to the climate crisis. In this context, the

researchers published a list of edible natural plants belonging to that region. They contributed

to the creation of books with recipes for gastronomic uses of these plants (Moura de Oliveira

Beltrame, 2021). In Turkey, it is possible to mention that there are a small number of

businesses, institutions, farms, etc. that implement sustainable gastronomy in a similar way in

culinary practices. It is seen that some of the subjects such as composting, water harvesting,

organic farming, organic farming, ancestor seed production practices, which are included in

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the content of trainings such as agroecology, permaculture, ancestor seed, which are included

in sustainable gastronomy trainings abroad, are tried to be given in Turkey through courses

carried out with various certificates, some projects in partnership with associations and

universities, and some of the trainings organized by municipalities. In this regard, it is possible

to mention that the aspect reflected in the institutions providing education at undergraduate

and graduate level is almost non-existent. The situation of sustainable gastronomy education;

When the university course contents are examined, it is seen that the courses such as

sustainable tourism, sustainable gastronomy, ecogastronomy, local dishes are especially

focused on tourism, and that their counterparts abroad are compared with school gardens and

greenhouses, farm partners (integrated into sustainable systems, extensive animal husbandry,

beekeeping and agroecology in agricultural production areas) and joint training activities with

artisan food enterprises. However, some nature and climate friendly cooperation texts such as

the “Cooperation Protocol on Creating a Sustainable and Climate Friendly Campus” have been

signed with some universities. Thus, it is aimed to implement zero waste, practices to prevent

food waste, composting, collection and use of roof and rainwater, use of ancestor seeds, and

energy-saving practices in pilot universities (YÖK, 2024). When the websites of the universities

selected for sustainable campus practices are examined, it is seen that their campuses include

practices such as parking areas with herbal production, park design with natural materials, and

waste separation. It is thought that Özyeğin University Gastronomy and Culinary Arts

department is implementing a campus orchard in its education program and in this context,

permaculture trainings, food production, etc. should be included in the curriculum (YÖK, 2024).

With the TUBITAK 4004 project “I Learn in Nature with Permaculture Philosophy for a

Sustainable World”, Yozgat Bozok University became a project partner to provide training for

teachers (TUBITAK, 2024). Within the scope of the “SDU Green, Livable and Sustainable

Campus Project” (2024), which is being implemented under the coordination of Süleyman

Demirel University Water Institute, studies on zero waste and water saving are being carried

out (TÜBİTAK, 2024). It is thought that these similar studies will contribute to sustainability. It

is also encouraging in terms of the spread of sustainable gastronomy studies.

Agricultural education in our country should be carried out through a curriculum in which

monoculture agricultural methods are generally taught. Monoculture agriculture, which is

traditionally practiced, is seen as a major obstacle to ecological sustainability. For this reason,

changes should be made in this regard in order to realize sustainable agricultural methods.

Kanbak (2018) states that monoculture agriculture is the most widely practiced agricultural

production method in the industry. He emphasizes that thanks to this method, it is possible to

grow a single product in the production area. He states that in the realization of practices for

the standardization of agriculture and market control, no plants and animals will be able to live

except for the products that will be produced first, and the importance of agricultural lands will

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increase. Although sustainable food is thought to attract attention depending on the level of

awareness of the society on issues such as climate crisis, water crisis, environmental pollution,

ancestor seed and destruction of ecology, these issues are seen as a major problem that can

deeply affect all humanity. For this reason, it is urgently necessary to support education and

practices for our country and to accelerate ancestral seed practices. In order for these to be

done, it is of great importance for the faculty members who teach gastronomy and culinary

arts, cookery and agricultural engineering to fulfill their responsibilities, especially in

universities, to review the trainings on these issues and include their applications in the

curriculum, to set an example to the public with pilot application areas, and to carry out studies

on this subject together with local and traditional methods.

Methodology

Ancestral seeds are considered one of the basic building blocks of national security. When the

powers that aim to control humanity by disrupting the genetic structure of seeds realized the

disruptions in their own lands, they set Mesopotamia as a focal point. The saying “The greatest

service that can be rendered to any country is to provide its culture with a useful plant seed”

supports this belief (Saracoglu, 2022). As it can be understood from this, ancestral seeds play

a leading role in protecting local and national value and are the center of attention of people

today. The aim of the research is to investigate ancestral seeds, to provide information about

these seeds and to present a written source on this subject to the literature. The research was

designed qualitatively. Document analysis technique was used by utilizing secondary sources.

This analysis technique is used to meticulously analyze the content of written sources (Wach,

2013). Within the scope of the analysis, all written and electronic sources are systematically

analyzed. As in other methods, document analysis method can be used to create a meaning,

develop empirical information and make sense of the researched topic (Corbin & Strauss,

2008). In order to achieve the aim, the relevant literature was reviewed and the most frequently

mentioned ancestral seeds in the sources were compiled. These seeds were identified as

Yellow Wheat, Black Melon, Çanakkale pepper, Ottoman Strawberry, Cranberry and Garlic.

These seeds constitute the sample of the research. Research was conducted as ancestor

seeds and it was seen that these were the most common seeds. For this reason, the research

was limited to these seeds. Information about the seeds was collected between 10.08.2024-

10.10.2024. In order to achieve the aim of the research, the following parameters were set out:

 What are the so-called ancestral seeds?

 What is the chronological order of ancestral seeds?

 What is the sustainability status of ancestral seeds today?

In line with the data obtained, survey technique, one of the quantitative research methods, was

used in the research. The population of the research consists of faculty members and

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associate, undergraduate and graduate students of the Department of Gastronomy and

Culinary Arts, Department of Cookery and Department of Agricultural Engineering in Turkey

and abroad.

The chronological order of ancestor seeds is given in Table 1. When the table is examined, it

is seen that the first product is Yellow Wheat.

Table 1. Chronological Order of Ancestor Seeds

Ancestor Seeds Year

Motherland

Yellow Wheat Neolithic Age Mesopotamia

Black Melon 3000 B.C.E. China

Garlic (Taşköprü Garlic) 2600-2100 BCE Central Asia

Ottoman Strawberry 23-79 AD France

Canakkale Pepper - Americas

Cranberry - West Asia

Results

Ancestral seeds play a critical role in preserving local and traditional agricultural varieties and

maintaining sustainable agricultural practices. Through natural selection over generations,

these seeds have adapted to environmental conditions, acquired disease resistance and

become compatible with local ecosystems. The use of ancestral seeds preserves genetic

diversity and provides alternative solutions to the threats faced by modern agriculture, such as

pests and diseases caused by uniform agriculture. In addition, crops produced with ancestral

seeds are often more nutritious and flavorful. As part of cultural heritage, they also support the

agricultural independence of local communities and contribute to a healthy food system for

future generations. In this part of the study, ancestral seeds will be discussed one by one and

detailed information about each product will be given.

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Strategies On Accelerating Sustainable Development Goals (SDG)

Management through AI Integration

Dimitrios A. Karras

National and Kapodistrian University of Athens (NKUA), Greece, and EPOKA University,

Albania, Orcid No. 0000-0002-2759-8482

Abstract:

The integration of artificial intelligence (AI) into the management of Sustainable Development

Goals (SDGs) presents a transformative opportunity to address pressing global challenges.

This paper explores the multifaceted applicability of AI in advancing the 17 SDGs, highlighting

its potential to enhance efficiency, drive innovation, and foster inclusive growth across various

sectors. Through a comprehensive review of existing literature and case studies, we identify

that AI can enable progress on 134 targets (approximately 79% of all SDG targets), while also

recognizing the risks associated with its implementation, including ethical concerns and

potential biases. We discuss specific applications of AI in critical areas such as healthcare,

agriculture, climate action, and education, illustrating how AI technologies can facilitate data-

driven decision-making and resource optimization. More precisely, it is herein attempted, how

AI can be applied to SDG targets and goals as well as a general flowchart of its applications.

More emphasis is paid to AI and SDG goals and targets relevance Additionally, we introduce

an emphasis about the necessity for robust regulatory frameworks and collaborative efforts

among stakeholders to ensure that AI deployment aligns with sustainable practices and

equitable outcomes. Ultimately, this paper aims to provide some insights into harnessing AI as

a catalyst for achieving the SDGs while addressing the challenges that accompany its rapid

advancement.

Introduction

The 2030 Agenda for Sustainable Development, with its 17 SDGs, provides a comprehensive

framework for global progress towards a more equitable and sustainable future. However,

achieving these goals requires overcoming significant challenges, including scarcity of

resources, complex interdependencies, and the need for accurate data and robust decision-

making processes. AI, with its ability to analyze vast datasets, identify patterns, and generate

insights, offers a powerful tool for addressing these challenges and accelerating progress

towards the SDGs. [1-7]. This paper attempts to present systematically, but at a preliminary

stage, the major issues about AI and SDG goals.

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AI Applicability Analytics for SDG Management

AI can be applied across various stages of SDG management, including data collection,

analysis, monitoring, and evaluation. Table 1 illustrates the key areas where AI can contribute

to SDG implementation. [1-7]

Table 1: Potential AI integration with SDG Management

SDG Goal Target AI Application Impact

No Poverty (SDG 1) 1.1 Poverty Mapping

Identifies poverty

hotspots using

satellite imagery

1.2 Financial Inclusion

Platforms

Provides access to

banking services for

underserved

populations

1.3 Social Protection

Optimization

Ensures social

protection programs

reach the most

vulnerable

1.4 Data Analysis for

Basic Services

Improves access to

basic services and

property rights

Zero Hunger (SDG

2) 2.1 Food Distribution

Optimization

Reduces waste and

ensures food reaches

those in need

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SDG Goal Target AI Application Impact

2.2 Nutritional Program

Monitoring

Improves

effectiveness of

nutritional programs

2.3 Precision Agriculture

Increases crop yields

and improves food

security

2.4 Sustainable

Agricultural Practices

Predicts weather

patterns and pest

outbreaks

Good Health and

Well-being (SDG 3) 3.1 Early Diagnosis and

Treatment

Reduces maternal

mortality

3.2 Child Health

Improvement

Enhances vaccination

tracking and disease

prevention

3.3 Disease Prediction

and Control

Tracks and predicts

outbreaks of infectious

diseases

3.4 Mental Health

Support

Provides personalized

care and early

intervention

Quality Education

(SDG 4) 4.1 Personalized

Learning Platforms

Improves educational

outcomes

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SDG Goal Target AI Application Impact

4.2 Early Childhood

Education Tools

Enhances interactive

learning

4.3 Access to Technical

Education

Provides quality

technical and

vocational education

4.4

Employment and

Entrepreneurship

Skills

Develops skills

through tailored

training programs

Gender Equality

(SDG 5) 5.1 Gender Disparity

Analysis

Identifies and

addresses gender

disparities

5.2 Combating Gender-

based Violence

Analyzes social media

to identify and combat

violence

5.3 Ending Harmful

Practices

Supports initiatives to

end child marriage

and FGM

5.5 Promoting Women’s

Leadership

Supports initiatives for

women’s participation

in leadership

Clean Water and

Sanitation (SDG 6) 6.1 Water Distribution

Optimization

Ensures access to

clean water

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SDG Goal Target AI Application Impact

6.2 Sanitation

Management

Improves predictive

maintenance of

sanitation facilities

6.3 Water Quality

Monitoring

Detects pollutants and

ensures safe water

6.4 Water-use Efficiency

Enhances efficiency in

agriculture and

industry

Affordable and

Clean Energy (SDG

7)

7.1 Energy Grid

Optimization

Provides reliable and

affordable energy

7.2 Renewable Energy

Efficiency

Enhances efficiency of

renewable energy

sources

7.3 Energy Efficiency

Improvements

Improves efficiency in

buildings and

industries

7.a Energy Technology

R&D

Supports research

and development in

energy technologies

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SDG Goal Target AI Application Impact

Decent Work and

Economic Growth

(SDG 8)

8.1 Economic Growth

through Innovation

Drives economic

growth

8.2 Industrial

Productivity

Drives innovation and

productivity

8.3 Supporting

Entrepreneurship

Provides access to

market data and

trends

8.5 Job Matching

Matches job seekers

with employment

opportunities

Industry, Innovation,

and Infrastructure

(SDG 9)

9.1 Infrastructure

Development

Optimizes

development and

maintenance

9.2 Sustainable

Industrialization

Supports efficient

resource use

9.3 Financial Services

Access

Improves access for

SMEs

9.5 R&D Support

Drives innovation

through research and

development

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SDG Goal Target AI Application Impact

Reduced Inequality

(SDG 10) 10.1 Addressing Income

Inequalities

Analyzes economic

data

10.2 Social and Economic

Inequality

Identifies and

addresses inequalities

10.3 Promoting Equal

Opportunities

Ensures equal

opportunities and

reduces discrimination

10.4 Social and Economic

Inclusion

Supports inclusive

policies

Sustainable Cities

and Communities

(SDG 11)

11.1 Urban Planning Ensures access to

affordable housing

11.2 Public Transportation

Optimization

Improves

sustainability of

transportation

systems

11.3 Participatory Urban

Planning

Supports inclusive

urban management

11.6 Urban Pollution

Management

Monitors and

manages pollution

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SDG Goal Target AI Application Impact

Responsible

Consumption and

Production (SDG

12)

12.2 Resource Efficiency Enhances efficiency in

production processes

12.3 Reducing Food

Waste

Improves supply chain

management

12.4 Hazardous Waste

Management

Monitors and

manages waste

12.5 Promoting Recycling Supports waste

reduction initiatives

Climate Action

(SDG 13) 13.1 Climate Change

Mitigation

Predicts and mitigates

impacts

13.2 Climate Policy

Integration

Supports policy and

planning

13.3 Climate Education Enhances awareness

and education

13.a Climate Finance Supports finance

initiatives

Life Below Water

(SDG 14) 14.1 Marine Pollution

Monitoring

Reduces marine

pollution

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SDG Goal Target AI Application Impact

14.2 Marine Ecosystem

Management

Supports sustainable

management

14.4 Sustainable Fishing Supports sustainable

practices

14.5 Marine Biodiversity

Protection

Protects marine

biodiversity

Life on Land (SDG

15) 15.1 Ecosystem

Monitoring

Protects terrestrial

ecosystems

15.2 Reforestation Efforts Supports reforestation

and afforestation

15.5 Combating

Deforestation

Reduces biodiversity

loss

15.9 Biodiversity

Integration

Integrates values into

planning

Peace, Justice, and

Strong Institutions

(SDG 16)

16.1 Conflict Prediction Prevents conflicts

16.3 Access to Justice

Supports legal

analytics and case

management

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SDG Goal Target AI Application Impact

16.6 Transparency and

Accountability

Promotes institutional

transparency

16.10 Human Rights

Monitoring

Analyzes human

rights abuses

Partnerships for

the Goals (SDG 17) 17.6 Global Partnerships Facilitates knowledge

sharing

17.8 Technology for

Development

Enhances technology

use

17.18 Data Collection and

Analysis

Improves decision-

making

17.19 Capacity Building Supports initiatives in

developing countries

This table provides a comprehensive overview of how AI can be applied to each SDG target,

highlighting specific applications and their impacts [1-7].

To illustrate how AI applications can enhance the Sustainable Development Goals (SDGs)

through various stages such as data collection, analysis, monitoring, and evaluation, a

flowchart can be structured. A flowchart depicting AI applications in SDG stages, including

data collection, analysis, monitoring, & evaluation, with examples like image recognition,

natural language processing, predictive modeling, etc. could be defined as follows [1-7]:

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A flowchart on how AI can be applied to meet SDG targets

1. Data Collection

 Image Recognition: Utilizes computer vision to gather data from satellite imagery for

monitoring deforestation or urban development.

 Natural Language Processing (NLP): Analyzes social media and survey responses to

assess public sentiment on health or education issues.

 IoT Sensors: Collects real-time data on environmental conditions, such as air quality

and water levels.

2. Data Analysis

 Predictive Modeling: Employs machine learning algorithms to forecast agricultural

yields or disease outbreaks based on historical data.

 Big Data Analytics: Integrates diverse datasets (e.g., demographic, economic) to

identify trends and correlations relevant to poverty alleviation or health outcomes.

 Sentiment Analysis: Uses NLP to derive insights from public opinions on policies

related to gender equality or climate action.

3. Monitoring

 Real-Time Dashboards: AI systems create dashboards that visualize key indicators for

SDG progress, enabling stakeholders to track performance dynamically.

 Anomaly Detection: Machine learning models identify irregular patterns in data, such

as sudden spikes in pollution levels or resource consumption.

 Geospatial Analysis: Combines satellite data with AI to monitor changes in land use

and biodiversity over time.

4. Evaluation

 Impact Assessment Models: AI evaluates the effectiveness of interventions by

comparing pre- and post-intervention data across various SDGs.

 Scenario Simulation: Predictive analytics simulate different policy scenarios to evaluate

potential outcomes on social, economic, and environmental targets.

 Feedback Loops: AI systems analyze feedback from stakeholders to refine programs

and policies aimed at achieving the SDGs.

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Examples of AI Techniques Across the above presented Flowchart Stages

Stage AI Technique

Application Example and relevant case studies

Data

Collection

Image

Recognition

Monitoring deforestation via satellite imagery

(A notable case study for monitoring deforestation via satellite imagery is the

Seringueira REDD+ Project in Brazil. This project utilizes satellite data from

Planet NICFI, Sentinel-1, and Sentinel-2 to effec

tively monitor forest loss at a

high spatial resolution of 4.7 meters.

Overview of the Seringueira REDD+ Project

Objective: The project aims to promote high-integrity nature-

based carbon

projects while ensuring transparency through reliable satellite monitoring.

Collaboration: Nadar, Moss, and explorer.land collaborated to provide

accurate monitoring and reporting of

deforestation and aboveground biomass

(AGB) changes in the Brazilian Amazon. https://www.nadar.earth/case-

studies/seringueira )

Data

Collection

NLP

Analyzing social media for public health sentiments (An example project is

Analyzing Social Media Messaging on Masks and

Vaccines: A Case Study on

Misinformation During the COVID-19 Pandemic [8] )

Data

Analysis

Predictive

Modeling

Forecasting crop yields based on weather patterns (An example case study is

Crop Yield Prediction Using Machine Learning Models: Case of Irish Po

tato

and Maize [9])

Data

Analysis

Big Data

Analytics

Identifying trends in economic inequality ( An example case study is Trends in

Income Inequality: Evidence from Developing and Developed Countries

[10,11])

Monitoring

Real-Time

Dashboards

Visualizing progress on SDG indicators (An example case study is the event

Visualizing Progress: Data Insights from the Atlas of Sustainable Development

Goals https://live.worldbank.org/en/event/2023/visualizing-progress-data-

insights-atlas-sustainable-development-goals )

Monitoring

Anomaly

Detection

Detecting pollution spikes in urban areas (An example case study is Air-

pollution prediction in smart city, deep learning approach [12])

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Stage AI Technique

Application Example and relevant case studies

Evaluation

Impact

Assessment

Models

Assessing the effectiveness of health interventions (An example overview of

case studies and literature is The effectiveness of interventions to change six

health behaviours: a review of reviews [13])

Evaluation

Scenario

Simulation

Evaluating potential impacts of renewable energy policies (An example case

study project is Tracking the Impacts of Innovation: Offshore wind as a case

study

This report is an initial o

utput of two projects focused on tracking innovation

impacts: the Innovation Impacts Dashboard (IID) project and the Tracking

Energy Innovation Impacts Framework (TEIIF) project.

ISBN: 978-92-9260-347-2 ,

https://www.irena.org/publications/2021/Jun/Impact-of-Innovation-Offshore-

wind-case-study )

This flowchart demonstrates the multifaceted role of AI in supporting the SDGs through

systematic data handling and analysis processes. By leveraging these technologies,

stakeholders can enhance their decision-making capabilities and improve the overall

effectiveness of initiatives aimed at achieving sustainable development.

Data Collection and Analysis.

 Remote Sensing and Image Recognition: AI-powered image recognition can analyze

satellite imagery to monitor deforestation, track agricultural practices, and assess urban

sprawl, contributing to SDG 13 (Climate Action), SDG 11 (Sustainable Cities and

Communities), and SDG 15 (Life on Land).

 Natural Language Processing (NLP): NLP can analyze large volumes of text data from

social media, news articles, and reports to identify public opinion, understand

community needs, and monitor progress on SDG indicators. This can be particularly

relevant for SDG 1 (No Poverty), SDG 3 (Good Health and Well-being), and SDG 16

(Peace, Justice, and Strong Institutions).

 Sensor Data and IoT: AI can process data from IoT devices deployed in various

environments to monitor air and water quality, energy consumption, and traffic patterns,

providing insights for SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and

Clean Energy), and SDG 11 (Sustainable Cities and Communities).

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Monitoring and Evaluation.

 Predictive Modeling: AI can leverage historical data and current trends to forecast

future outcomes related to SDG indicators, allowing for proactive interventions and

resource allocation. For instance, predicting food insecurity (SDG 2: Zero Hunger) or

water scarcity (SDG 6: Clean Water and Sanitation) can empower early action.

 Anomaly Detection: AI algorithms can identify unusual patterns and deviations from

expected trends in various datasets, flagging potential risks and enabling swift

responses. This is crucial for monitoring SDG 10 (Reduced Inequalities) and SDG 17

(Partnerships for the Goals).

 Impact Assessment: AI can help assess the impact of interventions and policies on

different SDG targets, facilitating evidence-based decision-making and optimizing

resource utilization. This can be relevant across all SDGs.

Examples of AI Application in SDG Management

The following Table 2 presents a sample of examples of AI applicability and correlation with

SDG targets

Table 2: AI Applications for Specific SDGs

SDG AI Application Example Expected Impact

SDG 1: No

Poverty

Predictive

Modeling

Forecasting poverty rates

based on socioeconomic

data and historical trends

Targeted interventions for poverty

alleviation

SDG 7: Affordable

and Clean Energy

Optimization

Algorithms

Optimizing energy grid

management for

renewable energy

integration

Reduced energy costs and carbon

emissions

SDG 13: Climate

Action

Climate

Modeling

Developing predictive

models for climate change

impacts

Better preparedness for extreme

weather events and mitigation

strategies

SDG 11:

Sustainable Cities

and Communities

Smart City

Infrastructure

Utilizing AI for traffic

management, waste

collection, and resource

optimization

Improved urban planning and

reduced environmental footprint

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AI applicability for SDG targets

AI has the potential to significantly contribute to achieving 134 of the 169 Sustainable

Development Goals (SDG) targets, which is approximately 79% of all targets [1-7]. Below is a

detailed overview of how AI can enable progress on each of these targets:

1. No Poverty (SDG 1)

 Target 1.1: AI can help identify and target poverty hotspots using satellite imagery and

data analytics.

 Target 1.2: AI-driven financial inclusion platforms can provide access to banking and

financial services for underserved populations.

 Target 1.3: AI can optimize social protection programs to ensure they reach the most

vulnerable.

 Target 1.4: AI can analyze data to improve access to basic services and property rights.

2. Zero Hunger (SDG 2)

 Target 2.1: AI can optimize food distribution networks to reduce waste and ensure food

reaches those in need.

 Target 2.2: AI can help monitor and improve nutritional programs.

 Target 2.3: AI-powered precision agriculture can increase crop yields and improve food

security.

 Target 2.4: AI can support sustainable agricultural practices by predicting weather

patterns and pest outbreaks.

3. Good Health and Well-being (SDG 3)

 Target 3.1: AI can assist in early diagnosis and treatment of diseases, reducing

maternal mortality.

 Target 3.2: AI can improve child health through better vaccination tracking and disease

prevention.

 Target 3.3: AI can help track and predict outbreaks of infectious diseases, aiding in

their control and prevention.

 Target 3.4: AI can support mental health initiatives by providing personalized care and

early intervention.

4. Quality Education (SDG 4)

 Target 4.1: AI-driven personalized learning platforms can improve educational

outcomes for students.

 Target 4.2: AI can enhance early childhood education through interactive learning tools.

 Target 4.3: AI can provide access to quality technical and vocational education.

 Target 4.4: AI can help develop skills for employment and entrepreneurship through

tailored training programs.

5. Gender Equality (SDG 5)

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 Target 5.1: AI can analyze data to identify and address gender disparities.

 Target 5.2: AI can analyze social media and other data to identify and combat gender-

based violence.

 Target 5.3: AI can support initiatives to end harmful practices such as child marriage

and female genital mutilation.

 Target 5.5: AI can support initiatives that promote women’s participation in leadership

and decision-making roles.

6. Clean Water and Sanitation (SDG 6)

 Target 6.1: AI can optimize water distribution systems to ensure access to clean water.

 Target 6.2: AI can improve sanitation management through predictive maintenance of

facilities.

 Target 6.3: AI can monitor water quality and detect pollutants, ensuring safe water for

all.

 Target 6.4: AI can enhance water-use efficiency in agriculture and industry.

7. Affordable and Clean Energy (SDG 7)

 Target 7.1: AI can optimize energy grids to provide reliable and affordable energy.

 Target 7.2: AI can enhance the efficiency of renewable energy sources, promoting

clean energy.

 Target 7.3: AI can improve energy efficiency in buildings and industries.

 Target 7.a: AI can support research and development in energy technologies.

8. Decent Work and Economic Growth (SDG 8)

 Target 8.1: AI can drive economic growth through innovation and productivity

improvements.

 Target 8.2: AI can drive innovation and productivity in various industries, fostering

economic growth.

 Target 8.3: AI can support entrepreneurship and small businesses through access to

market data and trends.

 Target 8.5: AI can help match job seekers with employment opportunities, promoting

full and productive employment.

9. Industry, Innovation, and Infrastructure (SDG 9)

 Target 9.1: AI can optimize infrastructure development and maintenance.

 Target 9.2: AI can support sustainable industrialization through efficient resource use.

 Target 9.3: AI can improve access to financial services for small and medium-sized

enterprises.

 Target 9.5: AI can support research and development, driving innovation.

10. Reduced Inequality (SDG 10)

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 Target 10.1: AI can analyze economic data to identify and address income

inequalities.

 Target 10.2: AI can identify and address social and economic inequalities.

 Target 10.3: AI can help ensure equal opportunities and reduce discriminatory

practices.

 Target 10.4: AI can support policies that promote social and economic inclusion.

11. Sustainable Cities and Communities (SDG 11)

 Target 11.1: AI can improve urban planning to ensure access to affordable housing.

 Target 11.2: AI can optimize public transportation systems, making cities more

sustainable.

 Target 11.3: AI can support participatory urban planning and management.

 Target 11.6: AI can monitor and manage urban pollution, improving air quality.

12. Responsible Consumption and Production (SDG 12)

 Target 12.2: AI can enhance resource efficiency in production processes.

 Target 12.3: AI can reduce food waste through better supply chain management.

 Target 12.4: AI can monitor and manage hazardous waste.

 Target 12.5: AI can promote recycling and waste reduction initiatives.

13. Climate Action (SDG 13)

 Target 13.1: AI can predict and mitigate the impacts of climate change.

 Target 13.2: AI can support the integration of climate change measures into policies

and planning.

 Target 13.3: AI can enhance climate education and awareness.

 Target 13.a: AI can support climate finance initiatives.

14. Life Below Water (SDG 14)

 Target 14.1: AI can monitor and reduce marine pollution.

 Target 14.2: AI can support the sustainable management of marine and coastal

ecosystems.

 Target 14.4: AI can support sustainable fishing practices.

 Target 14.5: AI can help protect marine biodiversity.

15. Life on Land (SDG 15)

 Target 15.1: AI can monitor and protect terrestrial ecosystems.

 Target 15.2: AI can support reforestation and afforestation efforts.

 Target 15.5: AI can help combat deforestation and biodiversity loss.

 Target 15.9: AI can integrate ecosystem and biodiversity values into planning and

development processes.

16. Peace, Justice, and Strong Institutions (SDG 16)

 Target 16.1: AI can help predict and prevent conflicts.

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 Target 16.3: AI can support access to justice through legal analytics and case

management systems.

 Target 16.6: AI can promote transparency and accountability in institutions.

 Target 16.10: AI can protect fundamental freedoms by monitoring and analyzing human

rights abuses.

17. Partnerships for the Goals (SDG 17)

 Target 17.6: AI can facilitate global partnerships and knowledge sharing.

 Target 17.8: AI can enhance the use of technology for development.

 Target 17.18: AI can improve data collection and analysis for better decision-making.

 Target 17.19: AI can support capacity-building initiatives in developing countries.

These examples illustrate the diverse ways AI can contribute to achieving the SDG

targets. The potential applications are vast and varied, offering innovative solutions to some of

the world’s most pressing challenges (https://www.nature.com/articles/s41467-019-14108-

y.pdf?pdf=button%20sticky ).

Challenges and Considerations

While AI presents immense potential for SDG management, its implementation faces several

challenges:

 Data Availability and Quality: Reliable and accessible data are crucial for AI algorithms

to function effectively. Many developing countries struggle with data scarcity and quality

issues.

 Algorithmic Bias and Fairness: AI models can inherit biases present in the data they

are trained on, potentially leading to unfair or discriminatory outcomes. This needs

careful consideration, especially when dealing with sensitive issues like poverty or

healthcare.

 Ethical Implications: Concerns related to data privacy, transparency, and accountability

must be addressed when deploying AI for SDG management.

 Capacity Building: Developing local expertise and capacity to implement and maintain

AI solutions is crucial for long-term sustainability.

Future Directions

The future of AI in SDG management lies in enhancing its capabilities and addressing the

identified challenges.

 Developing Robust Data Infrastructure: Investing in data collection, storage, and

management systems is vital for ensuring high-quality data for AI applications.

 Promoting Ethical AI Development: Establishing clear guidelines and standards for

ethical AI development and deployment is crucial to mitigate potential biases and risks.

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 Fostering Collaboration and Knowledge Sharing: Encouraging collaboration between

researchers, policymakers, and practitioners will facilitate knowledge sharing and

accelerate the development of effective AI solutions for SDGs.

Conclusions and future prospects of this study

AI holds immense potential to revolutionize SDG management by enabling data-driven

decision-making, improving monitoring and evaluation processes, and driving innovation for

achieving a sustainable future. By addressing the associated challenges and fostering

responsible AI development, we can leverage this transformative technology to accelerate

progress towards the SDGs and build a more equitable and sustainable world for all. This study

has paid attention and effort at preliminary stage, however, to comprehensively outline the

major issues of the applicability of AI towards reaching the SDG goals and targets. The author,

however, will present a more detailed analysis in the near future.

References:

Bekkar, A., Hssina, B., Douzi, S. et al. (2021). Air-pollution prediction in smart city, deep

learning approach. J Big Data 8, 161 (2021). https://doi.org/10.1186/s40537-021-

00548-1

Francisco, M., & Linnér, B. O. (2023). AI and the governance of sustainable development. An

idea analysis of the European Union, the United Nations, and the World Economic

Forum. Environmental Science & Policy, 150, 103590.

Iazzolino, G., & Stremlau, N. (2024). AI for social good and the corporate capture of global

development. Information Technology for Development, 1–18.

https://doi.org/10.1080/02681102.2023.2299351

Jepson, R.G., Harris, F.M., Platt, S. et al. (2010). The effectiveness of interventions to change

six health behaviours: a review of reviews. BMC Public Health 10, 538 (2010).

https://doi.org/10.1186/1471-2458-10-538

Kuradusenge, M.; Hitimana, E.; Hanyurwimfura, D.; Rukundo, P.; Mtonga, K.; Mukasine, A.;

Uwitonze, C.; Ngabonziza, J.; Uwamahoro, A. (2023). A. Crop Yield Prediction Using

Machine Learning Models: Case of Irish Potato and Maize. Agriculture 2023, 13, 225.

https://doi.org/10.3390/agriculture13010225

Makhlouf, Y. (2023). Trends in Income Inequality: Evidence from Developing and Developed

Countries. Soc Indic Res 165, 213–243 (2023). https://doi.org/10.1007/s11205-022-

03010-8

Brod Siqueira, M. et al. (2024). Artificial Intelligence for Sustainability: A Systematic Literature

Review in Information Systems, DOI: https://doi.org/10.24857/rgsa.v18n3-178,

https://rgsa.openaccesspublications.org/rgsa/article/view/7885

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Nasir, O.; Tallal Javed, R.; Gupta, S.; Vinuesa, R. & Qadir, J. (2023). Artificial intelligence and

sustainable development goals nexus via four vantage points, Technology in Society,

Volume 72, 2023, 102171, ISSN 0160-791X,

https://doi.org/10.1016/j.techsoc.2022.102171.

Singh, A., Kanaujia, A., Singh, V. K., & Vinuesa, R. (2024). Artificial intelligence for Sustainable

Development Goals: Bibliometric patterns and concept evolution trajectories.

Sustainable Development, 32(1), 724-754..

Tomašev, N., Cornebise, J., Hutter, F. et al. (2020). AI for social good: unlocking the

opportunity for positive impact. Nat Commun 11, 2468 (2020).

https://doi.org/10.1038/s41467-020-15871-z

Trotochaud M, Smith E, Hosangadi D, Sell TK. (2023). Analyzing Social Media Messaging on

Masks and Vaccines: A Case Study on Misinformation During the COVID-19

Pandemic. Disaster Medicine and Public Health Preparedness. Published online

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, https://doi.org/10.1007/s13398-014-0173-7.2

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Education and E-Learning

Meta Discourse ands Appraisal Analysis of Media Perspective on Thai

Government` Performance towards Thai Education

Sirikarn Thongmak

Srinakharinwirot University, Thailand

Abstract

This study aims to examine the distribution of Syntactic Patterns and Pragmatic Functions

based on the Interactional Metadiscoursal and Appraisal theory through the journalistic views

of the Thai and Native English Journalists. The data was drawn to reveal the distribution of

Syntactic Patterns and Pragmatic Functions from the opinion section of the popular English

newspaper on the Thai Government’s Performance in 10 English written Thai Journalists and

10 English native Journalists, making 20 pieces. The similarities and different between sub-

types of judgment resources were additionally explored to display the writers’ judgment as

evaluative assessments through the lens of media discourse. Both quantitative and qualitative

methods were carried out in this study to display the in-depth findings. Regarding the

judgments- polarity and attitudinal markers based the statistical results of this study, it revealed

that there are different Syntactic Patterns and Pragmatic Functions employed by different

writing norms and conventions as well as their communicative language communities. Thus,

the attitudinal judgment based on Interactional Metadiscoursal and Appraisal markers are

strongly voiced through the lens of journalists in the media discourse interactions.

Keywords: Metadiscourse, Appraisal, Media Perspective, Thai Government's Performance

Introduction

From the public great concern on the current reformation of Thai education, it is clear that the

journalistic views provided in the opinion section play a crucial role in judging and

disseminating their arguments against the government’s poor management publicly. Based on

media discourse, the journalistic views are regarded as a fair response to the facts of the public

act. Their opinion of the graving situation is presented to the readers in conveying the content

having certain discoursal implicitness which is worth carrying out the multifaceted appraisal

analysis. The appraisal developed by White and Martin (2003) convinces the writers’ language

use in explaining writers' attitudinal judgement, emotional differentiation; and individual

differences in attitudinal response; and the appropriateness of how to create reactions to the

situations. In a nutshell, the appraisal represents a discourse semantic function which can

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help the writers to make use of stances and construe their interpersonal meaning expressed

in the target texts.

With regard to the studies in Appraisal Theory, a lot of research are conducted in various

discourses, such as literature, academic written texts and media speeches (e.g. Asher, et al.,

2009; Bednarek, 2006; Caro, 2014; Gales, 2011; Putri, 2020). These researches greatly

explored evaluative meanings of attitudinal languages in a particular context. Nonetheless,

there are still scant studies of appraisal analysis conducted on the criticism of the Thai

government’ performance in Thai research context. With the significance of the selection of

linguistic use within a particular text type, the critical analysis with linguistic features is worth

exploring to understand online media perspectives. In this sense, we can see how the opinion

section reflects its journalistic perspective towards the governments’ political management of

such severer situations in terms of language analysis.

This study is therefore an attempt to explore how the media discourse based on appraisal

theory is conducted through on the journalistic views towards the Thai government’s

performance to the current reformation of Thai education. The data drawn was selected from

the opinion section of the popular English newspaper in Thailand (Bangkok Post). The aim is

to grasp the nature of linguistic perspectives and analyze how opinion section utilizes the

attitudinal language to display the writers’ judgment as evaluative assessments through the

lens of media discourse with the following research question:

RQ 1. What are the salient appraisal features identified in each judgment category found in

the opinion section?

RQ 2. How do the appraisal features found display perspectives of media towards Thai

government in dealing the current reformation of Thai education?

Method and Theoretical Framework

This study gives a great contribution in analyzing the target texts through the application of

appraisal framework. This is because, the appraisal theory is considered the most appropriate

framework in assisting the researcher to uncover and assess how the journalists evaluated the

governments’ performance and how they express the kinds of attitudes and how they project

the strength of the feelings involved in the opinion sections of the News.

Within the appraisal system, the judgement category was specifically applied to the analysis

of a sample of opinion sections of this study listed in the following framework (Martin & White,

2003; White, 2015).

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Based on the framework, judgement can be divided into two main categories including social

esteem referring to praising a person, in contrast, social sanction indicating to condemning a

person. The judgement types are always used to study how the speaker or author expresses

his subjective attitude in words in relation to the contextualized extension (Martin & White,

2003).

Data Collection and Preparation

The corpus data in this study were compiled from the online version of Bangkok Post of the

current reformation of Thai education issue, during January 2024 – July 2024. The online news

were selected due to the research methodological benefits and for reaching a wider and keener

audience than in any other modes of media. The online version of Bangkok Post was

specifically selected since it is the English-language oldest and longest daily newspaper

published in Thailand. The online version of Bangkok Post can be used as the reliable

representative of media discourse which portrays the critical interactions of journalists that

display through a broadcast platform.

The corpus consist of 20 Editorial sections of the criticism Thai government manipulation by

different authors. They were transcribed in Microsoft Word. Initial goal of corpus size contains

15,336 words. In addition, full texts are generally preferable because important information can

be found anywhere in a text. Since this study was conducted with small-scale corpus, the

Judgement Description Examples

Normality and

Abnormality

How unusual of the

appraised in positive

aspects

Nor: lucky, normal, cool, fortunate

Abnor: unlucky, peculiar, obscure,

unpredictable

Capacity and

Incapacity

The appraise’ s ability and

limitation

Cap: powerful, healthy, clever, fit, adult,

balanced

Incap: slow, stupid, thick, sick, weak,

unsuccessful

Tenacity and

Untenacity

The appraiser’s bravery,

patience and dependability

Ten: brave, cautious, careful

Unten: impatient, cowardly, rash,

inconstant

Veracity and

Inveracity

The appraiser’s honesty

and good manner of

speaking

Ver: honest, credible, frank

Inveracity: dishonest, deceitful, blunt

Propriety and

Impropriety

The appraiser’s good

manner and morality

Prop: good, moral, fair, ethical

Improp: bad, unfair, vain, immoral

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representativeness of the findings will be extracted with the saturation, particularly when

investigating high frequency items in order to answer the research questions (McEnery, et al,

2006). Therefore, the lexical features of judgement types and distinctive lexical items will be

focused in the target context of this study.

References

Asher, N., Benamara, F., & Mathieu, Y. Y. (2009). Appraisal of opinion expressions in

discourse. Lingvisticæ Investigationes, 32(2), 279-292.

Bednarek, M. (2006). Evaluation in media discourse: Analysis of a newspaper corpus. A&C

Black.

Bednarek, M. (2009). Language patterns and attitude. Functions of Language, 16(2), 165-192.

Caro, E. M. (2014). The expression of evaluation in weekly news magazines in English. In G.

Thomson & L. Alba-Juez (Eds.), Evaluation in context (Vol. 242, pp. 321-344). John

Benjamins Publishing Company.

Gales, T. (2011). Identifying interpersonal stance in threatening discourse: An appraisal

analysis. Discourse Studies, 13(1), 27-46.

Macken-Horarik, M., & Isaac, A. (2014). Appraising appraisal. In G. Thomson & L. Alba-Juez

(Eds.), Evaluation in context (Vol. 242, pp. 67-92). John Benjamins Publishing

Company.

Martin, J. R., & White, P. R. (2003). The language of evaluation (Vol. 2). Palgrave Macmillan.

Martin, J. R., & White, P. R. R. (2005). The language of evaluation: Appraisal in

English.Palgrave Macmillan.

McEnery, T., Xiao, R., & Tono, Y. (2006). Corpus-based language studies: An advanced

resource book. Routledge.

O‘Keeffe, A. (2011) Media and discourse analysis. In J. Gee, & M. Handford (Eds.) The

Routledge handbook of discourse analysis (pp. 441-454). Routledge.

Pekarova, R. (2011). Evaluative language in journalistic discourse. (Unpublished master’s

thesis). Masaryk University.

Putri, D. M. (2020). Evaluation on language attitude of presidential candidates in the discourse

of Debat Capres 2019: Appraisal analysis. Language Literacy: Journal of Linguistics,

Literature, and Language Teaching, 4(1), 139-144.

Sinclair, J. (1991. Corpus, concordance, collocation. Oxford University.

Thompson, G., & Zhou, J. (2003). Evaluation and organization in text: The structuring role of

evaluative disjuncts. In S. Hunston, & G. Thompson (Eds.), Evaluation in text: Authorial

stance and the construction of discourse (pp. 121-141). Oxford University.

White, P. R. R. (2015). Appraisal theory. In K. Tracy (Ed.), The international encyclopedia of

language and social interaction. (Vol.1, pp. 1-7). Wiley Blackwell.

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How Can We Advance Cognitive Skills for Sustainable Careers?

Integrating the Inner Development Goals (IDG) Framework

into Business School Classrooms

Yuliya Shtaltovna

International Business School, HS Fresenius, Berlin, Germany, and

Higher Education Circle, Inner Development Goals and UA_IDG_Network, Ukraine,

Orcid No: 0000-0003-2976-0305

Abstract

This theoretical manuscript aims to explore the role that dimension two, ‘Thinking-Cognitive

Skills’ of the Inner Development Goals (IDG) framework, can play in empowering sustainable

careers and sustainable development. We begin by setting the scene before introducing the

theoretical framework, which combines the IDG framework and Sustainable Career

Ecosystems Theory (SCET). Our attention then turns to systematically considering each of the

components of dimension two of the IDG framework. These include (a)critical thinking, (b)

complexity awareness, (c) perspective skills, (d) sense-making, and (e) long-term orientation

and visioning. The theoretical contribution comes from integrating the IDG framework and

SCET. Practical implications come from offering eight pragmatic recommendations to

empower students in the context of higher education to prepare for sustainable careers and

sustainable development: (i) curriculum design, (ii) interdisciplinary approach, (iii) experiential

learning, (iv) faculty development, (v) assessment and evaluation, (vi) campus culture, (vii)

collaboration and external partners, and (viii) research and innovation. Limitations and a future

research agenda are also provided.

Keywords: cognitive skills, Inner Development Goals (IDG), higher education, sustainable

careers, employability, strategic thinking.

Introduction

In a world driven by rapid change, cognitive skills are increasingly seen as vital for career

sustainability. They are integral to navigating the complexities of modern workplaces, as

highlighted by the New Psychological Contract (NPC), which emphasizes agility and

employability (Baruch & Rousseau, 2019; Donald, 2023). These skills are central to the Inner

Development Goals (IDG) framework, which is linked to the United Nations Sustainable

Development Goals (SDGs), particularly SDG4, focusing on quality education and lifelong

learning opportunities (United Nations, 2015).

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Theoretical Framework: IDG and SCET

The IDG framework works in conjunction with the Sustainable Career Ecosystems Theory

(SCET). While SCET emphasizes agility in career development, IDGs focus on inner qualities

such as thinking and cognitive skills. Together, these frameworks form a comprehensive

approach to preparing students for sustainable careers, particularly through higher education,

where skills like critical thinking, perspective-taking, and sense-making are taught and honed

(Donald et al., 2023; Jakubik, 2020; Shtaltovna & Muzzu, 2021a).

Dimension Two of the IDG Framework: Thinking-Cognitive Skills

The IDG framework comprises five dimensions, and this article specifically focuses on

Dimension Two: ‘Thinking-Cognitive Skills’. These include:

1. Critical Thinking: The ability to analyze information and make reasoned judgments

(Sala et al., 2020; King & Kitchener, 1994; Kahneman, 2011).

2. Complexity Awareness: Understanding and navigating complex systems and their

interdependencies (Ackoff, 1979; Juarrero, 1999; Juarrero, 2023; Meadows, 2008,

Snowden, 2009).

3. Perspective Skills: Appreciating diverse viewpoints and integrating different

perspectives (Dawson, 2020; Vygotsky, 1978).

4. Sense-Making: Structuring and interpreting experiences to guide understanding and

action (Weick, 2005; Urquhart & Snowden, 2024; Hübl, 2023).

5. Long-Term Orientation and Visioning: Envisioning the future and formulating

sustainable plans (Bennett & Lemoine, 2014; Sylvester & Donald, 2023).

Each of these components is crucial for fostering sustainable career practices in students,

enabling them to navigate the increasingly complex world of work effectively.

Integrating IDG Cognitive Skills in Higher Education

To equip students with these skills, higher education institutions, especially business schools,

can implement the following strategies:

Curriculum Design

Developing courses and learning modules centered on IDG principles, with a focus on

cognitive, emotional, social, and embodiment skills, can expose students to sustainable

development concepts early on (Jakubik et al., 2023). IDG-based curriculum design ensures

that students engage with sustainability and cognitive skill development throughout their

education.

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Interdisciplinary Approach

An interdisciplinary approach helps to contextualize cognitive skills across various fields of

study. For example, integrating IDGs in STEM education can enhance problem-solving and

critical thinking capabilities, preparing students for diverse professional environments (Līce et

al., 2023).

Experiential Learning

Promoting hands-on learning opportunities through project-based learning, internships, and

service-learning projects enables students to apply IDG principles in real-world contexts

(Donald & Mouratidou, 2022). This practical experience is crucial for developing a deep

understanding of how to navigate complexities and make sustainable decisions.

Faculty Development

Training educators on IDG principles is essential to ensure that they can effectively integrate

these concepts into their teaching. Providing resources and opportunities for continuous

professional development enables faculty to incorporate cognitive skills and sustainability into

their pedagogy (Shtaltovna & Muzzu, 2021b).

Assessment and Evaluation

Innovative methods for assessing student development in IDG-related competencies are

needed. Reflective assignments, journaling, collaborative projects, and personal development

plans offer ways to evaluate how well students are developing cognitive skills aligned with

sustainability (Shtaltovna, 2021).

Campus Culture

Creating a campus culture that values inner development fosters an environment where both

students and staff are encouraged to explore personal growth and sustainability (Wamsler &

Restoy, 2020). Emphasizing community engagement and promoting dialogue around

sustainability themes can cultivate a culture of inclusivity and shared purpose.

Collaboration with External Partners

Collaborations with businesses, non-profits, and other educational institutions provide

opportunities to extend the application of IDG principles beyond the classroom. Partnering with

external stakeholders can enhance the learning experience and provide practical insights into

sustainable career practices (Van der Heijden & De Vos, 2015).

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Research and Innovation

Encouraging research into inner development and its application in education and sustainable

careers supports the continuous evolution of IDG integration (Stålne & Greca, 2022). This

research can explore how cognitive skills contribute to sustainable career practices and drive

innovation in both academia and industry.

Conclusion

Integrating the IDG framework into business school education offers a powerful tool for

fostering cognitive skills essential for sustainable careers. The alignment of IDGs with SCET

and the broader context of sustainable development prepares students to become agile,

resilient, and ethically minded professionals capable of navigating the complexities of the

modern workforce. By embedding these cognitive skills into higher education, we empower

students to contribute meaningfully to sustainable development and build careers that are not

only successful but also responsible and forward-looking.

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Baruch, Y., & Rousseau, D. M. (2019). Sustainable careers and the psychological contract:

New horizons for career research and practice

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Dawson, T. L. (2020-2021). VUCA Unpacked. Medium Article

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Monitoring and Evaluation of Online Volunteer Tutorial for Alternative

Education Students

Christian Philippine Momongan

1)

, Vicente Obejero Jr.

1)

, George Cadano

2)

,

Angelika Fae Amado

2)

, Mileni Torres

2)

, Janice Diola

1)

and Aurelio Vilbar

1)

1) University of the Philippines Cebu, Philipppines

2) La Salle Green Hills University, Philippines

Introduction

Addressing the literacy issues of out-of-school persons in the country, the Philippine Republic

Act (RA) 9155 mandated the establishment of an Alternative Learning System (ALS) to provide

basic education to out-of-school children, youth, and adults. According to RA 9155, ALS is a

parallel learning system providing a viable alternative to formal education. It aims to deliver

quality education to the underserved Filipinos.

In this research, La Salle Greenhills-Alternative Education (LSGH), a Catholic private school

in Metro Manila, offers an ALS Program to overaged and working students to finish their Junior

High School Education (Grade 10). These 15 ALS students range from 18-32 years old. As

an academic partner of LSGH, the University of the Philippines Cebu Ugnayan ng Pahinungod

(Volunteerism) provided online volunteer tutors to coach the ALS students in writing academic

essays. Essay writing is one of the major components of the ALS Accreditation and

Equivalency (A&E) Assessment. According to the Needs Assessment, the ALS students

displayed satisfactory English oral communication performance but needed assistance in

writing academic essays acceptable for the ALS Assessment. LSGH requested that the UP

Cebu Pahinungod online volunteers guide the ALS students in writing effective essays. The

volunteers were UP Cebu faculty, students, staff, and Friends of UP Cebu Pahinungod. For

this online volunteerism, they used the internet and digital tools such as Google Meet for online

tutorial sessions, Google Classroom for the learning management system, and Facebook

Messenger for instant messaging. Although online volunteerism became an alternative to

face-to-face volunteerism during the pandemic (Vilbar, 2023), it has been widely used and

accepted beyond the pandemic era due to convenience and flexibility (Sun et al., 2023;

Lachance, 2021).

As supplementary support, tutorials can enhance student learning through real-time

interactions (Doukakis, 2021). They can develop language skills by providing flexibility,

interactivity, motivation, immediate feedback, and reflective learning compared to large face-

to-face classes (Linardopoulos, 2010; Kamardeen, 2014; and Rodrigues and Vethamani,

2015). With the nature of the ALS students having part-time jobs, online tutorials have become

the preferred method. According to Richardson (2016) and Said, A., & Syarif, E. (2016),

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students would choose online rather than in-person classes due to convenience, flexibility,

and maximizing optimal learning time.

Despite their convenience and flexibility, online tutorials can promote digital divide based on

geographical barriers and socioeconomic status (Corrigan, 2012; Lythreatis et al., 2022).

Tutors and tutees experience difficulties in accessing online lessons due to technical issues,

lack of social contextual cues, unreliable internet, high internet cost, and lack of ICT tools (Hara

& Kling, 2000; Alvarez, 2020; Mathew & Iloanya, 2016; Lynch, 2020). Furthermore, the online

tutorial environment promotes a climate of loneliness, less personal rapport, and anxiety when

not properly planned (Lythreatis et al., 2022; Kaufmann & Vallade, 2022). These issues

inspired the UP Cebu Pahinungod Office to dedicate two staff to monitor the online tutorials.

This collaborative research aimed to determine the monitoring and evaluation strategies of the

UP Cebu Pahinungod Office in sustaining the tutorial sessions. It sought the following

questions: (1) How did the office provide online support to the volunteers during the tutorial?

(2) To what extent did the support help the tutors and tutees? (3) What is the impact of

volunteerism on the tutees’ writing skills and motivation to continue schooling?

Methodology

This study utilized the following qualitative data-gathering procedures to assess the impact:

semi-structured interviews, focus-group discussions, and analysis of the recorded tutorial

sessions. It used the Elements of Volunteer Management from the Volunteer Onslow:

Planning, Connecting with Volunteers, Managing/Retaining Volunteers, and Evaluating. In the

planning stage, LSGH and UPC Pahinungod planned the online tutorial program’s learning

management system, tutorial schedule, writing content focus, and online class attendance

mechanism. This research strengthened the attendance mechanism to handle potential

nonattendance. According to the ALS studies in the Philippines, attendance and dropout

cases became the major issue in implementing ALS programs (Alvarez Jr., 2024; Castillo,

2021; Flores, 2022). Furthermore, according to the LSGH, the majority of the students have

odd and part-time jobs while enrolling in the program which consequently affected their

attendance. The tutorials were scheduled every Monday in the evenings for two months to

support the ALS students’ work.

This research used the online modality due geographical location between the ALS students

and the UP Cebu Pahinungod volunteer tutors. LSGH is located in Metro Manila which is in

the northern Philippines while UP Cebu is located in central Philippines. The 19 volunteers

were undergraduate and graduate students, faculty, and staff of UP Cebu, and three non-UP

affiliated. The tutorial used the modules from the Department of Education as the main

reference but the tutors provided additional writing exercises for reinforcement.

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In the Connecting with Volunteers Stage, the tutors had training on conducting online tutorials,

team building among fellow volunteers, and orientation about the program. In addition, the

tutors and tutees had a “Getting-to-Know You” session to foster positive relationships and

lessen anxiety and discomfort. In the Managing/Retaining Volunteers Stage, the Pahinungod

Office Staff conducted online semi-structured interviews among the tutors after each session

to assess their tutorial experience. The staff also conducted focus-group discussions to clarify

tutorial challenges and to recognize the tutors.

Figure 1 shows a student volunteer tutor who guided the student in organizing a paragraph.

Figure 2 shows a university staff who coached the student in effective writing techniques to

enhance the clarity and coherence of their work. Figure 3 shows a university instructor who

advised the student in developing strong arguments and supporting them with relevant

examples in their paragraph. All names of the tutors and tutees were pseudonyms to protect

their identity.

Figure 1 Online tutorial session with a university student volunteer

Figure 2 Online tutorial session with a university staff volunteer

Markus A. Launer CoSiM Conference Proceeding (2024)

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Figure 3 Online tutorial session with a university instructor volunteer

Results and Discussion

Online Monitoring and Evaluation Strategies

From the semi-structured interviews and FGD results, tutors claimed that the Volunteerism

office provided the following online monitoring and evaluation strategies: (a) promptness in

problem resolution; and (b) giving reminders prior to sessions. According to Ashley, “The staff

was always ready and swift in solving problems, like reaching out to tutees’ who were running

late, and might be absent.” She added, “Their swift responses solve problems immediately.”

Another tutor, Bea, said that the social media posting motivated them to continue improving

their strategies and exercises. She added, “Photos of other sessions inspire me to innovate

my exercise activities.” “Photos also affirm my sense of pride in seeing the tutees’ progress,”

she said.

In addition, Tutor Chelsea expressed her challenges during the tutorial sessions. “Lessons of

the module are too short. We can cover it in one session but I have to split it.” She suggested,

“Maybe we can have additional learning materials to use.” In addition, she mentioned an

instance where her tutee did not make it to the Google Meet link because of an error. “My tutee

was absent in one session because she received the wrong Google Meet link.” “Maybe the

tutees can be briefed thoroughly with the Meet Links and the schedule,” she added.

The testimonies of the tutors proved that the monitoring strategies provided by the Office

fostered strong assurance and emotional stability in conducting the online tutorial. Recognizing

the climate of loneliness and anxiety in an online learning environment (Lythreatis et al., 2022;

Kaufmann & Vallade, 2022), the staff promptly responded to issues concerning non-

attendance of tutees and instructional materials. According to the FGD, the tutors said that

staff were quick and accurate in responding to their immediate technical and instructional

questions. The promptness and precision of response is an essential element in online

tutorials. For example, the tutors experienced cases of students who were late or absent

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during the sessions. They needed to know immediately if these tutees would enter or not in

the Google Meet to avoid unnecessary long waiting time. As Doukakis (2021) states, the real-

time responses can develop successful online sessions.

In addition, the staff’s constant reminders to the tutors before each session made the tutors

more focused and organized. According to a university staff volunteer, she became more

aware of the tutorial sessions because of the notifications in her social media. The staff’s

monitoring strategy proved that successful online sessions require constant communication

comparable to in-person sessions (Richardson, 2016).

Impact on the Tutees

From the FGD, the ALS students stated that the online volunteerism tutorials developed their

writing skills and motivated them to continue their studies. They added that the sessions

promoted their ability to write better content in writing tasks and to be more mindful in

organizing their ideas. According to Tutee Ariana she was thankful to her tutor because she

explained the Effective Writing Modules clearly. Agreeing with Ariana, Tutee Brian shared that

he learned more in writing deeper content because the tutor provided more examples that

demonstrated strong content applicable to real-life. He added that unlike the traditional

classroom with many students, the tutorial was one-on-one which was customized based on

his needs. He expressed his gratitude to the tutor for guiding him.

The sharing of Ariana and Brian demonstrated the power of personalized one-on-one online

tutorials and the dedication of the volunteers in improving the academic performance of the

tutees. If tutors have the content knowledge and proficiency in using technical tools (Gomez-

Rey et al., 2017; Gulbahar and Kalelioglu, 2015) and have the passion to guide the students,

the online tutorials would be successful. According to Doukakis (2021) the real-time interaction

between the tutor and the tutee during the tutorials can develop language skills, motivation,

and reflective learning.

As supplementary support, tutorials can enhance student learning through real-time

interactions (Doukakis, 2021). Tutorials can develop language skills by providing flexibility,

interactivity, motivation, immediate feedback, and reflective learning compared to large face-

to-face classes (Linardopoulos, 2010; Kamardeen, 2014; and Rodrigues and Vethamani,

2015). With the nature of the ALS students to have part-time jobs, online tutorials have

become the preferred method. According to Richardson (2016) and Said et al. (2016),

students would choose online rather than in-person classes due to convenience, flexibility, and

maximizing optimal learning time.

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Table 1. Impact of the tutorial on the ALS students

Themes Categories Sample statements

Developed writing

skills

Developed content Since I’ve already learned the lesson before, it’s

easier for me to understand when my tutor

discusses it with me. As a fan of writing, I appreciate

how her clear explanations and examples have

further improved my content.

My tutor provides examples and guidelines during

our classes.

Developed organization Honestly, this online tutorial has helped me

organize my writing. My tutor discusses the lesson

on rhetorical patterns so well, which helps me clarify

my ideas, and I can use these skills in my everyday

writing.

The tutorial improved my writing, especially my

essays. The first lesson on rhetorical patterns

helped me organize my texts better.

Developed self-

directed learning

Tutors promoted active

participation

She asks for my opinions when introducing new

topics.”

Her voice is very great. It keeps me attentive to her

instructions during our tutorial.

Tutors showed care I love how my tutor checks on me first thing after

missing a session rather than reprimanding.

Another impact of the volunteerism, it developed self-directed learning because of the tutors’

personality of showing care and encouragement. These ALS adult students have part-time

jobs which they deem equally important to their studies. Consequently, these jobs became

one of the reasons for their absences. However, the students claimed that the tutors motivated

them to learn. According to Charlene, she appreciated the tutor’s kindness whenever she

would ask her, “How are you?” She explained that the gesture became more heartwarming

rather than reprimanding about her missed assignments. Furthermore, Ariana shared that she

felt empowered when the tutor asked her opinion before starting the topic. She said it made

her more confident and encouraged her to participate more.

The experiences of Ariane, Brian, and Charlene proved that online volunteer tutors can

transform online learning into a self-directed learning experience if tutors have encouraging

motivational behaviors that promote trust and mindfulness (Heliyon, 2020). The tutors did not

play as the source of writing knowledge but as facilitators of transformative learning. According

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to the tutors, their tutees became more open about their personal life after many sessions.

This sharing promoted more engagement and interest in learning (Collison et. al, 2000). As

Said et al. (2016) highlighted, successful tutors are the tutors who serve as catalysts and

motivators.

Conclusion

The Office of Volunteerism’s online monitoring strategies, such as promptness in problem

resolution and in giving reminders prior to sessions, promoted emotional security, lesser

anxiety, and confidence among the online volunteers. Its prompt and precise online support

through Facebook instant messenger built a stronger communication mechanism for running

the tutorial sessions. These strong supports were translated into positive impact on the ALS

students’ learning. The students claimed that the tutorial developed their writing skills and self-

directed learning. They shared that the tutors’ kindness and volunteerism inspired them to

create better writing outputs and to be more participative during tutorials.

Moreover, the researchers recommend more directness from the tutees, with regards to their

nonattendance, to allow tutors enough flexibility in responding to their circumstances. Tutors

could then arrange makeup sessions or asynchronous writing exercises. Lastly, the

researchers recommend to the Office of Volunteerism and La Salle Greenhills: (a) a thorough

tutee orientation on the schedule and tutorial platform and the basic protocol of nonattendance

and (b) the establishment of a session reminder system for the tutees to prompt their

immediate session attendance-nonattendance status.

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System. International Journal of Scholars in Education, 7(1), 1–16.

https://doi.org/10.52134/ueader.1445226

Castillo, S. (2021). The Relationship of Competencies and Teaching Strategies of Alternative

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Intuitive Decision-Making

Measuring Emotional Intelligence

Joeffrey Maddatu Calimag

1)

and Markus A. Launer

2)

1) Kyungsun University, Korea, Orcid No. 0009-0007-6673-1518

2) Ostfalia University and Institut für gemeinnützige Dienstleistungen gGmbH (non-profit

organization), Orcid No. 0000-0001-9384-0807

Introduction

Measuring Emotional Intelligence (EI) involves assessing an individual’s ability to recognize,

understand, and manage their own emotions, as well as the emotions of others. Various tools

and methods have been developed to quantify EI, ranging from self-report questionnaires to

performance-based assessments. Self-report measures, such as the Emotional Quotient

Inventory (EQ-i) and the Trait Emotional Intelligence Questionnaire (TEIQue), rely on

individuals’ subjective evaluation of their emotional abilities. In contrast, performance-based

assessments, like the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), evaluate

an individual’s actual performance on tasks designed to measure different components of EI,

such as emotion perception and regulation. These tools are widely used in both research and

organizational settings to explore the role of EI in personal and professional success.In this

paper, the authors present the tools used to measure Emotional Intelligence.

Measuring Emotional Intelligence

Emotional intelligence measures tend to use either a self-report personality-based approach,

an informant approach, or an ability-based assessment procedure. In his paper, the

measurement and psychometric properties of four of the major emotional intelligence

measures were discussed (Conte, 2005). He reviewed and examined the comparability of

these measures.

 Emotional Competence Inventory,

 Emotional Quotient Inventory

 Multifactor Emotional Intelligence Scale

 Mayer–Salovey–Caruso Emotional Intelligence Test)

Bru-Luna (2021) conducted a systematic review of existing instruments used to assess

emotional intelligence (EI) in professionals, focusing on their characteristics and psychometric

properties, such as reliability and validity. A literature search was performed using the Web of

Science (WoS) database, resulting in 2,761 items that met the eligibility criteria. From these,

40 different instruments were identified and analyzed. Most of these instruments are based on

Markus A. Launer CoSiM Conference Proceeding (2024)

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three primary models—skill-based, trait-based, and mixed—which differ in how they

conceptualize and measure EI. Each type of tool has its own inherent advantages and

disadvantages. The instruments most frequently reported in the studies include the

 Emotional Quotient Inventory (EQ-i),

 Schutte Self Report Inventory (SSRI),

 Mayer-Salovey-Caruso Emotional Intelligence Test 2.0 (MSCEIT 2.0),

 Trait Meta-Mood Scale (TMMS),

 Wong and Law’s Emotional Intelligence Scale (WLEIS), and

 Trait Emotional Intelligence Questionnaire (TEIQue).

Williams et al. (2009) examined the relationships between trait EI, objective measures of

emotional ability, and psychopathology, and the factor structure of five measures of emotional

skills. According to them, two distinct methods for measuring Emotional Intelligence (EI) are

now well established. The first method, self-report measures, involves questionnaires where

respondents indicate their level of agreement or disagreement with various statements (e.g.,

the Trait Emotional Intelligence Questionnaire – Adolescent Short Form [TEIQue – ASF]

(Petrides et al., 2006). These measures can be susceptible to socially desirable responding,

as individuals may provide answers that present them in a favorable light (Conte, 2005).

The second method, ability-based EI, is assessed by having individuals complete tasks that

require elements of EI to perform well (e.g., the MSCEIT, Mayer, Salovey, & Caruso, 2000).

These tasks may involve identifying emotions from facial expressions or evaluating the

effectiveness of different strategies for managing emotions. However, the scoring methods for

some of these tasks have been criticized for lacking full objectivity (Conte, 2005). Additionally,

it has been argued that ability-based EI measures assess emotion-related knowledge rather

than actual performance and that there is limited evidence supporting the notion that ability EI

is a latent trait that can be reliably measured psychometrically (Brody, 2004; Williams et al.

(2009)).

Dulewicz and Higgs (2000b) found that, in a sample of general managers, an Emotional

Intelligence scale based on 16 relevant competencies demonstrated strong reliability and

predictive validity over a seven-year period. Building on these findings and a comprehensive

literature review, they aimed to move beyond competency assessment. By developing the

questionnaire, Cronbach alpha reliability co‐efficiency for each of the element scales ranged

from 0.6 to 0.8. The alpha for the overall EIQ score derived from the seven elements was 0.77

(Dulewicz & Higgs, 2000a).

They developed a tailored questionnaire, the Emotional Intelligence Questionnaire (EIQ),

designed to specifically assess seven elements of an individual's emotional intelligence

through self-report (Dulewicz and Higgs, 1999; 2000a; Dulewicz, Higgs & Slaski, 2003).

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1. self‐awareness: being aware of one's feelings and managing them;

2. emotional resilience: being able to maintain one's performance when under

pressure;

3. motivation: having the drive and energy to attain challenging goals or targets;

4. inter‐personal sensitivity: showing sensitivity and empathy towards others;

5. influence: influencing and persuading others to accept one's views or proposals;

6. intuitiveness: making decisions using reason and intuition when appropriate; and

7. conscientiousness: being consistent in one's words and actions, and behaving

according to prevailing ethical standards.

The structure of the second tool, the EQ-i (Emotional Quotient Inventory), is grounded in the

existing literature and its author's experience as a clinical psychologist (Bar-On, 1997a). The

concept was developed by logically grouping variables and identifying key underlying factors

believed to influence effective and successful functioning and promote positive emotional

health (Bar-On, 1997b). The EQ-i provides a total EQ score, five composite scale scores, and

15 sub-scale scores, as defined by Bar-On (1997a). This structure, outlined in Table I, was

empirically supported through several factor analyses, confirming the 1-5-15 framework of the

EQ-i. Thus, the EQ-i represents a hierarchical model of emotional intelligence (Bar-On, 1997a).

Accordeing to Zadorozhny et al. (2024) the Trait Emotional Intelligence Questionnaire

(TEIQue) is the only inventory that directly and comprehensively operationalizes the trait EI

theory (Austin et al., 2008; Petrides et al., 2016).

Finegan (1989) discussed emotional intelligence as a subset of social intelligence and

personal intelligences (Gardner, 1983), describing it as a mental ability that facilitates the

cognitive processing of emotions (Mayer and Salovey, 1993). Three studies are highlighted to

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illustrate the concept of emotional intelligence and its measurement: (1) a study by Mayer,

DiPaolo and Salovey (1990) involving 139 undergraduates, which examined the ability to

recognize emotional content in visual stimuli; (2) a study by Salovey et al. (1995) with 86

participants, which focused on measuring individual differences in the ability to attend to,

clarify, and manage emotions; and (3) a study by Mayer and Geher (1996) with 40 participants,

which investigated the accurate identification of emotions. The implications of emotional

intelligence for achievement, emotional well-being, and cultural contexts are also discussed.

Emotional Intelligence was assessed by Downey, Papageorgiou and Stough (2006) byusing

the Swinburne University Emotional Intelligence Test (SUEIT; Palmer and Stough, 2001) for

the workplace. The workplace SUEIT is a 64-item self-report test designed to measure how an

individual typically thinks, feels, and behaves at work based on emotional information.

Participants rate each statement on a 5-point Likert-type scale (1 = never, 5 = always),

indicating the degree to which each statement reflects their usual thoughts, feelings, and

actions in a work setting. A second measure of Emotional Intelligence (EI) used by Downey,

Papageorgiou and Stough (2006) n the study was the Trait Meta-Mood Scale (TMMS; Salovey

et al., 1995). The TMMS is a 30-item self-report instrument where participants respond on a

5-point scale (1 = strongly disagree, 5 = strongly agree). The items are divided into three

subscales, based on factor analyses conducted by Salovey and his colleagues: attention to

feelings (e.g., "I pay a lot of attention to how I feel"), clarity of feelings (e.g., "I am usually very

clear about my feelings"), and mood repair (e.g., "Although I am sometimes sad, I have a

mostly optimistic outlook") (Downey, Papageorgiou & Stough, 2006). Preliminary psychometric

analysis of the TMMS by Salovey et al. (1995) indicates that this scale can serve as a reliable

and valid self-report measure of the ability to monitor and regulate emotions. Their findings

show that each subscale of the TMMS captures a coherent and internally consistent construct,

with reliability coefficients for attention to feelings for clarity of feelings, and for mood repair.

Additionally, the scale demonstrates evidence of both convergent and discriminant validity.

The results of Downey, Papageorgiou and Stough, (2006) were:

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Tapia, M. (2001) measures emotional intelligence. Tapia (2001) (a) developed a measure of

emotional intelligence called the Emotional Intelligence Inventory and (b) identified the

underlying dimensions of this inventory by testing 111 high school students at a bilingual

college preparatory school. The original inventory consisted of 45 items, but after removing

the four weakest items, the reliability coefficient was α = 0.83. The revised 41-item inventory

was then administered to 319 junior and senior high school students at the same school,

resulting in a reliability coefficient of α = 0.81. A maximum likelihood factor analysis with

varimax rotation identified four factors: empathy, utilization of feelings, handling relationships,

and self-control. The psychometric properties of the revised Emotional Intelligence Inventory

were robust, making it a suitable tool for investigating emotional intelligence (Tapia, 2001).

Caruso, Mayer and Salovey (2002) research the relation of an ability measure of emotional

intelligence to personality. Is emotional intelligence merely a simplistic theory of personality,

or does it represent a distinct form of intelligence? For emotional intelligence to be meaningful,

it must capture something unique that is not encompassed by standard personality traits. To

investigate this, the study examined an ability-based test of emotional intelligence and its

relationship to various personality test variables to assess the degree of overlap between these

constructs (Caruso, Mayer & Salovey, 2002). Dulewicz, Higgs and Slaski (2003) measure the

content, construct and criterion‐related validity of emotional intelligence. They summarize

existing information on the reliability and validity of two measures of EI, the Dulewicz and Higgs

EIQ and the Bar‐on EQ‐i.

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Salovey, Mayer, Caruso and Lopes (2003) measure emotional intelligence as a set of abilities

with the Mayer-Salovey-Caruso Emotional Intelligence Test. Mayer,Salovey, Caruso and

Sitarenios (2003) measure emotional intelligence with the MSCEIT V2.0. Dulewicz, V., &

Higgs, M. (2000) researched emotional intelligence with a review and evaluation study. Schutte

et al. (1998) developmed and validated a measure of emotional intelligence. Personality and

individual differences. Schutte et al. (1998) developed a measure of emotional intelligence

based on the model proposed by Salovey and Mayer (1990) in their work Emotional

Intelligence. The initial pool of 62 items was designed to reflect the different dimensions of this

model. A factor analysis conducted on responses from 346 participants led to the creation of

a 33-item scale. Further studies demonstrated that the 33-item measure had strong internal

consistency and test-retest reliability. Validation studies revealed that scores on this measure

(a) correlated with eight out of nine theoretically related constructs, such as alexithymia,

attention to feelings, clarity of feelings, mood repair, optimism, and impulse control; (b)

predicted first-year college grades; (c) were significantly higher for therapists compared to

therapy clients or prisoners; (d) were significantly higher for females than males, aligning with

previous research on emotional skills; (e) showed no relation to cognitive ability; and (f) were

associated with the openness to experience trait within the Big Five personality dimensions.

Groves, Pat McEnrue and Shen (2008). primary measure is based on the Mayer and Salovey

(1997) model “Mayer-Salovey-Caruso Emotional Intelligence Test”, short MSCEIT9 (Mayer et

al., 2003). Existing research indicates that the MSCEIT has robust psychometric properties,

including strong construct, convergent, discriminant, and predictive validities, particularly when

compared to other emotional intelligence measures (Daus and Ashkanasy, 2005; McEnrue

and Groves, 2006; Day and Carroll, 2004; O'Conner and Little, 2003; Brackett and Mayer,

2003). Groves, Pat McEnrue and Shen (2008) specifically examined the measure for its utility

for management development applications.

Mayer, J. D., Salovey, P., Caruso, D. R., & Sitarenios, G. (2001). Emotional intelligence as a

standard intelligence. Pérez, Petrides and Furnham (2005). Measure trait emotional

intelligence. Emotional intelligence. Groves, Pat McEnrue and Shen (2008) develope and

measures emotional intelligence of leaders. They empirically test whether it is possible to

deliberately develop emotional intelligence as conceptualized in the Mayer and Salovey model.

Roberts, Schulze and MacCann (2008) describe the status of measurements of emotional

intelligence in 2008.

The latest studies in 2024

Saikia, George, Unnikrishnan, Nayak and Ravishankar (2024) describe thirty years of

emotional intelligence. They provide a scoping review of emotional intelligence training

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program among nurses. They analyze the stressful environment of healthcare setting that can

be detrimental to nurses' mental and emotional health.

Zadorozhny et al (2024) determined the temporal stability of a construct is essential for

confirming its validity and usefulness in real-world settings. To date, there have been few

studies examining the test-retest reliability of trait emotional intelligence (trait EI), especially

over longer durations. The present study provides data from the Trait Emotional Intelligence

Questionnaire (TEIQue) over various intervals, ranging from 30 days (one month) to 1,444

days (approximately four years). The findings support trait EI theory, showing strong temporal

stability across all levels of the construct, including global, factor, and facet levels.

According to Zadorozhny et al (2024), there are currently few measures of Emotional

Intelligence (EI) that have demonstrated test-retest reliability, internal consistency, and validity

in terms of a robust factor structure and predictive ability (Davis & Wigelsworth, 2018). To date,

there have been limited studies on the test-retest reliability of the Trait Emotional Intelligence

Questionnaire (TEIQue) (Perazzo et al., 2021), and most of these studies have not adequately

assessed its temporal stability due to their use of short test-retest intervals (Costa & McCrae,

1998; Wood et al., 2022). It has been suggested that intervals of less than a year are

considered short-term for evaluating the stability of personality traits (Murray et al., 2003;

Schuerger et al., 1989). As a result, using shorter test-retest intervals limits the ability to

examine longitudinal changes and may introduce confounding factors such as memory effects

(Sovet et al., 2014; Zadorozhny et al (2024)).

Mayer et al (2024) research how many emotional intelligence abilities are there. They provide

an examination of four measures of emotional intelligence. Various measures of emotional

intelligence have been developed over nearly 25 years to assess the four-area model of

emotional intelligence:

 the Multifactor Emotional Intelligence Scale, (MEIS, Mayer, Caruso, & Salovey,

1999),

 the Mayer-Caruso-Salovey Emotional Intelligence Test (MSCEIT, Mayer, Salovey, &

Caruso, 2002),

 the Youth Research Version (YRV) of the MSCEIT (MSCEIT-YRV, Mayer, Salovey, &

Caruso, 2014) and

 a forthcoming version (MSCEIT-2; Mayer et al., 2023).

According to Yousaf, Javed and Badshah (2024), the interdependent dynamics of innovative

work behavior (IWB), innovative culture (IC), employee inventive performance (EIP), and

emotional intelligence (EI) become apparent as key factors influencing the creative fabric of

firms.

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Emotional Quotient Inventory® 2.0 (EQ-i® 2.0)

The EQ-i 2.0 is one of the most advanced and thoroughly researched measures of emotional

intelligence in the assessment industry. This tool is indispensable for personal, professional,

and leadership development, and for recruiting high performing talent. The EQ-i 2.0 measures

a set of emotional and social skills that influence the way people perceive and express

themselves, develop and maintain social relationships, cope with challenges, and use

emotional information in an effective and meaningful way. The EQ-i 2.0 highlights an

individual’s emotional and social strengths and weaknesses. A growing body of research

suggests that emotional intelligence is a key determinant of success in life.

Assessment Scales

The EQ-i 2.0 includes five validity indices rendering a Total Emotional Intelligence score plus

the following composite scores:

 Self-Perception: Self-Regard, Self-Actualisation, Emotional Self-Awareness

 Self-Expression: Emotional Expression, Assertiveness, Independence

 Interpersonal: Interpersonal Relationships, Empathy, Social Responsibility

 Decision Making: Problem Solving, Reality Testing, Impulse Control

 Stress Management: Flexibility, Stress Tolerance, Optimism

 Well-Being Indicator: Happiness

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The Trait Meta-Mood Scale 24, with 24 questions, in five-point Likert scale.

1 I pay a lot of attention to my feelings.

2 I am usually very conscious of what I feel.

3 I usually spend time thinking about my emotions.

4 I think my emotions and state of mind deserve to be paid attention to.

5 I allow my feelings to affect my thoughts.

6 I constantly think about my state of mind.

7 I often think about my feelings.

8 I pay a lot of attention to the way I feel.

9 My feelings are clear to me.

10 I can usually define my feelings.

11 I nearly always know how I feel.

12 I usually know how I feel about people.

13 I often become aware of my feelings in different situations.

14 I can always say how I feel.

15 I can sometimes say which emotions I am experiencing.

16 I can manage to understand my feelings.

17 I usually have an optimistic outlook, although I sometimes feel sad.

18 Even when I feel sad, I try to think about pleasant things.

19 When I am sad, I think about all life’s pleasures.

20 I try to have positive thoughts even when I feel bad.

21 If I think about things too much and end up complicating them, I try tocalm myself down.

22 I am concerned about having a good state of mind.

23 I have a lot of energy when I feel happy.

24 When I am angry, I try to change my state of mind.

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Appendix: Mayer-Caruso-Salovey Emotional Intelligence Test (MSCEIT, Mayer, Salovey,

& Caruso, 2002), MSCEIT™ measures Emotional intelligence. A Closer Look at the Four

Abilities

Perceiving Emotions

What is Perceiving Emotions? Everyone experiences and relates to feelings and emotions.

Even the world around you communicates and sends emotional messages. Emotions contain

valuable information about relationships and about the world around you. This ability to

perceive emotions starts with being aware of these emotional clues, and then accurately

identifying what they mean. How is this ability used? You need to be aware of your own

feelings and emotions so that you have accurate information about the world around you.

Being aware of others' emotions is a key to working with people.

Using Emotions to Facilitate Thought What is Using Emotions?

How we feel influences how we think. If you feel sad, you may view the world one way, while

if you feel happy, you interpret the same events differently. People in a sad or negative mood

tend to focus on details and search for errors. Those in a more positive mood are better at

generating new ideas and novel solutions to problems. Knowing which moods are best for

which situations and "getting in the right mood" is an ability. How is this ability used? If you

stay aware of your emotions, which contain valuable information, and then use them to solve

problems, the outcome may be more positive.

Understanding Emotions

Emotions contain information, and our ability to understand this information and think about it

plays an important role in our day-to-day life. This ability answers questions such as: Why are

we feeling happy? How will my friend feel if I say that to him? What will happen if I say that to

her? How is this ability used? Insight into ourselves, and others, may require emotional

knowledge. This knowledge helps us to understand people better.

Managing Emotions

What is Managing Emotions? If emotions contain information, then ignoring this information

means that we can end up making a poor decision. At times, we need to stay open to our

feelings, learn from these feelings, and use this information to make decisions and to take

appropriate action. Sometimes, though, it may be best to disengage from an emotion and

return to it later in order to manage it effectively. How is this ability used? If you can find the

right balance in managing your emotions, you should be more sucessfull.

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Wong and Law’s Emotional Intelligence Scale (WLEIS),

Instrucciones: A continuación, encontrará algunas afi rmaciones sobre sus emociones y

sentimientos. Lea atentamente cada frase e indique por favor el grado de acuerdo o

desacuerdo con respecto a las mismas [Instructions: Here you will fi nd some statements about

your emotions and feelings. Please read carefully each statement and indicate the extent to

which you agree or disagree with that statement] Evaluación de las propias emociones [Self-

Emotion Appraisal, SEA]

1. La mayoría de las veces sé distinguir porqué tengo ciertos sentimientos [I have a good

sense of why I have certain feelings most of the time]

2. Tengo una buena comprensión de mis propias emociones [I have good understanding of

my own emotions]

3. Realmente comprendo lo que yo siento [I really understand what I feel]

4. Siempre sé si estoy o no estoy feliz [I always know whether or not I am happy] Evaluación

de las emociones de los demás [Other´s Emotion Appraisal, OEA]

5. Conozco siempre las emociones de mis amigos a través de sus comportamientos [I always

know my friends’ emotions from their behaviour]

6. Soy un buen observador de las emociones de los demás [I am a good observer of others’

emotions]

7. Soy sensible a los sentimientos y emociones de los demás [I am sensitive to the feelings

and emotions of others]

8. Tengo una buena comprensión de las emociones de las personas que me rodean [I have

good understanding of the emotions of people around me] Uso de las emociones [Use of

Emotion, UOE]

9. Siempre me fi jo metas y luego intento hacerlo lo mejor para alcanzarlas [I always set goals

for myself and then try my best to achieve them]

10. Siempre me digo a mi mismo que soy una persona competente [I always tell myself I am

a competent person]

11. Soy una persona auto-motivadora [I am a self-motivating person]

12. Siempre me animo a mi mismo para hacerlo lo mejor que pueda [I would always encourage

myself to try my best] Regulación de las emociones [Regulation of Emotion, ROE]

13. Soy capaz de controlar mi temperamento y manejar las difi cultades de manera racional [I

am able to control my temper so that I can handle diffi culties rationally]

14. Soy capaz de controlar mis propias emociones [I am quite capable of controlling my own

emotions]

15. Me puedo calmar fácilmente cuando me siento enfadado [I can always calm down quickly

when I am very angry]

16. Tengo un buen control de mis propias emociones [I have good control of my own emotions]

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Appendix: Brief Emotional Intelligence Scale- 10 (BEIS-10)

This instrument can be found at: Davies et al. (2010): Validity and reliability of a brief emotional

intelligence scale (BEIS-10).

1= Strongly Disagree to 5= Strongly Agree

Appraisal of own emotions

1. I know why my emotions change

2. I easily recognize my emotions as I experience them

Appraisal of others’ emotions

3. I can tell how people are feeling by listening to the tone of their voice

4. By looking at their facial expressions‚ I recognize the emotions people are experiencing

Regulation of own emotions

5. I seek out activities that make me happy

6. I have control over my emotions

Regulation of others’ emotions

7. I arrange events others enjoy

8. I help other people feel better when they are down

Utilization of emotions

9. When I am in a positive mood‚ I am able to come up with new ideas

10.I use good moods to help myself keep trying in the face of obstacles

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Schutte Emotional Intelligence Scale (SEIS)

Schutte et al (1998) describe appraisal and expression of emotion (13 items)‚ Regulation of

emotion (10 items)‚ Utilisation of emotion (10 items).

1. I know when to speak about my personal problems to others.

2. When I am faced with obstacles‚ I remember times I faced similar obstacles and overcame them.

3. I expect that I will do well on most things I try.

4. Other people find it easy to confide in me.

5. I find it hard to understand the nonverbal messages of other people.

6. Some of the major events of my life have led me to re-evaluate what is important and not important.

7. When my mood changes‚ I see new possibilities.

8. Emotions are some of the things that make my life worth living.

9. I am aware of my emotions as I experience them.

10.I expect good things to happen.

11.I like to share my emotions with others.

12.When I experience a positive emotion‚ I know how to make it last.

13.I arrange events others enjoy.

14.I seek out activities that make me happy.

15.I am aware of the nonverbal messages I send to others.

16.I present myself in a way that makes a good impression on others.

17.When I am in a positive mood‚ solving problems is easy for me.

18.By looking at their facial expressions‚ I recognize the emotions people are experiencing.

19.I know why my emotions change.

20.When I am in a positive mood‚ I am able to come up with new ideas.

21.I have control over my emotions.

22.I easily recognize my emotions as I experience them.

23.I motivate myself by imagining a good outcome to tasks I take on.

24.I compliment others when they have done something well.

25.I am aware of the nonverbal messages other people send.

26.When another person tells me about an important event in his or her life‚ I almost feel as

though I have experienced this event myself.

27.When I feel a change in emotions‚ I tend to come up with new ideas.

28.When I am faced with a challenge‚ I give up because I believe I will fail.

29.I know what other people are feeling just by looking at them.

30.I help other people feel better when they are down.

31.I use good moods to help myself keep trying in the face of obstacles.

32.I can tell how people are feeling by listening to the tone of their voice.

33.It is difficult for me to understand why people feel the way they do.

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Trait Emotional Intelligence Questionnaire (TEIQUE), TEIQUE v.1.50

Short Form TEIQUE-SF

Well-being (5‚ 9‚ 20‚ 24‚ 12‚ 27); self-control (4‚ 7‚ 15‚ 19‚ 22‚ 30); emotionality

(1‚2‚8‚13‚16‚17‚23‚28); sociability (6 ‚10‚ 11‚21‚25‚ 26)

1= Completely Disagree to 7= Completely Agree

1. Expressing my emotions with words is not a problem for me.

2. I often find it difficult to see things from another person’s viewpoint. *

3. On the whole‚ I’m a highly motivated person.

4. I usually find it difficult to regulate my emotions. *

5. I generally don’t find life enjoyable. *

6. I can deal effectively with people.

7. I tend to change my mind frequently. *

8. Many times‚ I can’t figure out what emotion I’m feeling. *

9. I feel that I have a number of good qualities.

10.I often find it difficult to stand up for my rights. *

11.I’m usually able to influence the way other people feel.

12.On the whole‚ I have a gloomy perspective on most things. *

13.Those close to me often complain that I don’t treat them right. *

14.I often find it difficult to adjust my life according to the circumstances. *

15.On the whole‚ I’m able to deal with stress.

16.I often find it difficult to show my affection to those close to me. *

17.I’m normally able to “get into someone’s shoes” and experience their emotions.

18.I normally find it difficult to keep myself motivated. *

19.I’m usually able to find ways to control my emotions when I want to.

20.On the whole‚ I’m pleased with my life.

21.I would describe myself as a good negotiator.

22.I tend to get involved in things I later wish I could get out of. *

23.I often pause and think about my feelings.

24.I believe I’m full of personal strengths.

25.I tend to “back down” even if I know I’m right. *

26.I don’t seem to have any power at all over other people’s feelings. *

27.I generally believe that things will work out fi ne in my life.

28.I find it difficult to bond well‚ even with those close to me. *

29.Generally‚ I’m able to adapt to new environments.

30.Others admire me for being relaxed.

* Reverse scored

Well-being: [Self-esteem; Happiness; Optimism]‚

Self-control: [Emotion Regulation; low Impulsiveness; Stress Management]

Emotionality: [Empathy; Emotion Perception; Emotion Expression; Relationship Skills]

Sociability: [Emotion management; Assertiveness; Social awareness/ Social Competence]

Auxiliary facets: [Adaptability; Self-motivation]

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Swinburne University Emotional Intelligence Test (SUEIT)

Palmer & Stough‚ 2001

EI: Emotional Recognition and Expression (ERE); Understanding Emotions External (UE);

Emotions Direct Cognition (EDC); Emotional Management (EM); and Emotional Control (EC).

1=Never‚ 2= Seldom‚ 3= Sometimes‚ 4= Usually‚ 5= Always

1. I can tell how others are feeling.

2. I generate positive moods and emotions within myself to get over being frustrated.

3. Examination of feelings is useful in solving problems.

4. When I’m anxious I can remain focused on what I am doing.

5. I can tell whether others like each other or not.

6. When I’m under stress‚ I tend to irritate those around me.

7. I find it difficult to talk about my feelings with others.

8. I find it hard to determine how others are feeling from their body language alone.

9. Difficult situations elicit emotions in me that I find hard to overcome.

10. Others find it easy to pick-up on how I am feeling.

11. I find it difficult to keep from getting stressed out when I am under a lot of pressure.

12. My moods and emotions help me generate new ideas.

13. I can tell how others feel by the tone of their voice.

14. When I am anxious‚ I find it difficult to express this to others.

15. I find it easy to influence the moods and emotions of those around me.

16. I don’t easily pick-up on the emotional overtones of the environment I am in.

17. I can tell when others are trying to hide their true feelings.

18. I try not to let my emotions guide me when problem solving.

19. I find it easy to control my anger.

20. I can describe my feelings on an issue to others.

21. I don’t think it’s a good idea to use emotions to guide my decision making.

22. I find it hard to identify if somebody is upset without them telling me.

23. I find it hard to get people to cooperate with each other.

24. I come up with new ideas using rational thoughts rather than my moods and emotions.

25. I find it hard to concentrate on a task when I’m really excited about something.

26. I can portray how I’m feeling to others through my body language.

27. I find it hard to determine friendships between people I don’t know well.

28. I overcome conflict with others by influencing their moods and emotions.

29. I watch the way people react to things when I’m trying to build rapport with them.

30. My problem solving is based on sound reasoning rather than feelings.

31. I find it difficult to think clearly when I’m feeling anxious about something.

32. I have trouble finding the right words to express how I feel.

33. I find it difficult to get others excited about things.

34. I can pick-up on the emotional ‘overtone’ of the discussion.

35. I attend to my feelings on a matter when making important decisions.

36. I overcome anger by thinking through what’s causing it.

37. Others know when I am worried.

38. I readily understand the reasons why I have upset someone.

39. I find it hard to reduce anxiety in others.

40. I weigh-up how I feel about different solutions to problems.

41. I can be upset and still think clearly.

42. I find it hard to convey my anxiety in others.

43. I can determine when other’s emotional reactions are inappropriate.

44. I find it easy to comfort others when they are upset about something at work.

45. Other’s facial expressions reveal a lot to me about the way they are feeling.

46. I find it difficult to control strong emotions.

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47. Feelings should be kept at bay when making important decisions.

48. I readily notice the ‘feel’ of different environments.

49. When something gets me down I find it difficult to snap out of it.

50. I go with my ‘feelings’ when making important decisions.

51. I can detect my emotions as I experience them.

52. When discussing an issue‚ I find it difficult to tell whether others feel the same way as me.

53. Thinking about how I felt in certain situations helps me to remember them.

54. I can easily snap out of feeling down.

55. I find it hard to distinguish my emotions.

56. I can tell when someone feels the same way as myself about another person without

actually discussing it.

57. I find it difficult to maintain positive moods and emotions when I’m under stress.

58. When others get worked-up I stay out of their way.

59. I find it hard to determine exactly how others feel about issues I have with them.

60. When something goes wrong in my life‚ I find it difficult to remain positive.

61. Others can easily tell how I feel.

62. I try to keep emotions out of my decision making.

63. I can tell when someone doesn’t really like me.

64. When someone upsets me‚ I think through what the person has said and find a solution.

Conclusion

It could be shown that Emotional Intelligence can be measured with different scales. The

authors recommend further research on this connection.

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Managing Intuitive and Emotional Intelligence for Digital Wisdom and the

Future

Marcus Anthony

Beijing Institute of Technology, China, Orcid No. 0000-0003-0211-2770

Extended Abstract

The significance of digital literacy in today’s society is widely recognized. It has become

increasingly evident that emotional intelligence (Goleman, 2011) holds greater importance in

the digital era, particularly in light of the ongoing crisis in sensemaking. This crisis

encompasses the pervasive confusion and uncertainty surrounding the definitions of truth,

morality, and wisdom, along with the challenges posed by misinformation and disinformation.

The swift advancement of technology and the omnipresent influence of social media have

exacerbated this crisis, necessitating the ability of individuals and societies to navigate the

digital landscape with heightened discernment. This paper posits that the fundamental

competencies of the future will include emotional intelligence (comprising mindfulness, intuitive

acuity, embodiment, empathy, and awareness of emotional triggers); digital literacy (which

entails a foundational understanding of digital economies, digital media, and media literacy);

and essential psychological insights (addressing human biases, conditioning, suggestion,

contagion effects, motivation and more) (Anthony, 2022, 2013).

A central tenet of this paper is that merely grasping the workings of software and hardware, as

well as the economic frameworks underlying the internet and social media (digital literacy), is

inadequate for fostering a robust level of self-awareness and self-empowerment in the digital

age. This inadequacy arises because major tech firms have adeptly mastered the techniques

of capturing users' attention and sustaining their engagement through algorithms and

behavioral nudges. Consequently, there is an urgent need to broaden the conventional

spectrum of human cognitive abilities. This expansion is vital not only to promote greater

mindfulness and present-mindedness but also to encourage a deeper sense of embodiment

within our digital interactions.

Emotional intelligence, which encompasses mindfulness, intuitive acuity, and the cultivation of

wisdom, is an essential aspect of Marcus T. Anthony’s (2022, 2023) framework of Digital

Wisdom. Digital Wisdom is structured around three key areas: Know Thyself, Know the

Humans, and Know the Machines. This framework has been purposefully developed to move

beyond the now outmoded notion of Digital Literacy, which is closely aligned with the third

domain of Digital Wisdom: Know the Machines (Anthony, 2022, 2023). By merging emotional

intelligence with digital literacy, this paper seeks to advocate for teaching these concepts within

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a wider framework that recognizes the interplay between technological advancements and

human emotions.

The paper will begin by clarifying the definitions of emotional intelligence and digital literacy,

followed by an examination of the relevance of Digital Wisdom in the contemporary digital

landscape, particularly amidst the current AI explosion (Anthony, 2022, 2023). Subsequently,

the discussion will outline various contemporary issues through which these concepts can be

applied in concert. The crisis in sensemaking will be explored in depth, along with associated

developments, including rising rates of anxiety, depression, and suicide, a crisis of meaning,

and diminishing trust in media, compounded by the spread of misinformation and

disinformation across various platforms.

The interrelationship between emotional intelligence, mindfulness, present-mindedness, and

embodiment is increasingly acknowledged. Daniel Goleman (2011) highlights the significance

of self-awareness and emotional regulation as fundamental components of mindfulness,

suggesting that nurturing mindfulness can enhance emotional intelligence. This enhancement

enables individuals, whether online or offline, to react to emotional stimuli in a more thoughtful

and “intelligent” manner. Jon Kabat-Zinn (2013), who is renowned for creating Mindfulness-

Based Stress Reduction programs, supports this idea, asserting that mindfulness practices

can lead to improved empathetic responses. Such improvement is critical in an increasingly

fragmented and divided digital culture, where understanding and compassion often take a back

seat to division.

Moreover, Patricia Jennings (2015) emphasizes the importance of mindfulness within

educational contexts, advocating for its incorporation to promote emotional intelligence among

educators and students alike. Her research underscores the necessity of resilience in

confronting the challenges of modern education, particularly regarding emotional and

psychological well-being. This paper will draw on Jennings’ findings to demonstrate how

emotional intelligence can be cultivated in educational environments, preparing future

generations with the competencies needed to flourish in a complex digital ecosystem.

Additionally, the implications of emotional intelligence and digital literacy extend beyond

individual well-being; they profoundly influence organizational and societal dynamics. As

workplaces become increasingly digital and interconnected, it is essential for leaders and

employees alike to develop emotional intelligence to foster collaboration, innovation, and trust

(Goleman, 2011). Organizations that prioritize emotional intelligence within their cultures are

better equipped to navigate the complexities of the digital era, as they can address challenges

with empathy, agility, and insight.

In summary, the integration of emotional intelligence and digital literacy is not merely

advantageous; it is vital for successfully maneuvering through the intricacies of the digital age.

By embracing the concept of Digital Wisdom, as articulated by the author (Anthony, 2023) we

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can create a more comprehensive approach to education and personal development that

equips individuals to thrive amidst the challenges posed by misinformation, emotional distress,

and the rapid evolution of technology. Ultimately, this paper advocates for a paradigm shift in

how we perceive and teach these competencies, fostering a future where emotional

intelligence and digital literacy coexist harmoniously, empowering individuals to make wise

and informed choices in their personal and professional endeavors.

Keywords: emotional intelligence, digital literacy, mindfulness, crisis in sensemaking, well-

being, resilience, artificial intelligence, intuition, misinformation, disinformation.

References

Anthony, M.T. (2022). “A Critical Futures Studies Perspective on Embodiment and the Crisis

in Sensemaking.” In: Crisis Management - Principles, Roles and Application.

10.5772/intechopen.107776.

Anthony, M.T. (2023). Power and Presence: Reclaiming Your Authentic Self in a Digitised

World. MindFutures.

Goleman, D. (2011). Leadership: The Power of Emotional intelligence. More Than Sound.

Jennings, P. A. (2015). Mindfulness for teachers: Simple skills for peace and productivity in

the classroom. W. W. Norton & Company.

Kabat-Zinn, J. (2013). Full catastrophe living: Using the wisdom of your body and mind to face

stress, pain, and illness. Bantam Books.

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Rational and Intuitive Decision-Making in the Area of Sustainability: a Review

of Literature

Piotr Pietrzak

1)

, Markus A. Launer

2)

and Marta Mendel

1)

1) Warsaw University of Life Sciences, Poland, Orcid No. 0000-0002-1319-4815 and

0000-0003-0202-2169

2) Ostfalia University and Institut für Dienstleistungen gGmbH (non-profit organization),

Germany, Orcid No. 0000-0001-9384-0807

Introduction

In today’s complex global environment, the pursuit of sustainability has become a critical

priority for organizations, governments, and individuals alike. As we face unprecedented

challenges related to climate change, resource depletion, and social inequality, decision-

making processes have taken center stage in shaping a sustainable future. The way we make

decisions - whether through rational analysis or intuitive judgment - can significantly influence

the effectiveness and impact of sustainability initiatives.

Although sustainability is gaining recognition as an important research area (e.g. Markard et

al. 2012; Baumgartner, 2014; Ceschin & Gaziulusoy, 2016; Engert, Rauter & Baumgartner,

2016), additional studies are necessary to explore how managers incorporate sustainability

principles into their everyday decision-making and project operations. This highlights a need

for further research to identify effective strategies and methods for embedding sustainability

into the routine processes of project management (Silvius et al., 2017). Therefore, the aim of

this study is to conduct a literature review on rational and intuitive decision-making in the field

of sustainability.

The intended audience for this study includes academics and researchers focused on

decision-making theories, sustainability, and project management. It also targets managers

and decision-makers, particularly in sectors like energy, manufacturing, and corporate social

responsibility, who are looking for practical ways to integrate sustainability into their daily

operations. Additionally, sustainability professionals, such as consultants, sustainability

officers, and environmental analysts, who aim to apply decision-making frameworks to achieve

sustainable results, will find value in this research. Lastly, policy makers and government

officials, interested in how decision-making processes shape sustainability initiatives and

influence regulatory policies, are also key readers.

The article consists of five sections. After the introduction, the key principles of the

sustainability concept will be presented. Next, the nature of rational and intuitive decision-

making will be explained. The following section will showcase the existing research findings

on rational and intuitive decision-making for sustainability. The article ends with conclusions.

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Sustainable development - basic principles

The dynamic economic growth in the second half of the 20th century not only contributed to

increasing prosperity in many developed countries but also led to accelerated environmental

depletion and the impoverishment of populations. In response to these problems, the concept

of sustainable development emerged. It integrates elements from multiple disciplines,

including natural sciences, social sciences, and the humanities. Over the years, it has been

defined and interpreted in various ways (e.g. Spangenberg, 2011; Morioka & de Carvalho,

2016; Amui et al., 2017). The concept of sustainable development arose from concerns about

the Earth’s ecosystem's ability to withstand the pressures caused by human activity. It was a

deliberate effort aimed at preventing, or at least reducing, the imbalance between economic

growth and social development, as well as between socio-economic development and the

natural environment. That is why, the sustainable development, in the literature (e.g., Purvis

et. al, 2019), is described using the three-column (pillars) model, the equilateral triangle model,

or the three overlapping circles model - see Figure 1. These models indicate that sustainable

development can only be achieved by treating all three areas equally, without any one area

dominating the others.

Figure 1. Models describing the concept of sustainable development

Source: Purvis et. al, 2019, p. 682.

The term “sustainable development” was introduced into global discourse by the United

Nations (UN) bodies. The concept was first mentioned during the UN Conference on the

Human Environment, held in Stockholm in 1972. Its precursor was the notion of

“ecodevelopment”, described as a development strategy focused on the rational use of local

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resources and the knowledge held by farmers for the benefit of isolated rural areas in the Third

World (Nowak, 2022).

The concept of sustainable development is currently described through the lens of the

Sustainable Development Goals (SDGs). This is a set of 17 goals and 169 targets, adopted

by the UN General Assembly in 2015 as part of the “2030 Agenda”. These goals provide a

concrete list of priority actions and directions aimed at achieving sustainable development

globally. Among them, one can identify (Mio et al., 2020): (1) “No Poverty”, (2) “Zero Hunger’,

(3) “Good Health and Well-Being”, (4) “Quality Education”, (5) “Gender Equality”, (6) “Clean

Water and Sanitation”, (7) “Affordable and Clean Energy”, (8) “Decent Work and Economic

Growth”, (9) “Industry, Innovation and Infrastructure”, (10) “Reduced Inequalities”, (11)

“Sustainable Cities and Communities”, (12) “Responsible Consumption and Production”, (13)

“Climate Action”, (14) “Life below Water”, (15) “Life on land”, (16) “Peace, Justice and Strong

Institutions”, (17) “Partnership for the Goals”.

Rational and intuitive decision-making - basic principles

The exploration of decision-making processes is far from new and has been developing for

approximately 300 years, drawing insights from various disciplines (Oliveira, 2007). These

contributions have included establishing mathematical bases for economics and applying

decision theories to diverse fields such as finance, medicine, the military, and cybernetics.

Consequently, decision theories have integrated numerous widely recognized concepts and

models, which significantly impact nearly all biological, cognitive, and social sciences (Oliveira,

2007). Among different concepts, attention is given to rational and intuitive decision-making.

Rational behavior, judgment, and decision-making serve as foundational models for

understanding individual actions in both economic practice (Kahneman et al., 1982) and

behavioral economics (Camerer et al., 2004). Rational explanations of thought and behavior

are crucial for our everyday understanding of one another’s actions (Bratman, 1987), play a

key role in economic and social science theories (Binmore, 2008), and form the basis of

cognitive information-processing theories (Oaksford & Chater, 2007).

In rational decision-making models, decision-makers evaluate multiple potential alternatives

across various scenarios before making a choice. They assess these scenarios based on their

probabilities, allowing them to estimate the expected outcomes for each option. The final

decision is the one that offers the most favorable expected outcome and the highest likelihood

of success - Figure 2. Rational decision-making models describe how decision-makers use a

specific set of alternatives to address problems (Hoch et al., 2001).

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Figure 2. Stages of rational decision-making

Source: Heracleous, 1994, p. 17.

Similarly, intuition is a concept with multiple definitions (Taggart, 1997). It continues to be a

vague and ambiguous phenomenon within the field of decision-making (Sinclair, 2014). Reber

(2017) characterized intuition as an innate judgment process that occurs without deliberate

thought or conscious awareness. In a similar vein, Bowers et al. (1990) defined intuition as the

recognition of patterns, meanings, and structures that are initially not consciously perceived

but ultimately guide decision-making.

Intuition can be seen as complementing rather than opposing rational analysis (Hodgkinson &

Sadler-Smith, 2003). Prior to this, Epstein et al. (1996) provided strong empirical support for

the idea that these two modes of processing are not mutually exclusive. They introduced the

concept of two distinct constructs - rationality/experience and analysis/intuition - that together

shape behavior. Today, the complementary nature of these constructs is widely recognized

(e.g. Thanos, 2022).

Decision-making in the area of sustainability

At the outset, it is worth noting that few studies have thus far focused on decision-making

models in the area of sustainable development (e.g. Zavadskas et al., 2016; Depczyński, et

al., 2023; Malik, 2024; Mai et al., 2024). For example Bolis et al. (2017) investigated how

different decision-making rationalities relate to sustainable development, aiming to understand

better how to advance a more sustainable development model. Their review encompassed

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151 studies examining the link between rationality and sustainability. The literature reviewed

uniformly stressed the necessity of moving away from the current decision-making framework,

which is largely driven by instrumental rationality - a method criticized for its excessive focus

on self-interest. The authors emphasize the importance of adopting alternative rationalities to

support sustainable development, such as: (1) substantive rationality, which involves

incorporating sustainability values into decision-making processes; (2) communicative

rationality, which fosters cooperation and coordination to achieve more sustainable outcomes;

(3) bounded rationality, which takes into account human cognitive limitations and the complex

nature of sustainability issues. Additionally, Kibert et al. (2011) present a framework aimed at

embedding sustainability principles into decision-making processes. This framework is crafted

to ensure that sustainability considerations are consistently integrated into both organizational

and project-specific decisions. It seeks to balance environmental, economic, and social factors

to secure long-term, sustainable results (Kibert et al., 2011).

Nevertheless, to the best of the authors’ knowledge, none of the existing studies have

addressed whether rational or intuitive decision-making is more effective in the area of

sustainability.

Achieving sustainability requires a balance between rigorous analysis and intuitive insight.

Rational and intuitive decision-making approaches can complement each other to produce

more effective and adaptive strategies. For example, a rational analysis provides

a structured framework essential for evaluating various sustainability options. It involves

methodical examination of data, applying quantitative tools such as cost-benefit analysis and

life-cycle assessment to evaluate environmental, social, and economic impacts. This

structured approach ensures that decisions are based on objective criteria, leading to well-

supported and justifiable outcomes. For instance, Ren et al. (2013) employed Multi-Criteria

Decision Making (MCDM) to evaluate various biomass-based technologies for hydrogen

production. They developed a framework that incorporates fifteen criteria spanning economic,

environmental, technological, and socio-political dimensions to assess sustainability. The

study analyzed four biomass-based technologies - pyrolysis, conventional gasification,

supercritical water gasification, and fermentative hydrogen production. The MCDM approach

identified biomass gasification as the most sustainable technology among the options,

recommending it for further development and implementation.

On the other hand, intuition brings valuable insights that are often crucial in complex or novel

situations where data alone may not suffice. Intuitive decision-making relies on an individual’s

or group’s accumulated experience and gut feelings, allowing for rapid judgments in scenarios

where time and information are limited. This ability to quickly navigate uncertainties and make

decisions in the face of ambiguous or unprecedented challenges can complement the thorough

analysis provided by rational methods (Menzel, 2013). In situations where quick decisions are

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necessary - such as during environmental crises or in time-sensitive projects -intuition can

provide immediate insights that help make informed choices without waiting for exhaustive

analysis.

One of the key benefits of integrating rational and intuitive methods in the area of sustainability

is enhanced flexibility. Decision-makers often face dynamic and uncertain environments where

conditions can change rapidly. Rational analysis provides a detailed examination of options,

but it may not always account for sudden shifts or emerging trends. Intuitive decision-making,

however, allows individuals to adapt quickly to changing circumstances, leveraging their

experience and instincts to navigate new challenges effectively.

By blending these approaches, decision-makers can strike a balance between thorough

analysis and the ability to respond swiftly to unforeseen developments. This adaptability is

crucial for sustainability, where the ability to pivot and adjust strategies in response to new

information or changing conditions can significantly impact the effectiveness of sustainability

initiatives.

To enhance the decision-making process in the area of sustainability, it is considered essential

to (Rudolph & Bauer, 1999; Munck & Tomiotto, 2019):

 educate people about values related to sustainability, including ethics, cooperation, and

environmental stewardship, to shape their personal choices.

 ensure accountability for decision-makers to enhance collective actions and collaborative

decision-making, especially for decisions affecting society and the environment.

 advocate for systemic reforms in the existing development model.

Conclusion

In summary, merging rational and intuitive decision-making approaches presents considerable

benefits for promoting sustainability. Rational analysis offers a structured framework and data-

driven insights, while intuition provides crucial context and swift judgment in complex

situations. The integration of these methods enables decision-makers to adopt a more

balanced, adaptable, and innovative strategy for sustainability. This combined approach

enhances the effectiveness and flexibility of strategies designed to tackle environmental,

social, and economic challenges. As global sustainability concerns intensify, utilizing both

rational and intuitive decision-making will be vital for crafting and executing successful

strategies toward a sustainable future.

As noted, there has yet to be research that simultaneously analyzes the effectiveness of

rational and intuitive decision-making in the context of sustainability. Therefore, in the future,

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the authors recommend conducting empirical studies comparing the effectiveness of rational

versus intuitive decision-making approaches. This could involve analyzing how each approach

influences decision outcomes, stakeholder satisfaction, and sustainability impacts. It is also

proposed to examine how different contexts such as industry type, geographic location, and

organizational size - affect the applicability and outcomes of rational and intuitive decision-

making approaches in sustainability. By exploring these areas, future research can enhance

our understanding of how to effectively utilize both rational and intuitive decision-making

methods to improve sustainability outcomes.

The authors hope that the presented discussion will serve as inspiration and a basis for further

research on sustainability and decision-making models.

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Speed and Timing of intuitive Decision-Making

Agnieszka Tul-Krzyszczuk

1)

, Olena Kulykovets

1)

, Barbara Wyrzykowska

1)

and

Markus A. Launer

2)

1) Warsaw University of Life Sciences, Institute of Management, Poland

2) Ostfalia University and Institut für Dienstleistungen gGmbH (non-profit organization),

Germany

Introduction

Dual-process theories have been proposed to explain human reasoning and judgment. The

central feature of these theories is the attribution of responses to two types of thinking

described either as heuristic versus analytic (Evans, 1989), associative versus rule-based

(Sloman, 1996), experiential versus analytic (Epstein, 1991), System 1 versus System 2

(Stanovich, 1999), gist versus verbatim (Reyna & Brainerd, 1995) or Type 1 versus Type 2

(Evans, 2008). There are many points of disagreement, theorists generally agree that there

are heuristic processes (Type 1) that are fast, automatic, unconscious, and require low effort

(Kahneman, 2003, Kahneman and Klein, 2009).

Dual Process Theory: Time difference between rational and intuitive decision-making

Dual-process theories differentiate between two types of cognitive processes: fast, automatic,

and intuitive (Type 1), which are more prone to errors, and slow, controlled, and deliberate

(Type 2), which are more analytical. When time constraints are tight, performance tends to rely

more on the low-effort Type 1 processes, resulting in a higher likelihood of biases

(Andrzejewska et al, 2013).

Many adult judgment biases are considered to result from fast heuristic responses, often

referred to as default responses, because they are the first thoughts that come to mind. These

fast, automatic reactions are central to Type 1 processes, a key aspect of intuitive thinking that

requires minimal cognitive effort or control (Betsch & Glöckner, 2010; Glöckner & Betsch,

2012). In contrast, Type 2 processes are characterized by their slow, conscious, deliberate,

and effortful nature, requiring significant engagement of central working memory resources.

As a result, Type 2 processes are believed to be influenced by individual differences in

cognitive capacity, whereas Type 1 processes are generally considered independent of

cognitive ability (Evans & Stanovich, 2013).

Many theories describe thinking as a combination of qualitative-heuristic and quantitative-

analytic processing. Fuzzy-trace theory, in particular, suggests that intuitive reasoning

emerges from qualitative-heuristic processes that focus on the gist or essential meaning of a

problem. In contrast, quantitative-analytic processes are detail-oriented and work with the

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precise, verbatim details of a problem. As individuals age, gain education, and practice within

a specific domain, they become more adept at extracting and processing the gist of a situation,

leading to a greater reliance on intuition. Fuzzy-trace theory, therefore, places intuition at the

highest level of cognitive development (Reyna, 2004, 2012, 2013), setting it apart from other

dual-process theories. Experts, within their area of expertise, can quickly grasp the gist of a

situation, whereas novices must rely on cognitively demanding analytic processes to handle

the exact details of the problem. While other dual-process theories attribute much of intelligent

behavior to skilled analytic reasoning, fuzzy-trace theory highlights the importance of intuitive

reasoning. It proposes that both types of reasoning occur simultaneously, with task demands

determining which type dominates behavior (Reyna & Brainerd, 1995, 2011).

Sahm and von Weizäcker (2015) examine how reason and intuition impact decision-making

over time. When dealing with a series of similar problems, individuals can choose to make

decisions rationally, following expected utility theory, or intuitively, following case-based

decision theory. While rational decisions tend to be more accurate, they also incur higher costs,

although these costs may diminish over time. The study finds that intuition can ultimately

outperform rational decision-making if individuals have enough ambition. Additionally, intuitive

decisions are more common at the early and late stages of a learning process, while rational

decision-making tends to dominate in the middle stages (Sahm & von Weizäcker, 2015).

When individuals estimate the amount of time that can be saved by increasing the speed of an

activity, they often fall prey to a time-saving bias (Svenson, 2008). This bias leads them to

overestimate the potential time savings that come from increasing speed. In the context of

driving, judgments about time savings due to speed increases tend to follow the Proportion

heuristic, which suggests that people intuitively estimate time savings based on the

proportionate change in speed rather than the actual time saved (Svenson, 1970, 2008).

Rapid Responses to Situations

Individuals in occupations that involve crisis situations, such as police officers, firefighters, and

paramedics, develop crucial decision-making habits that enable them to respond intuitively to

sudden emergencies. This ability is largely the result of extensive drill training. Through

rigorous and repeated practice, these professionals cultivate nearly automatic (intuitive)

decisions and actions, rooted in past learning and drills, so that their responses become

"second nature." Such intuitive reactions are essential in these fields, as they allow for rapid

and effective decision-making in high-pressure situations (Patton, 2003).

These intuitive responses are not unique to emergency professions; they also occur in

everyday experiences, such as recalling lyrics when hearing a melody or remembering a poem

segment in response to specific stimuli. Similar patterns are evident in sports and the

performing arts, where the ability to react accurately within split-second timing is clearly

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intuitive. This is despite the fact that thorough analysis, which leads to appropriate decisions

and actions, often involves highly complex issues that would typically require substantial time

to reach effective conclusions—time that is not available in these high-pressure situations.

During the initial stages of learning, these decisions do require significant time to process, but

with practice, they become increasingly intuitive (Patton, 2003).

Intuitive reactions are essential or highly beneficial in situations that demand sudden,

instantaneous, and accurate actions, or when the circumstances are highly complex. While

much of this intuitive ability is developed through learning and experience, there is also an

innate aspect that allows some individuals to excel beyond others, regardless of the effort

others put in (Patton, 2003).

This process of developing intuitive reasoning is evident in learning to read. It begins with the

practice of recognizing individual letters, progresses to recognizing words, and eventually

leads to the recognition of entire phrases. Over time, the ability to read evolves from slowly

piecing together letters to fluently interpreting extensive written material (Patton, 2003).

It's important to note, however, that intuitive decisions are not always made in an instant. Often,

even in decisions that are carefully thought out, there can be an intuitive component. A

decision-maker who is conscious of the influence of intuition and understands its role in

shaping choices is likely to achieve an effective balance between the careful analysis of data

and alternatives and the intuitive insights that guide decision-making. This balance is crucial

for making well-rounded decisions that benefit from both logical deliberation and instinctive

understanding (Patton, 2003)..

Unconscious Thought Theory

Dijksterhuis and Nordgren (2006) identified two distinct modes of thought: unconscious and

conscious. Each mode has unique characteristics that make it more suitable for different

situations. Contrary to common assumptions, conscious thought is more effective for making

decisions about straightforward issues, while unconscious thought tends to be more

advantageous for dealing with complex matters. This distinction highlights the different

strengths of each mode depending on the complexity of the decision at hand (Dijksterhuis and

Nordgren, 2006).

Humans often engage in extended thought processes, especially when facing significant

decisions or working on scientific discoveries, which can span months or even years.

Dijksterhuis and Strick (2016) propose that during these periods of sustained thinking,

progress is made not only through conscious deliberation but also while individuals are

consciously focused on something else—essentially engaging in unconscious thought. Their

review of the literature on unconscious thought (UT) processes reveals substantial evidence

supporting its existence. When viewed as a form of unconscious goal pursuit, UT is particularly

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effective for thought processes that are complex, significant, or personally engaging. We also

explore other characteristics of the UT process that contribute to its effectiveness in these

contexts (Dijksterhuis & Strick, 2016).

In numerous experiments, Dijksterhuis compared participants who were distracted with those

who made a decision immediately after being presented with decision-related information

(immediate decision condition), a comparison also frequently used in creativity research.

However, this comparison does not necessarily confirm the presence of an active unconscious

thought (UT) process, as distraction could simply cause participants to forget some of the

relevant information. For instance, when deciding between two job offers, distraction might

lead participants to forget trivial details while retaining crucial information. In such cases,

distracted participants might make better decisions, but this improvement wouldn't necessarily

be due to an active UT process (Dijksterhuis & Strick, 2016).

Another noted advantage of distraction is its ability to help individuals break free from fixation

on incorrect solutions (Schooler & Melcher, 1995; Smith & Blankenship, 1989). For example,

when writing, you might find yourself unable to create a satisfactory opening for a new

paragraph because you're "stuck" on a sentence that doesn't feel quite right—like a needle

stuck in a groove. Taking a short walk or having a cup of coffee can help you forget the

unsatisfactory sentence, allowing you to start fresh. However, demonstrating that distraction

leads to better outcomes than continuous, uninterrupted work on a problem does not

necessarily provide evidence of an active unconscious thought (UT) process (Dijksterhuis &

Strick, 2016).

Participants are distracted from further conscious thinking about the problem, which prevents

any potential negative impact that conscious thought might have after an initially accurate

impression—an effect some researchers believe could explain the unconscious thought (UT)

effect (Lassiter et al., 2009; Payne et al., 2008). Additionally, the potential benefits of

distraction, such as forgetting irrelevant information (Shanks, 2006) or overcoming fixation

(Smith & Blankenship, 1989), would be expected to improve performance in both groups.

However, an increasing number of studies indicate that participants in the UT condition

consistently perform better than those who are simply distracted (Dijksterhuis & Strick, 2016).

Theory on Incubation

The benefit of setting a problem aside to aid in finding solutions has been a topic of interest

among theorists for at least a century. Wallas (1926, p. 80) built on Poincaré’s (1910) earlier

exploration of mathematical creativity, identifying the stage during which a problem is not

actively thought about as “Incubation” (Gilhooly, 2016). When someone steps away from an

unsolved problem for a while, they may suddenly experience an unexpected insight into the

solution. This phenomenon is referred to as incubation (Smith and Blankenship, 1989) in

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combination with intuition and problem-solving (Dorfman, Shames & Kihlstrom, 1996; Lebed,

2017).). There is substantial evidence from laboratory studies supporting the benefits of

Delayed Incubation, which suggests that taking a break from a problem after working on it for

a while can be advantageous (Dodds et al., 2012, for a qualitative review). A quantitative meta-

analysis by Sio and Ormerod (2009) found a positive effect of Delayed Incubation (Gilhooly,

2016). The theory of incubation is mainly researched regarding Creative problem solving,

however, there is a strong connection to intuition (Gilhooly, 2016)..

According to Smith and Blankenship (1989), after an initial phase of unsuccessful attempts to

solve a problem, a person might either persist with uninterrupted work or temporarily set the

problem aside, revisiting it later. The concept of "incubation" in a laboratory setting refers to

the improved performance observed in those who return to a problem after a delay, compared

to those who work on it continuously. According to the forgetting-fixation hypothesis, during

the initial problem-solving phase, incorrect solutions may become entrenched, making correct

solutions less accessible. Over time, forgetting or reduced accessibility of these fixated

incorrect solutions can make the correct solutions more accessible, thereby facilitating the

incubation effect. (Smith & Blankenship, 1989).

There is further evidence from various types of experiments, including those focused on

incubation and problem-solving. The unconscious thought (UT) paradigm is partly rooted in

research on incubation in creativity (e.g., Wallas, 1926; Orlet, 2008). This research suggests

that taking a break or allowing thoughts to incubate can enhance problem-solving and creative

thinking, supporting the idea that UT processes can contribute to better outcomes in certain

contexts (Dijksterhuis & Strick, 2016).

Sio and Ormerod (2009) recently reviewed this body of literature and concluded that an

incubation period does indeed aid creative problem-solving. However, the moderators they

identified do not clearly indicate whether these effects are due to genuine unconscious thought

(UT)—an active cognitive process—or simply the result of other outcomes from a period of

distraction, such as forgetting irrelevant information or misleading cues, without necessitating

the assumption of an active UT process (see also Orlet, 2008; Dijksterhuis & Strick, 2016).

Orlet's (2008) review and synthesis of the literature on incubation reveals several key points:

(a) experimental studies on incubation primarily focus on observing and measuring cognitive-

mental processes; (b) current research on incubation seldom addresses the variability in

psychological states during the incubation phase, particularly when solving interpolation and

dialectic problems; and (c) sensory-perceptual phenomena, such as the formation of symbols

during incubation, are not adequately considered. The review also highlights the need for

developing methodologies that account for the full spectrum of cognitive-mental and sensory-

perceptual processes involved in fostering novel insights and original discoveries (Orlet, 2008;

Dijksterhuis & Strick, 2016).

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Smith and Blankenship (1989) proposed that during the initial stages of problem solving, the

retrieval of incorrect information and strategies from memory can obstruct the recall of the

correct information and strategies necessary for effective problem solving. Overcoming this

fixation, a key component of the incubation process, involves forgetting—or reducing the

accessibility of—irrelevant or inappropriate information, making the correct information

relatively more accessible. This overall concept is known as the forgetting-fixation hypothesis

(Smith and Blankenship, 1989).

Gilhooly outlines three primary explanations for the effects of incubation: Unconscious Work,

where problem-solving continues subconsciously; Intermittent Work, where breaks allow for

renewed focus and fresh perspectives; and Beneficial Forgetting, where time away from the

problem helps reduce fixation on incorrect solutions, making it easier to access the correct

information when returning to the task (Gilhooly, 2016).

However, there are studies in which incubation effects were not observed, such as those

conducted by Gall and Mendelsohn (1967), Dominowski and Jenrick (1972), and Olton and

Johnson (1976). Stories such as Coleridge composing the poem *Kubla Khan* in a dream,

Mozart envisioning complete compositions flawlessly, and Kekulé discovering the benzene

ring structure in a dream have been shown to be inaccurate (Weisberg, 2006, pp. 73–78).

Intuitive Decision-Making as a gradual Process: The Process of Spreading Activation

Intuition has been defined as the instantaneous, experience-based impression of coherence

elicited by cues in the environment. In a context of discovery, intuitive decision-making

processes can be conceptualized as occurring within two stages, the first of which comprises

an implicit perception of coherence that is not (yet) verbalizable. Through a process of

spreading activation, this initially non-conscious perception gradually crosses over a threshold

of awareness and thereby becomes explicable. Because of its experiential basis, intuition

shares conceptual similarities with implicit memory processes. (Zander et al, 2016)

Within this two-stage model, Bowers et al. (1990) suggest that the cognitive processes

underlying intuitive hunches are continuous rather than discrete. According to this continuity

model, intuition is viewed as a gradual process that begins with an initial, implicit perception of

a complex and ambiguous input and evolves into a more explicit understanding, where

individuals can articulate why and how certain pieces of semantic information are connected.

Over time, this sense of coherence develops implicitly. As more environmental cues suggest

a particular interpretation, these cues accumulate meaning, activating related representations

in memory (Zander et al, 2016).

To empirically examine their two-stage model of intuition, Bowers et al. (1990) designed

several experimental paradigms, including the triads task, which has since become a widely

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used tool for studying intuitive decision-making processes (Bolte and Goschke, 2005; Ilg et al.,

2007; Topolinski and Strack, 2009a,b; Remmers et al., 2014).

This model aligns with the idea that unconscious thought helps organize information. For

example, Ritter and Dijksterhuis (2014) proposed, based on their empirical findings, that during

periods of unconscious thought (such as during incubation), representations become more

organized and polarized, and memory shifts toward being more gist-based. Their results imply

that unconscious thought is a process in which disorganized information gradually becomes

more structured until a certain threshold is reached, at which point conclusions can be brought

to conscious awareness (Ritter and Dijksterhuis, 2014).

A common empirical result from studies using the triads task is that participants are notably

accurate in distinguishing between coherent and incoherent triads, even during the initial

guiding stage, where they cannot explicitly identify the common associate (CA) (Bowers et al.,

1990; Bolte et al., 2003; Bolte and Goschke, 2005; Ilg et al., 2007). The results have been

interpreted as supporting a genuine continuity in the underlying perceptual-cognitive

processing of information. This interpretation is based on the observation that semantic

processing triggered by sensory input spreads gradually, potentially converging on common

semantic nodes. Which model best describes the underlying cognitive and neural processes

taking place in the triads task remains an open research question. Thus, the intuitive

perception of semantic coherence develops gradually over time, making the continuity model

a better fit for explaining both behavioral performance and neural activation observed in the

triads task. (Zander et al., 2016).

Strategic Decision-Making and Intuition

According to Mintzberg (1994), strategy cannot be planned because it involves synthesis—a

blending of ideas and resources—while planning focuses on analysis, which entails breaking

down and examining the parts. This distinction between analytic and synthetic processes

reflects a previously discussed duality in human information processing (see Taggart and

Robey, 1981). Mintzberg (1994) describes the idea of planning strategy as an oxymoron

because it conflates two fundamentally distinct cognitive processes: analysis and synthesis

(Sinclair, Sadler-Smith and Hodgkinson, 2009).

Sinclair, Sadler-Smith and Hodgkinson (2009) describe intuition as a rapid, nonsequential

mode of information processing that incorporates both cognitive and emotional (including

somatic) elements. Khatri and Ng (2000) as well as Miller and Ireland (2005) also assume,

intuition in strategic decision-making would be fast. see, However, the nature of strategic

decision-making is, it is not fast.

Calabtretta et al. (2016) propose a three-step process for managing the tension between

intuition and rationality through paradoxical thinking. Their empirical data suggest that this

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process begins with preparing the foundation for paradoxical thinking by fostering managerial

acceptance of the contradictory elements inherent in both rational and intuitive decision-

making approaches. The next step involves developing decision-making outcomes by

integrating intuitive and rational practices. Finally, the outcomes of paradoxical thinking are

embedded within the organizational context. For each step, the model outlines a set of

practices that leverage either the intuitive or rational aspects of decision-making, which

practitioners can use to navigate this cognitive tension at different stages of the process

(Calabtretta et al., 2016). According to them, the intuitive process encompasses problem

definition, analysis, and synthesis. However, these stages occur more rapidly and are largely

non-conscious, with each stage being deeply intertwined with the others ((Calabtretta et al.,

2016). Calabtretta et al (2016) describe a paradoxon: The paradox arises from the fact that

intuition and rationality represent two fundamentally different modes of thinking, yet both are

essential for effective strategic decision-making (Lewis, 2000). the rationality–intuition tension

can stem from the one-sided focus on rationality and analytical thinking among organizational

decision makers (Cabantous & Gond, 2011; Callon, 2009).

The intuitive process occurs without deliberate, rational thought and is often accompanied by

a strong sense of certainty (see also Simon, 1987; Epstein et al., 1996; Shapiro and Spence,

1997; Sinclair et al., 2002). However, in strategic decision-making, in can be questioned if

decisions are made rapid. Razher it seems, they meant a slow intuitive decision-making

(Sinclair, Sadler-Smith and Hodgkinson, 2009).

In strategic management, intuitive processing is associated with the rapid "digestion" of

complex and ambiguous information sources, complementing—but not necessarily

replacing—rational processing (see Mintzberg, 1976; Louis and Sutton, 1991). This process

involves a non-conscious scanning of internal resources stored in long-term memory (Reber,

1989) and external cues from the environment (Klein, 1998) to identify relevant information

that fits into a "solution picture," similar to assembling a jigsaw puzzle. As the pieces start to

come together and make sense, the "big picture" suddenly emerges, often accompanied by a

sense of certainty or relief (Sinclair and Ashkanasy, 2005: 357). It is important to note that

while intuition and insight are related, they are not the same (Sinclair, Sadler-Smith and

Hodgkinson, 2009). They describe a continuum in which non-conscious cognitive processes

help interpret relevant environmental cues, match these cues with existing patterns, or detect

mismatches—such as when a decision-maker senses that something is "off" or "doesn’t feel

right" (Klein, 1998). These cognitive processes are accompanied to varying degrees by

emotional responses or affect (Sinclair, Sadler-Smith and Hodgkinson, 2009).

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Conclusion

It could be shown that intuitive decision-making is not always fast. The concept of Unconscious

Thoughts and Incubation describe a time-delayed intuitive decision-making. In strategic

decision-making, authors assume a fast-decision-making process. We argue, that strategic

decisions are never taken in short time. Therefore intuition can surely be also slow.

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Literature Study on Rational and Intuitive Decision-Making

Haseeb Khan

1)

, Muhammad Nisar Khan

2)

, Mohammad Daud Ali

3)

and Markus A. Launer

4)

1) University AWKUM, Pakistan

2) Bacha Khan University, Pakistan

3) University of Haripur, Pakistan

4) Ostfalia University and Institut für gemeinnützige Dienstleistungen gGmbH, Germany

Introduction

Today, intuition is an important decision-making theory across various disciplines, e.g

management, sociology, psychology and philosophy combined (Sinclair & Ashkanasy, 2005;

Hodgkinson et al., 2008; Dane & Prat, 2009; Hogarth, 2010) as well as in neuroscience

(LeDoux 1996; Barais et al, 2015, 2017, 2018; Craig, 2002; Damasio, 1999; Korteling and

Toet, 2020), behavioural sciences (Hodgkinson et al., 2008) para-psyachology (Bem, 2011;

Bem et al., 2015, Radin, 2017) as well as medicine and health sciences (Glatzer et al., 2020;

Chlupsa et al., 2021) or engineering and design (Cash & Maier, 2021; de Rooij et al., 2021).

Intuition is described in various ways in management (Simon, 1987; Agor, 1989; Behling &

Eckel, 1991; Shapiro & Spence, 1997; Burke & Miller, 1999; Andersen, 2000; Akinci & Sadler-

Smith, 2011; Gore & Sadler-Smith, 2011; Hodgkinson & Sadler-Smith, 2018; Cristofaro, 2019;

Sadler-Smith, 2022; Paliszkiewicz, Çetin, Launer, 2023), strategic decision-making (Wally &

Baum, 1997; Brockmann & Anthony, 1998; Hodgkinson et al., 2009a; Callabnretty et al.,

2017;), in different industries (Launer, Çetin, Svenson, Ohler, 2021), supply chain

management (Carter et al., 2017), as well as different management level (Paliszkiewicz, Çetin,

Launer, 2021).

There are many measurement studies and instruments on rational and intuitive decision-

making. However, each study uses different approaches. There is no literature study out there

yet describing all dimension. The latest literature study by Pietrzak, Launer and Svenson

(2022) is a great starting point-

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Theoretical Foundation based on existing Studies

Single Process Approaches

Rational Decision-Making

Rational decision-making is often described as an Information processing (Epstein, 1990) or

cognitive style (Messick, 1984; Riding & Rayner, 1998; Antonietti, 2003; Pachur & Bröder,

2013). Scott & Bruce (GDMS, 1995) describe the Analytical Style as a search & evaluation

process using a logic and systematic analysis and evaluation in terms of specific goals (Keen,

1974; Mitrof, 1983). This can also be based on Allinson and Hayes’ theory (1996) or Riding’s

(1997) analytic style. Burns & D`Zurilla, (PMPI, 1999) describe the rational processing style as

a structured thinking process, fact-based, goal-oriented, and evaluating alternatives based on

stress (Aldwin, 1994; Lazarus & Folkman, 1984) and problem solving (D’Zurilla & Goldfrid,

1971; D’Zurilla & Nezu, 1990, Mayde u-Olivare s & D’Zurilla, 1996).

Cools, & van den Broek (CoSI, 2007) and Pachur & Spaar (USID, 2015) describe two different

rational decision-making styles mainly based on education and experimental psychology

(Grigorenko & Sternberg, 1995; Rayner & Riding, 1997, 1998), Messick, 1984; Miller, 1987;

Hunt, Krzystofiak, Meindl, & Yousry, 1989; Riding & Cheema, 1991), perception, learning,

problem solving, decision making, communication, and creativity in important ways (Hayes &

Allinson, 1994; Kirton, 2003), field-dependent and field-independent (Witkin, Moore,

Goodenough & Cox, 1977); information processing (Shipman & Shipman, 1985), learning and

innovation (Sadler-Smith & Badger, 1998), and industrial, work, and organizational psychology

(Hodgkinson, 2003) and management (Hodgkinson & Sadler-Smith, 2003).

One dimension is the Knowing Style based on facts, details, logical, reflective, objective,

impersonal, rational, precise, methodical decisions (Allinson & Hayes, 1996; Myers &

McCaulley, Quenk, & Hammer, 2003. Miller, 1987. Riding & Cheema, 1991) which is

empirically related to the REI study (Pacini & Epstein, 1999). Cools, & van den Broek (2007)

found this style to be similar to existing conceptualizations of the analytic pole, e.g. Allinson

and Hayes’ theory (1996) or Riding’s (1997) analytic style.

On the other hand is the Planning Style described as sequential, structured, conventional,

conformity, planned, organized, systematic, routine-based (Allinson & Hayes, 1996; Miller,

1987; Riding, Cheema, 1991). The planning style is empirically related to the Adaptiveness

pole of the KAI (Kirton, 1994) and the REI study by Pacini and Epstein (1999). Cools, & van

den Broek (CoSI, 2007) mention the Creating Style based on Myers, McCaulley, Quenk, &

Hammer (2003) which was not used in this study. This style is related to existing

conceptualizations of the intuitive pole (Cools, & van den Broek (2007), such as intuition in

Allinson and Hayes’ theory (1996) or the innovativeness pole of Kirton (1994).

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Dual Process Approaches

The basic, historical approach is the dual process theory distinguishing between rational

decision-making (Deliberation) and intuition. Several frameworks in psychology assume a

dual-process (Chaiken & Trope, 1999; Epstein, 2008; Hammond, 1996; Ham & Van den Bos,

2011; Kahneman, 2011; Mukherjee, 2010; Sloman, 1996; Stanovich & West, 2000; Evans &

Stanovich, 2013; Evans, 2008; Keck & Tang, 2020). There are two perspectives within the

dual process theory: the unitary view postulates that cognition and intuition are opposite poles

of a single dimension, whereas the dual-process view proposes that they are independent

constructs (Hodgkinson et al., 2009b). There are two major studies with a dual approach that

develop scales and items.

The study Rational-Experiental Inventory (REI) by Epstein, Pacini & Norris (1998) and the new

version by Pacini & Epstein (1999) was based on the Cognitigve-Experiental Self-Theory

(CEST) by Epstein, Pacini, Denes-Raj & Heier (1996). They describe decision-making with a

Rationality Scale (Need for Cognition or Analytical-Rational Thinking) and an Intuitive-

Experiental Scale or faith for intuition. In principal, they relate to Jung (1964/1968), natural

decisions by Tversky & Kahneman (1983), automatic decisions by Bargh (1989) and Higgins

(1989), heuristic (Chaiken, 1980; Fiske & Taylor, 1991), schematic (Leventhal, 1984),

prototypical (Rosch, 1983), narrative (Bruner, 1986), implicit (Weinberger & McClelland, 1991),

imagistic-nonverbal (Bucci, 1985; Paivio, 1986), experiential (Epstein, 1983), and mythos

(Labouvie-Vief, 1990). Pacini and Epstein (1999) relate their inventory to the big five theory

researched by D. W. Fiske (1949), and later expanded upon by others, including Norman

(1967), Smith (1967), Goldberg (1981), and McCrae & Costa (1987).

They describe intuition in an Experiental Scale or faith for intuition or Intuitive-Experiental. They

describe intuition based on the so-called gut feeling, hunches, instincts, feelings, snap

judgement, heart (Buck, 1985; Leventhal, 1984; Jung, 1964/1968), deliberative-effortful-

intentional-systematic (Bargh, 1989; Chaiken, 1980; Higgins, 1989), explicit (Weinberger &

McClelland, 1991), extensional (Tversky & Kahneman, 1983), verbal (Bucci, 1985; Paivio,

1986), and logos (Labouvie-Vief, 1990).

The second key study using a dual approach is the Preference for Intuition or Deliberation

according to Betsch (2014, PID) based on Epstein et al (1996). She distinguishes into

Deliberation or Analytical and Planning (Cacioppo & Petty, 1982) and Affective Intuition (Jung,

1962; Slovic, Finucane, Peters, & MacGregor, 2001, Loewenstein, Weber, Hsee, & Welch,

2001; Myers & McCaulley, 1986; Keller et al. 2000). She bases her theory on the concept of

Interoception (Wilson & Schooler, 1991; Wilson, Lisle, Schooler, Hodges, Klaaren, & LaFleur,

1993), routinized decision making (Betsch, Haberstroh, Molter, Glöckner, 2004; Betsch,

Haberstroh, Hohle, 2002), implicit attitude formation (Betsch, Plessner, Schwieren, & Gütig,

2001), predictive behavior (Epstein, 1983), the processes, contents, and correlates of intuition

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(Hogarth, 2001); reasoning (Sloman, 1996), the context of discovery (Bowers, Regher,

Balthazard, & Parker, 1990), and behavioral interests, personality, and experiences (Langan-

Fox & Shirley, 2003).

More and more, theories view the relationship between the rationality and intuition as more

complex (Thompson et al., 2009). Krajbich et al. (2015), De Neys and Pennycook (2019) and

De Neys, (2021) show a revised dual-process models comparing fast and slow intuition. Bago

and De Neys (2017) sketch a revised dual process model in which the relative strength of

different types of intuitions determines reasoning performance. Pennycook et al. (2015)

showed a three-stage model to explain what causes analytic thinking to occur. Therefore, the

concept of rationality needs to be described more comprehensively.

On the way to a multidimensional approach of intuition

Today, researchers in the field of intuition more and more follow a multi-dimensional and

interdisciplinary approach (Shirley & Langan-Fox, Sadler-Smith & Shefy, 2007, 1996;

Cristofaro, 2019; Sinclair, 2011, 2014, 2020). Based on Dane & Pratt`s and Sinclair`s

constructs, many scholars followed developed a broader theory on intuition (Hodgkinson et al.,

2008, 2009a, 2009b; Sadler-Smith, 2010, 2015, 2016; Blume and Covin, 2011; Akinci and

Sadler-Smith, 2012, 2013, 2019; Baldacchino, 2013, 2019; Baldacchino et al., 2015; Healey

et al., 2015; Sadler-Smith et al., 2021; Okoli et al., 2021). Gore and Sadler-Smith (2011)

disaggregate intuition by discriminating between domain-general mechanisms and domain-

specific processes, primary and secondary types of intuition. Cristofaro (2020) describes in

depth an Affect-Cognitive Theory. But there is still a need for comprehensive model due to the

lack of synergies between scholars from different disciplines (Adinolfi & Loia, 2022).

Intuition is not a homogeneous concept, but a label used for different cognitive mechanisms

(Glöckner & Witteman, 2010; Hogarth, 2010; Pratt & Crosina, 2016). There were conceptual

shortcomings stemming from the tendency to ignore the philosophical heritage of intuition or

to dismiss the relevance of this heritage to contemporary theory (Osbeck, 1999, 2001).

Multi-dimensional Approaches of Intuitive Decision-Making

There are five multidimensional studies with a more detailed, structured dimensions on

intuition. Intuition according to Scott & Bruce (1995, GDMS) was decribed in four styles based

on the items by Bruce (1991). The first style is intuitive-based (Hunt et al, 1989; Harren, 1979),

based on feelings (Keen, 1973), and a learned habit (Driver, 1979; Driver et al.,1990). The

second style was dependent decisions (Harren, 1979; Phililips, Pazienza & Ferrin, 1984). This

was also described by Simon (1987) as intuition based on interpersonal interaction or women`s

intuition (Snodgrass, 1985) and lately in neurobiology (Marks-Tarlow, 2014). Later Lieberman

(2007) goes even beyond describing dependent decision based on social cognitive

neuroscience in: (a) understanding others, (b) understanding oneself, (c) controlling oneself,

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and (d) the processes that occur at the interface of self and others. The third subdimension

Avoidant was not used in this study (Driver, 1970; Behling, Gifford & Tolliver, 1980; Driver et

al, 1990). In their stiudy they found the fourth dimension called Spontaneous.

Burns & D`Zurilla (1999, PMPI) describe intuitive decision-making designed to assess a

person’s awareness and perception of his or her dominant mode of processing across stressful

situations (Aldwin, 1994; Folkman & Lazarus, 1980; Pearlin & Schooler, 1987; Carver, Scheier,

& Weintraub, 1989; Tobin et al., 1989) and the cognitive -experiential self-theory (CEST) by

Epstein (1990, 1994). The CEST theory described intuition as an experiential intuition focusing

on such qualities as the speed and 224mpulses224y of processing (minimal time and mental

effort); the reliance on feelings, vibes, hunches, and instincts) and the recall of past coping

experiences and familiar coping responses (Burns & D`Zurilla, 1999). Based on a content

analysis of the item clusters, exploratory and confirmatory factor analyses, the three factors

were named rational processing, emotional processing, and automatic processing. The

Automated Processing is described as quickly and efficiently, swiftly, aware, repetitive and

experience-based (Burns & D`Zurilla, 1999). In the literature, it was described as fast and

efficient, outside of awareness, unintentional, and uncontrolled (Bargh, 1994; Smith, 1994;

Shiffrin & Schneider, 1977) based on expertise (Carter et al., 2017). Logan (1988, 1989)

described it as an automatic memory retrieval, Bargh (1994) as a goal-dependent automaticity

and for Smith (1994) it was all about speed and efficiency. It is an immediate knowing of how

to cope based on past coping experiences (Burns & D`Zurilla, 1999). The Emotional

Processing described as instincts, feelings, vibes, gut feeling, hunches, and emotions (Burns

& D`Zurilla, 1999). People with a preferfernce to emotional processing aren more extraverted,

preferring emotional and interpersonal relationships, and are more adaptive for emotion-

focused coping, expressing emotions and seeking social support. Later Miller and Ireland

(2005) describe strategic decision making based on holistic hunches and automated expertise.

Pretz et al (2014, TintS; Denin et al., 2022) described intuitive decision-making in three

dimensions based on the literature review by Pretz & Totz (2007). Intuition has a holistic nature

of intuition (Jung, 1971; Hammond, 1996) described as knowing without being able to explain

how we know (Vaughan, 1979). The first sub dimension is Affective Intuition based on feelings

(Bastick, 1982), a feeling of certainty (Hogarth, 2001), or emotional processing (Epstein, 1998;

Bechara, Damasio, & Damasio, 2000). Affective intuition was described as body impulses incl.

heart-based, emotions, hunches (anticipation), and gut feeling decisions (Pretz et al., 2014).

The second type of intuition is Inferential Intuition (Hill, 1987) as an automated (Vaughan,

1979) and heuristical (Wescott, 1968; Forgas, 1994) type of intuition in an implicit judgmental

sense (Greenwald & Banaji, 1995). It is also described as experience-based, quick, familiar

decisions with reasoning, logic (Klein, 1998, Sternberg et al., 2001). Third type of intuition is a

Holistic Style (Jung, 1926; Hammond, 1996) or holistic mechanism (Bowers, Regehr,

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Balthazard, & Parker, 1990; Dijksterhuis, 2004; Wilson & Schooler, 1991) which was divided

by an factor analysis into a Holistic Big Picture Intuition and a Holistic Abstract Intuition (Pretz

et al., 2014). The holistic-associative view of intuition is acknowledged also by psychology

researchers (Agor, 1986; Kihlstrom, 1987; Shapiro & Spence, 1997; Betsch & Glöckner, 2010;

Glöckner & Witteman, 2010) as well as management scholars (Dreyfus & Dreyfus, 1986;

Simon, 1987; Prietula & Simon, 1989; Kahneman & Tversky, 2000) and lately by Adinolfi &

Loia (2022).

Pachur and Spaar (2015, USID) distinguish in domain-specific perspective based on previous

studies e.g. PID, REI, GDMS, CoSI, PMPI) two major dimensions. First, the quick

Spontaneous Intuition and Experience-based Style described as experienced (Boucouvalas,

1997), immediate, swiftly, quick, snap decisions, awareness, experience, repetitive decisions

and heuristics (Gigerenzer et al., 2011) by experts (Pachur, 1986 & Marinello, 2013). The

importance of experience has been researched best by Klein (1998) in his recognition-primed

decision model. Pachur and Marinello (2013) described that expert are more likely to rely on a

lexicographic heuristic, whereas the non-experts used a more complex strategy, that

aggregates across different cues (Garcia-Retamero & Dhami, 2009).

Second is the Affective Intuition based on feelings, body impulses, and hunches, inner

reactions, knowledge of human nature, life experience, gut feeling, hunches, heart (Burns &

D`Zurilla, 1999; Pretz et al., 2014; Betsch, 2014). Affective intuition is still a rather broad

descrition of many different feelings, body impulses, and moods. Therefore, this dimension on

intuition will be deepened.

New Dimensions for intuitive Decision-Making

Launer and Cetin (2023) describe new dimensions and styles in their Measurement and

Instrument Study. The new dimension will be described briefly.

Body Impulses

Different kind of feelings are a source of intuitive decision-making (Bonabeau, 2003; Burke &

Miller, 1999; Dane, Pratt, 2006; Klein, 2003; Sinclair, Ashkanasy. 2005) and relief or certitude

(Cappon, 1994; Petitmengin-Peugeot, 1999). Results of the collection of senses in the internal

state of the body (interoception or body Impulsess) from neurology and medicine (LeDoux

1996; Barais et al, 2015, 2017, 2018; Craig, 2002; Cameron, 2002; 2009; Barrett, Simmons,

2015; Khalsa, Lapidus, 2016; Damasio, 2008; Damasio, Tranel & Damasio, 1991) showed that

emotional processes guide (or bias) decision-making, e.g. in the homoestatic sensory activity

(Craig, 2002, 2009). The concept of gut feeling needs to described newly from a broad and

unspecific term to a more differentiated approach based on feelings in the stomach, colon and

the visceral sensory system (Gershon, 2001; Hooper et al, 2001: Barbosa, Rescigno, 2010;

Mayer, 2001; Arumugam et al 2011; Brandtzaeg, 2011; Cryan, Dinan, 2012; Haller,

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Hörmannsperger, 2013; Schemann, 2020). The interoception and somatic markers of the heart

beating rate influences decision-making (Schandry, 1981; Polatos, Schandry, 2004; Dunn et

al, 2007; Pollatos, Herbert, B. M., Matthias, Schandry, 2007; Garfinkel et al, 2015; Schulz,

2016) and skin arousals (Loggia, Juneau, Bushnell, 2011; Breimhiorst et al, 2011).

Anticipation

The described scales on intuition describe an affective type of decisions based on hunches

(Scott, Bruce, 1995; Pacini, Epstein, 1999; Pretz et al 2014; Pachur, Sppar, 2015). In this study

we enlarge this characteristics to an own dimension called Anticipation (Launer, XXX). The

received information in this regard comes from outside the body (Sinclair, 2011, 2014). Many

researchers try to explain atypical or paranormal decision making (Honorton, Ferrari, 1989),

anticipation of solutions, e.g. presentiments of future emotions (Radin, 2004), precognition

(conscious cognitive awareness), premonition (affective apprehension) according to Bem et

al. (2015), extrasensory perception (ESP) by Thalbourne and Haraldsson (1980) paranormal

belief and experiences (Lange, Thalbourne, 2002), or automatic evaluation (Ferguson, Zayas,

2009). In sports, the concept of anticipating future moves by people is also called heuristics

(Grush, 2004; Williams, Ward, 2007; Schultz, 2013), however it rather belonmgs to the

heuristic theory (Launer, XXX).

Unconscious Thoughts

In a study by Carlson (2008) based on the TIntS by Pretz and Totz (2007), he included the

dimension incubation based on the theory by Dijksterhuis (2004). Decisions can not only be

made fast but also after a period of time and (unconscious) reflection and activation (Bowers

et al., 1990; Waroquier et al, 2010), incubation (Wallas, 1920; Shirley & Langan-Fox, 1996),

unconscious thinking (Dijksterhuis and Nordgren (2006), distraction (Kohler, 1969), removal of

blockages (Duncker, 1945), completion of schemes (Mayer, 1996), or in intuitive step-ups

(Nicholson, 2000). Despite the many critics on the quality of the decision (González-Vallejo et

al., 2008; Srinivasan et al, 2013; Newell & Shanks, 2014; Čavojová, Mikušková, 2014; Abbott,

2015; Nieuwenstein et al., 2015) slow decision-making is the usual process in management

(Pachur & Aebi Forrer, 2013).

New Dimension Technology based Decisions

Rosak and Launer (2023) describe in their presentation and short paper the decision-making

based on new technologies. Today, decision-making is more and more performed using

Artificial Intelligence.

Modern technology has significantly transformed decision-making in companies, including the

IT industry (Selart et al., 2008). Intuitive decision-making has shifted towards a more data-

driven approach, though research on intuition and IT remains limited due to challenges in

defining and measuring intuition (Ramrathan & Sibanda, 2017). IT investment decisions are

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Page 227

often riskier than other capital investments, making decision-making a key managerial task

(Kusumawati & Subriadi, 2019). Since the 1960s, decision support systems (DSS) have

evolved, with modern technologies like dashboards and web tools enhancing decision-making

by offering advanced functionalities such as data analysis, modeling, and collaboration

(Bhargava et al., 2007). Despite these advances, early-stage technology-based service

innovations still face high failure rates (van Riel et al., 2011).

Businesses are increasingly adapting their processes, structures, and models due to rapid

advancements in digital technologies (Kraus et al., 2021). This technology revolution has made

modern tech essential in daily operations, strategies, and decision-making. Intuitive decision-

making is now shifting to a more data-driven approach, especially in the IT industry (Selart et

al., 2008). However, research on intuition and technology remains limited, partly due to

challenges in defining and measuring intuition (Ramrathan & Sibanda, 2017). IT investment

decisions carry higher risks than other capital investments, making decision-making a critical

aspect of management (Kusumawati & Subriadi, 2019).

PRISMA Literature Search

In the future, a systematic PRISMA-nabsed literatutre study will be added to this paper.

Integrated, multi-dimensional and multi-disciplinary Framework

When combing all approaches on how to measure intuition in an integrated, multi-dimensional

and multi-disciplinary framework, a rather broad definition on intuition is needed. Intuition

seems to be an unconscious, spontaneous inferential or slow decision making process based

on holistic abstract or big picture (Holistic), experience-learned heuristics, affective and

emotional feelings and body impulses, decision based on technologyperception without

awareness, environmental influences by people as well as the capability for pre-cognition

based on hunches (Launer et al., 2020).

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Analysis of Intuition Dimensions

Unconscious

Thoughts

Theory on

Personality (Book)

Literature Study

Scott &

Bruce

Pacini &

Epstein

Burns &

D`Zurilla

Cools &

van den Broek

Pretz & Totz /

Carlson

Betsch

Pachur & Spaar

Launer & Cetin

Dijksterhuis

Epstein

Bem

Thalbourne &

Haraldsson

Khan & Launer

1995

1999

2007

2007/2008 (2014)

2014

2015

2023

2004

2003

2011/2015

1980

2024

GDMS

REI

PMPI

CoSI

TIntS

PID

USID

RIDMS

UTT

CEST

Precognition

ASGS

Rational Decision Making or

deliberation in general

Rational

analytical

Rational

Processing

Deliberation

Rational, verbal

reasoning

Analytics (search & evaluation)

Rational

(Search &

Evaluation) =

analytical

Analytical Style

Planning

Cognitive Styles

(Knowing)

Knowing Style

Knowing

Cognitive Styles

(Planning)

Rational

(Planning &

Knowing Style

Planning Style

Holistic, uncritical perception and

unconscious intuition

Thinking in

abstract

terms

Holistic abstract

and holistic big

picture

Holistic Big

Pictutre

Holistic Big Pictutre

Holistic Abstract

Holistic Big Picture

Fast Decisions

Spontaneous decisions intuition

Spontaneous

Automated

Processing

Spontaneous

Experienced based inferential or

heuristical Intuition

Automated

Processing Inferential

Experience-

based

heuristically

Experiental

(Learning facts and

emotions)

Experience-based

heuristically

Emotional affective decisions (gut,

heart and skin feeling as well as

somatic markers)

Experiential Emotional

processing Affective Affective Affective Em itional Style Emitional Style

Feelings & Emotions

Intuitive incl.

Feelings &

hunches

Experiental =

feeling)

Emotional

(Feelings,

Gut feeling)

Heart Affective

(Feelings)

Feelings /Gut &

Heart) Body Impulses Bo dy Impulses

Mood

Anticipation, presentiments, pre-

cognition and pre-monition

Experiential

(Hunches) Emotional hunches Anticipation Precognition

extrasensory

perception (ESP),

psychokinesis (PK),

and life after death

(LAD).

Anticipation

Support from others or

environmental influences Dependent

Experiential

by feeling a

person is

wrong or

right

Support by

Colleagues

Support by

Colleagues

Slow unconscious thinking,

Incubation or Unconscious

Thoughts

Incubation

(Carlson)

Slow

Unconscious

Thoughts

Unconscious

Thoughts

Theory

Slow Unconscious

Thoughts

Not used dimension in our study

Avoidant

Creating Creating

Technology-based

Para-PsychologyScale Development Studies

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229

Implications

Launer, Svenson, and Cetin developed 12 dimensions to measure rational and intuitive decision-

making across various fields. Their framework includes categories such as Rational (Analytic,

Planning, Knowing), Holistic (Abstract, Big Picture), Fast (Spontaneous, Heuristic), Slow

(Incubation), Emotional decisions, and a new dimension, Anticipation (hunches). These dimensions

offer a comprehensive and independent approach to understanding decision-making.

Their findings show that the rational decision types (planning, knowing, and analytical) correlate with

each other, while affective intuition (emotions, body impulses, mood) forms a distinct, closely related

group. The often vague "gut feeling" is now better defined, with anticipation emerging as a new

dimension of intuition. The study also clarifies that fast and slow unconscious decision-making are

distinct forms of intuition, and decisions influenced by others now have greater clarity as a factor of

intuition.

Limitations and future research

The RIEHUAD approach has several limitations, necessitating caution when interpreting its findings.

These limitations include reliance on self-report measures for evaluating validity (Burns & D'Zurilla,

1999; Hodgkinson & Sadler-Smith, 2011) and the lack of a process-based description of decision-

making (Topolinski, 2011). The model overlooks contextual and environmental factors influencing

intuition (Elsbach & Barr, 1999) and fails to address instinctual dimensions (Sun & Wilson, 2014).

Additionally, interpersonal intuition, particularly in teaching and communication settings, remains

underexplored, with "teacher intuition" as a potential new dimension (Akinbode, 2013).

The study does not consider wise decision-making, a blend of rational and intuitive choices (Sadler-

Smith, 2012), nor does it assess the success or quality of decisions, as both rational and intuitive

decisions can be imperfect or ambiguous (Watkins, 1970; Burke & Miller, 1999). Furthermore, the

study does not examine decision speed or frequency, nor how much information is typically gathered

before decisions are made. While the questionnaire measured participant preferences, some

dimensions still require deeper testing through qualitative experiments.

Conclusion

This study introduces an Integrated multidisciplinary multidimensional framework based on existing,

widely accepted studies and empirical studies. They provide a comprehensive collection of all

dimensions for rational and intuitive decision-making and four additional dimensions for the

emotional decision-making style. It is usable for all kind of decision-making in the broad research

field. In the future, a PRISMA-based systematic literature study will be added to the paper.

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Latest research on the Human Gut Microbiome and the ENS System

Muhammad Umair

1)

, Mohammad Daud Ali

2)

and Markus A. Launer

3)

1) Auyub Medical College Abbottabad, Pakistan

2) University of Haripur, Pakistan, Orcid No. 0000-0001-9630-8656

3) Ostfalia University od Applied Sciences and Institut für gemeinnützige Dienstleistungen gGmbH

(independent non-profit Organization), Germany, Orcid No. 0000-0001-9384-0807

Abstract

The research in the gut-brain axis has advanced in recent years. The historic research on the ENS

system has been modernized in medical science. The historic scientific breakthrough in

understanding the interaction of the nervous system with the digestive system occurred with the

discovery of the so-called enteric nervous system (ENS) in the mid-nineteenth century Jahrhunderts.

This study is a mixed method research about the gut brain-axis and intuitive decision-making. Three

methods will be mixed: 1) systematic literature study, 2) qualitative interviews with the identified

scientists, and 3) a quantitative study on intuition in a cross-cultural study based on the results of

.Launer& Svenson, 2022 (RHIA) and Launer & Cetin, 2023 (RIDMS). This extended abstract shows

the theory so far and gives an outlook on the methodology used. As a result, the knowledge will give

a deeper knowledge about thze gut-brain-axis and intuitive decision-making

Introduction

The notion of a "gut feeling" is deeply rooted in traditional beliefs, despite lacking scientific evidence.

This idea revolves around an instinctive sense or intuition when making decisions. The concept dates

back to ancient times when the stomach was considered the primary organ responsible for intuitive

choices. Over time, this idea evolved into the phrase "gut feeling," which is now associated with

interoception—the biological process where internal organ functions influence the brain. Our actions

are shaped not only by external factors but also by internal signals. The gut plays a pivotal role in

this process, serving as the central hub for complex interactions between our genes and the immune

system's external impact on the body, making it a key organ in environmental communication

(Brandtzaeg, 2011).

The enteric nervous system (ENS), often referred to as the gut's autonomous nervous system, has

captivated scientists for over a century. True to its name, it operates autonomously, managing

complex tasks and regulating essential functions independently of external input. Simultaneously,

the ENS receives and processes a barrage of signals from various cells within the gut wall and

lumen, integrating these inputs (Annahazi & Schemann, 2020). Despite remarkable scientific

advancements in recent years that have deepened our understanding of the communication between

microbes and their hosts, the fundamental mechanisms behind the microbiota-gut-brain connection

remain elusive (Silva, Bernardi & Frozza, 2020).

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Medical Theory

Human Gut Microbiome

Our knowledge of species and functional composition of the human gut microbiome is rapidly

increasing, but it is still based on very few cohorts and little is known about variation across the world

(Arumugam et al., (2011). However, the main stream of medical research is in regards to bowel

disease (Greenblum et al., 2012), the selective entry of nutrients (digestion) the immune system

(Barbarosa & Resigno, 2010), aging (Rampelli et al., 2023), metabolic programming (Mischke &

Plösch, 2013) as well as its role in obesity and insulin resistance (Lee, Sears & Maruthur, 2020). Tan

(2023) describes the microbiota-gut-brain axis in stress and depression. Frontiers in Neuroscience,

17, 1151478. But, human individual is best described as a super-individual in which a large number

of different species (including Homo sapiens) coexist. Fasano and Flaherty, (2022) describe the gut

feelings and the microbiome in relation to our health.

The primary function of the intestine is to absorb nutrients and water from the external environment.

To ensure that the body receives the necessary energy and essential nutrients, it first requires the

secretion of various digestive enzymes and functional components, such as bile acids. This crucial

exchange with the environment leads to the intestine’s unique role as a semipermeable barrier,

distinct from other body surfaces like the skin. The intestinal mucosa acts as a highly selective

barrier, permitting the absorption of specific luminal substances (nutrients) through active transport

or passive diffusion while effectively blocking the entry of harmful agents such as viruses, bacteria,

and parasites (Haller & Hörmannsperger, 2013).

In an adult human, the gut epithelium spans an estimated surface area of about 300 m² when

considering the villi, microvilli, crypts, and folds. Although this barrier consists of only a single cell

layer, making it inherently fragile, it is safeguarded by a range of chemical and physical innate

defense mechanisms that work closely with the local adaptive immune system (Brandtzaeg, 2009a).

The healthy gut is home to an immense population of beneficial bacteria, or "symbionts," which

outnumber the body's cells by about tenfold, comprising an estimated 10¹³ to 10¹⁴ microbial cells with

a total weight of 1–2 kilograms (Neish, 2009). Numerous genes govern both the innate and adaptive

branches of the immune system. Over time, human immunogenetics have evolved to detect and

respond to "danger," shaped by the challenges of a "dirty environment," even long after the hunter-

gatherer era. Throughout this evolutionary journey, the intestinal immune system has developed two

adaptive anti-inflammatory strategies: immune exclusion, facilitated by SIgA, to control microbial

colonization on surfaces and prevent the mucosal penetration of potentially harmful agents; and oral

tolerance (Brandtzaeg, 2011b).

Hooper et al. (2001) report findings that demonstrate how this commensal bacterium influences the

expression of genes associated with several critical intestinal functions, such as nutrient absorption,

strengthening the mucosal barrier, xenobiotic metabolism, angiogenesis, and postnatal intestinal

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development. These results underscore the fundamental importance of the interactions between

resident microorganisms and their hosts (Hooper et al., 2001).

The idea that the gut and brain are intricately connected, influencing not only gastrointestinal function

but also emotional states and intuitive decision-making, is deeply embedded in our language. Recent

neurobiological research into this gut-brain interaction has uncovered a complex, bidirectional

communication system. This system plays a crucial role in maintaining gastrointestinal homeostasis

and digestion and likely impacts emotions, motivation, and higher cognitive functions, such as

intuitive decision-making. Moreover, disruptions in this communication network have been linked to

various disorders, including functional and inflammatory gastrointestinal issues, obesity, and eating

disorders (Mayer, 2011; Pandey et al., 2017; Launer et al., 2020).

The ENS System

Decades of work in animal models have demonstrated that the enteric nervous system (ENS) plays

a key role in controlling gut functions. Recent advances made it possible to extend such studies to

the ENS of man in health and even in disease. (Schemann & Neunlist, 2004; Schemann et al., 2002).

Our body is building a brain in the gut. Goldstein, Hofstra, & Burns (2013) describe the development

of the enteric nervous system (Baron et al, 2022).

The enteric nervous system (ENS), which forms the intrinsic neural network of the gastrointestinal

tract, comprises various types of neurons and glial cells. These are organized within two

intramuscular plexuses that run throughout the entire length of the gut, regulating coordinated

smooth muscle contractions and other essential gut functions (Sasselli, Pachnis, & Burns, 2012).

The enteric nervous system (ENS) is the largest and most complex division of the peripheral and

autonomic nervous systems (PNS and ANS) in vertebrates. It comprises a vast array of neurons—

comparable in number to those in the spinal cord—and features a variety of neurotransmitters and

neuromodulators similar to those in the central nervous system (CNS). The ENS is organized into

an interconnected network of neurons and glial cells, grouped into ganglia within two major plexuses

(Sasselli, Pachnis & Burns, 2012). These components create an integrated circuitry that governs

intestinal motility, fluid exchange across the mucosal surface, blood flow, and the secretion of gut

hormones. While the gut also receives extrinsic parasympathetic and sympathetic innervation, the

intrinsic neuronal circuits of the ENS are capable of generating reflexive gut contractile activity

independently of CNS input (Sasselli, Pachnis & Burns, 2012).

The neural crest origin of the enteric nervous system (ENS) was first demonstrated by Yntema and

Hammond, who found that when the vagal (hindbrain) region of the neural crest was ablated in avian

embryos, enteric ganglia did not develop along the gastrointestinal tract (Yntema and Hammond,

1954). This finding was later confirmed and expanded through studies using isotopic and isochronic

grafts of quail pre-migratory neural crest cells into chick embryos (Le Douarin, 1973).

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Basal Ganglia

The basal ganglia play a crucial role in an attentional mechanism that helps connect sensory input

to motor output in the executive forebrain. This focused attention creates an automatic link between

voluntary effort, sensory input, and the activation of sequences of motor programs or thoughts

(Brown & Marsden, 1998; Haber & Gdowski, 2005; Mink, 2003; Smith, Bevan, Shink & Bolam, 1998).

As a major neural system, the basal ganglia receive inputs from various cortical areas, process this

information, and relay it back to the cortex through connections in the midbrain and thalamus.

Although inputs to the basal ganglia originate from multiple cortical regions, including the frontal,

parietal, temporal, and limbic cortices, the feedback from the thalamus is primarily directed toward

frontal cortical areas, such as the prefrontal, premotor, and supplementary motor areas. This

thalamic feedback, similar to the cerebellar connections that ascend through the thalamus to the

primary motor cortex, integrates the basal ganglia into motor function (Gerfen & Wilson, 1996;

Heimer & Heimer, 1983).

Interoception

Contrary to the processing of external cues, such as hearing, touch, smell, and sight, interoception

is the capability of the inner body state. It involves afferent pathways that manage internal

physiological functions (Tsakiris & Critchley, 2016). Research indicates that primates have a

specialized cortical area for homeostatic afferent activity, which mirrors the body's overall

physiological condition.

This interoceptive system, connected to autonomic motor control, contrasts with the exteroceptive

system, which directs somatic motor functions. The primary interoceptive representation located in

the dorsal posterior insula generates specific and clear bodily sensations, such as pain, temperature,

itch, sensual touch, muscular and visceral sensations, vasomotor activity, hunger, thirst, and

breathlessness. In humans, this initial interoceptive activity is further processed in the right anterior

insula, forming a meta-representation that underpins self-awareness and emotional consciousness

(Craig, 2003).

Interoception impacts more than homeostatic and allostatic reflexes; it is essential for motivation,

emotion, social cognition, and self-awareness. From early development, the ongoing integration of

biological data from the body establishes the foundation for conscious awareness and the subjective

sense of being a distinct individual (Tsakiris & Critchley, 2016).

Stomach and Colon Feeling (bacteria)

The gut-brain connection

The gut-brain connection involves complex cross-communication through multiple biological

networks, including the neural network, neuroendocrine system, immune system, and metabolic

pathways, facilitating bidirectional communication between the brain and gut (Gwak & Chang, 2021;

Ma et al., 2019). Alterations in gut microbiota can impact brain physiology and cognitive functions

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(Morais, Schreiber & Mazmanian, 2021). There is increasing recognition of the gut microbiota's role

in modulating various neurochemical pathways via the highly interconnected gut-brain axis (Silva,

Bernardi & Frozza, 2020; Morais, Schreiber & Mazmanian, 2021).

Neurobiological research into gut-brain communication has uncovered a complex, bidirectional

system that not only ensures the maintenance of gastrointestinal homeostasis and digestion but also

influences affect, motivation, and higher cognitive functions (Mayer, 2011). The sympathetic and

parasympathetic nervous systems modulate intestinal functions, potentially mediating the emotion-

related changes in motor, secretory, and possibly immune activities within the gastrointestinal tract.

Sensory information in the gut is encoded through three primary mechanisms: by primary afferent

neurons, immune cells, and enteroendocrine cells. Both extrinsic and intrinsic primary afferents

contribute to multiple reflex loops designed to optimize gut function and preserve gastrointestinal

homeostasis during internal disturbances (Mayer, 2011).

Sylvia et al. (2020) indicate that the mechanisms by which short-chain fatty acids (SCFAs) might

affect brain physiology and behavior are not yet fully understood. Enteroendocrine cells (EECs),

specialized epithelial cells derived from the endoderm, are dispersed throughout the gastrointestinal

(GI) tract (Dalile, Van Oudenhove, Vervliet & Verbeke, 2019). These cells constitute the body's

largest endocrine organ and are crucial in regulating GI secretion and motility, controlling food intake,

and managing postprandial glucose levels and metabolism. EECs detect luminal content and release

signaling molecules that can enter the bloodstream to function as hormones on distant targets, act

locally on neighboring cells, or engage distinct neuronal pathways, including those involving enteric

and extrinsic neurons (Latorre et al., 2016).

The saprophytic gut microbial flora plays a crucial role in modulating the gut-brain communication

pathway, now recognized as the "microbiota-gut-brain axis." The gut microbiota is essential for

maintaining homeostasis at local, systemic, and brain levels. Numerous neuroactive molecules,

hormones, and metabolites facilitate this bidirectional communication, enabling cross-talk between

the gut and brain (Bistoletti, Bosi, Banfi, Giaroni, & Baj, 2020). The dorsal vagal complex in the

brainstem of the central nervous system (CNS) organizes vagovagal reflexes and establishes

connections between the CNS and the gut. This complex effectively links the "CNS brain" with the

"ENS brain," creating a brain-gut connectome that provides reflexive adjustments to optimize

digestion and nutrient and fluid assimilation (Powley, 2021).

The connection between the gut environment and the brain can significantly influence host mood

and behavior. While the link between gut microbiota and the brain has been recognized for some

time, recent studies have begun to uncover the mechanisms by which gut microbiota and the integrity

of the gut barrier impact brain function and behavior (Gwak & Chang, 2021). This interaction between

the microbiota and the gut-brain axis (GBA) is bidirectional, involving communication from gut

microbiota to the brain and vice versa, mediated through neural, endocrine, immune, and humoral

pathways (Carabotti, Scirocco, Maselli & Severi, 2015; Ma et al., 2019).

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Microglia, the brain's resident immune cells, play a critical role in modulating neurogenesis,

influencing synaptic remodeling, and regulating neuroinflammation by constantly monitoring the

brain's microenvironment. Dysfunction in microglial activity has been linked to the onset and

progression of various neurodevelopmental and neurodegenerative diseases. However, the complex

array of factors and signals that influence microglial behavior remains to be fully understood (Abdel-

Haq, Schlachetzki, Glass & Mazmanian, 2019).

Akyildiz et al. (2019) explore minimally invasive, heterogeneous, and externally accessible electrical

and molecular communication channels to transmit information between devices through the

Microbiome-Gut-Brain Axis (MGBA), which includes the gut microbial community, gut tissues, and

the enteric nervous system. Gut microorganisms can activate the vagus nerve, a process that plays

a crucial role in influencing brain function and behavior. The vagus nerve appears to distinguish

between non-pathogenic and potentially pathogenic bacteria, even in the absence of noticeable

inflammation, and vagal pathways can mediate signals that lead to either anxiogenic or anxiolytic

effects, depending on the nature of the stimulus (Forsythe, Bienenstock & Kunze, 2014).

Orexin-A is a key chemical mediator in the gut-brain axis, with hypothalamic orexin-A influencing

gastrointestinal motility and secretion, while peripheral orexin in the intestinal mucosa can affect

brain functions, potentially forming an orexinergic gut-brain network. Orexin-A is thought to regulate

nutritional processes, including short-term food intake, gastric acid secretion, and motor activity

during the cephalic phase of feeding. Additionally, orexin-A is linked to stress systems and

responses, particularly through its interaction with the hypothalamic-pituitary-adrenal (HPA) axis

(Mediavilla, 2020).

Skin Feeling

Interoception and Skin Feeling

The C-tactile(CT) affernts in hairy skin, which respond to the slightest of touch like cares, have

attracted attention in the literature. This is skin-mediated interoceptive processes similar to pain and

tactile pleasures (Crucianelli & Morrison, 2023). In order to investigate the brain underpinnings of

mindfulness, touch, and interoception, Casals-Gutierrez & Abbey's research (2020) studied MRI

operations researches to thoroughly understand the underpinnings of brain’s interoception, touch,

and mindfulness which revealed that there may be some possible regions where these modalities

interconnect. Skin-mediated signals like pain, temperature, and affective touch have been redefined

as interoceptive (Crucianelli & Ehrsson, 2023). Neurophysiology and functional neuroimaging

suggest that social, affective touch is a prominent category of tangible experience, operating mainly

in social interactions and relationships, and playing a role in physiological regulation during stress

and challenges (Morrison, 2016).

Touch can safeguard detrimental physiological effects of maladaptive reactions. Inter-individual

touch can sack negative affect while evoking strong moods of pleasure, though context and internal

state can alter the hedonic value of touch (Ellingsen et al., 2016). While hostile somatosensations

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remain well-characterized in terms of peripheral signaling, pleasant tactile sensations may be

mediated by specialized peripheral tactile afferents like C-tactile fibers, which respond to light and

slow stroking and are related only in hairy skin (Vallbo et al., 1999; Löken et al., 2009; Zaman et al.,

2020). Soviet studies of interoceptive conditioning found it to be unconscious, slower to establish,

and more resistant to extinction than exteroceptive conditioning (Uno, 1970).

Interoception and Heartbeat

Individuals with having clearer perception of heart activity exhibit superior levels of momentary

emotional experiences, such as anxiety, and score higher on traits like emotional capability. This

facet of cardiac consciousness focuses on heartbeat perception (Schandry, 1981). Non-invasive

measures of heartbeat detection accuracy are frequently used to index interoceptive sensitivity

(Brener & Ring, 2016). Interoception focusing on heart has received certain attention owing its role

in decision-making, clinical disorders and emotional experience like depression and anxiety (Schulz,

2016). Schulz's meta-analysis revealed an extensive network linked to heart-focused interoceptive

attentiveness, which includes the posterior insula, precentral gyrus, right claustrum, and medial

frontal gyrus.

The right-hemispheric dominance highlights the processing of non-verbal information, with the

posterior insula serving as the primary gateway for cardioception. Increased heart-focused

interoceptive accuracy correlates with heightened emotional intensity, improved memory, and more

adaptive decision-making (Garfinkel et al., 2013; Werner et al., 2009).

Paulus & Stein (2010) suggested that interoception essentially cause anxiety and mood disrders.

The claim has been strengthened by the work of (Domschke et al., 2010) who related anxiety

disorders to interoception whereas Wiebking et al. (2010) termed depression the outcome of lack of

interoception. Interoceptive signals can be harmful, and confusing for those people who are under

panic disorders, adding to their difficulties to make intuitive decisions (Wölk et al., 2014).

Anticipation - Information from outside the body

Paranormal Beliefs

Research has shown a positive link between belief in the paranormal and various psychopathological

outcomes, including higher rates of psychiatric disorders, depression, and manic symptoms

(Thalbourne and Storm, 2019; Liu et al., 2021; Dag, 1999; Peltzer, 2002; Thalbourne and French,

1995). The "psychodynamic functions hypothesis" (Irwin, 2009) suggests that these beliefs help

impose order on a chaotic world, alleviating uncertainty by providing meaning or an illusion of control

(Irwin, 1993, 2003, 2009). This process involves "magical ideation," defined as "belief in forms of

causation that by conventional standards are invalid" (Eckblad and Chapman, 1983, p. 215), often

serving as a coping mechanism for those who feel powerless (Ofori et al., 2017; Drinkwater et al.,

2019). McGarry and Newberry (1981) noted that individuals with paranormal beliefs tend to see the

world as unjust and unpredictable (Roe and Bell, 2016; Stone, 2016).

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While paranormal beliefs might offer a sense of control and adaptive benefits in certain situations

(Schumaker, 1987; Dean et al., 2021; Parra and Giudici, 2022), they are generally associated with

poorer psychological functioning and increased distress. Despite this, paranormal beliefs are

widespread in non-clinical populations, as a 2005 Gallup poll found that three-quarters of Americans

held at least one paranormal belief (Moore, 2005; Irwin et al., 2012a). In general populations, these

beliefs are usually benign unless combined with cognitive distortions, which can influence how

individuals interpret their experiences (Irwin et al., 2012a,b; Drinkwater et al., 2021). This perspective

suggests that supernatural beliefs reflect rather than determine mental states, impacting well-being

indirectly through cognitive-perceptual factors (Irwin, Dagnall & Drinkwater, 2013).

Radin, a senior scientist at the Institute of Noetic Sciences, demonstrated the ability to anticipate

future events through physiological responses such as skin resistance and pupil dilation (Radin,

2004a; Radin & Borges, 2009). Meta-studies, examining up to 90 experiments, confirm these effects,

showing that individuals’ responses can be influenced by future stimuli, a phenomenon known as

precognition (Bem, 2011; Bem et al., 2015; Mossbridge et al., 2014, 2015). Humans constantly and

automatically evaluate their environment, which can trigger adaptive responses (Ferguson & Zayas,

2009).

Psi phenomena, including ESP, telepathy, clairvoyance, and precognition, can function without

conscious awareness, facilitating adaptive outcomes (May & Marwaha, 2015). The "Psi-mediated

Instrumental response" (PMIr) model predicts that psi operates unconsciously to trigger preexisting

behaviors in response to environmental opportunities or threats (Hitchman, 2012; Hitchman, Roe,

Sherwood, 2012a, 2012b).

Recent studies suggest that paranormal belief helps individuals cope with stress and is linked to

higher emotional intelligence (EI) (Irwin, 1992; Dudley, 2002). Rogers et al. (2006) explored how

coping strategies predict, and EI moderates, belief in the paranormal. A study by Rattet and Bursik

(2001) found that while extraversion and intuition are linked to precognitive experiences, paranormal

beliefs are more associated with dissociative tendencies.

Anticipation, though underexplored in business and psychology, is a key concept in sports

psychology, as seen in research on soccer goalkeepers (Schulz, 2013). Meta-analyses show that

anticipation of future events is possible and can influence behavior, as demonstrated by retroactive

avoidance of negative stimuli (Bem, Tressoldi, Rabeyron & Duggan, 2016; Roe, Grierson & Lomas,

2012; Maier et al., 2014). Poli (2017) emphasized anticipation as a valid research topic, exploring

how systems use future information in decision-making processes. Anticipation, categorized into

explicit (conscious) and implicit (unconscious) forms, plays a crucial role in understanding

anticipatory behavior and its potential risks and benefits (Poli, 2017; Adams et al., 2009; Miller,

2018). Self-referential cycles in anticipatory systems are distinguished as either incomplete or

complete, with incomplete systems requiring external interpretation (Poli, 2018).

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Conclusion

The extended abstract shows the latest literature on the gut-brain-axis and intuitive decision-making.

It describes the methodology used for a deeper study.

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Literature Study on the Avoidance of Decision-Making

Atiq Khattak

1)

, Mohammad Daud Ali

1)

and Markus A. Launer

2)

1) University of Haripur, Pakistan, Orcid No. 0009-0009-3454-2338 and 0000-0001-9630-8656

2) Ostfalia University and Institut für gemeinnützige Dienstleistungen gGmbH (Independent non-

profit Organization), Germany, Orcid No. 0000-0001-9384-0807

Extended Abstract

Introduction

The decision-making styles study by Scott and Bruce (1995) is the only tool that includes the

avoidance of decision-making. They outlined four decision styles based on previous theories and

research, defining them behaviorally: (a) the rational style involves a comprehensive search and

logical evaluation of alternatives, (b) the intuitive style relies on instincts and emotions, (c) the

dependent style seeks advice and guidance from others, and (d) the avoidant style tries to evade

making decisions.

Their research showed a negative correlation between rational and avoidant decision-making styles

in both military officers and students, aligning with Phillips et al. (1984), who concluded that rational

decision-makers tend to face problems rather than avoid them. However, unlike Phillips et al.'s

(1984) finding that dependent decision-makers were just as likely to avoid problems as rational or

intuitive ones, this study found that dependent decision-makers were more inclined to avoid

decisions, supporting Harren's (1979) view that dependent decision-makers tend to be passive and

avoidant.

The avoidance of decisions as a decision-making style is lacking attention in the field if decision-

making (Launer & Cetin, 2023). This extended abstract / short paper describes this decision-making

style in detail.

Theoretical Foundation based on existing Studies

Decision Avoidance Result from Reason and Emotion.

Multiple research studies have explored why individuals often avoid making decisions by delaying

action, failing to act, or sticking to the status quo. This review connects findings from various fields

and identifies four key decision avoidance effects: choice deferral, status quo bias, omission bias,

and inaction inertia. These effects are explained through a rational-emotional model, which highlights

factors that lead to decision avoidance. Key elements of this model include cost-benefit analysis,

anticipated regret, and difficulty in selecting an option. Additional factors influencing decision

avoidance, such as negative emotions, decision strategies, counterfactual thinking, and preference

uncertainty, are also discussed.

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Avoidance and Decision Making in Anxiety

While the intense dread and apprehension associated with severe anxiety can cause significant

personal distress, it is often the excessive avoidance behaviors that lead to the greatest impairment.

These behaviors prevent individuals from engaging in social activities, walking in public, or

addressing their emotions. Similarly, in obsessive-compulsive disorder, the distress caused by

obsessions is compounded by avoidance behaviors like checking, rituals, and compulsions, which

interfere with normal life. Additionally, while fear itself is not typically life-threatening, avoidance can

be—such as when fear of flying leads to driving long distances (despite flying being safer) or when

avoiding painful thoughts results in harmful drinking (Beckers & Craske, 2017).

Despite the central role of avoidance in anxiety and other clinical conditions, its study has not

consistently garnered attention throughout the history of psychological science. Although avoidance

learning was a key focus during the behaviorist era, interest significantly declined with the rise of

cognitive psychology, leading to decades of limited theoretical progress in understanding avoidance,

despite its recognized importance in clinical psychology. However, in recent years, there has been

a resurgence of interest in avoidance behavior, with a significant increase in empirical and theoretical

research over the past decade (Krypotos et al., 2015). This revival has brought more sophisticated

theoretical analyses and a deeper understanding of both the behavioral and neurobiological aspects

of avoidance in both normal and clinical contexts (Krypotos et al., 2015; LeDoux et al., 2017; Beckers

& Craske, 2017).

The decline in interest in avoidance research may be partly due to the complex relationship between

fear and avoidance. Early theories, such as Mowrer’s (1951), emphasized the role of fear in the

development and persistence of avoidance. However, more recent conceptual and empirical findings

have challenged this, showing that fear and avoidance do not always align. Fear can occur without

avoidance, and avoidance can take place without visible fear. Consequently, fear learning research

has often focused on other areas, like Pavlovian conditioning. Nonetheless, avoidance remains

central to the impact of clinical anxiety, and understanding its nature and the decision-making

processes behind it is essential for improving clinical interventions (Beckers & Craske, 2017).

Recent theories have expanded on Mowrer's two-factor theory, highlighting the role of threat

expectations (Lovibond et al., 2008), occasion setting (De Houwer et al., 2005), Pavlovian influences

(Krypotos et al., 2014), and habit formation (LeDoux et al., 2017) in shaping avoidance behavior.

These developments help clarify the connections and distinctions between fear, defensive

responses, and avoidance. The articles in this special issue of *Behaviour Research and Therapy*

offer a comprehensive overview of current research on avoidance and suggest future directions for

both basic science and clinical applications concerning avoidance behavior and decision-making in

anxiety (Beckers & Craske, 2017).

In their opening article, Arnaudova et al. (2017) explore various pathways through which avoidance

can escalate into excessive behavior, commonly seen in anxiety and related disorders. Drawing on

findings from animal studies and experimental cognitive psychology, they discuss mechanisms that

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contribute to excessive avoidance and propose potential clinical interventions to help reduce it. In

another review, Kirlic et al. (2017) suggest that the key to understanding avoidance behavior lies not

just in avoidance tendencies but in the conflict between approach and avoidance drives, along with

the resulting dysregulated decision-making. They present basic animal paradigms and their human

adaptations to study this conflict, highlighting the underlying neurobiological mechanisms. Treanor

and Barry (2017) offer a compelling theoretical analysis of how avoidance behavior is sustained

through associative fear learning and extinction. They emphasize the different roles avoidance can

play and suggest behavioral and pharmacological strategies, particularly in combination with

exposure therapy, to address avoidance in clinical anxiety. These approaches warrant further

investigation in future studies (Beckers & Craske, 2017).

The remaining papers in this special issue present empirical findings that offer new insights into the

relationship between fear and avoidance. Echoing Kirlic et al. (2017), Rattel et al (2017) and

Bublatzky et al. (2017) demonstrate that approach incentives can reduce avoidance behavior in the

lab, whether avoidance stems from instructed threats or experientially acquired fears. These findings

suggest that approach incentives may disrupt the cycle of avoidance, which typically blocks exposure

to fear-reducing information and reinforces continued avoidance (Beckers & Craske, 2017).

Ng and Lovibond (2017) highlight the role of threat expectations in maintaining avoidance by showing

that the intention to avoid is as effective as actual avoidance in reducing anticipatory arousal. This

supports the expectancy theory of avoidance, which has gained prominence as a new theoretical

framework (Lovibond et al., 2008; Krypotos et al., 2015).

Vervliet et al. (2017) offer an innovative perspective by proposing that feelings of relief reinforce

avoidance behavior and that dysregulated relief processing may contribute to excessive, habit-like

avoidance. Meanwhile, Xiu et al. [this issue] emphasize the importance of individual learning

histories, showing that the persistence of avoidance during threat extinction depends on the initial

reinforcement rate of avoidance (Beckers & Craske, 2017).

Finally, Hunt et al. (2017) provide evidence that individual differences in distress tolerance and

coping strategies, such as suppression or distraction, influence when fear responses lead to

deliberate avoidance, especially in response to generalized threats.

This refines a theoretical understanding of avoidance in anxiety and offer practical, testable

suggestions for improving the clinical management of avoidance behaviors (Beckers & Craske,

2017).

Decision Making In Avoidance–Reward Conflict

Decision-making in humans is shaped by the anticipation of rewards and punishments, but how

these two factors interact remains unclear. The Avoidance–Reward Conflict (ARC) Task is a novel

paradigm designed to explore this interaction. It varies the level of reward and the likelihood of

punishment within a single framework, making it applicable to both non-human primates (NHPs) and

humans (Sierra-Mercado et al., 2025).

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The ability to seek rewards while avoiding danger is a fundamental trait shared across species. Both

animals and humans can learn to associate certain stimuli with either rewarding or aversive

outcomes. Extensive research on the behavior and neurobiology of reward and fear in both animals

and humans (Phelps and LeDoux 2005; Schultz 2006) suggests similarities in the brain circuits

involved. Studies on non-human primates (NHPs) show that the amygdala is crucial for fear and

avoidance learning (Weiskrantz 1956), a finding echoed in human neuroimaging, where the

amygdala is activated during fear learning and exposure to negative stimuli (Irwin et al. 1996; LaBar

et al. 1998). For reward processing, NHP studies indicate that neurons in the ventral striatum

respond to expected and received rewards (Apicella et al. 1991a, b; Schultz et al. 1992), while similar

findings in humans using PET and fMRI further confirm the ventral striatum's role in reward

processing (Elliott et al. 2000; Delgado et al. 2000). Dopaminergic neurons in the midbrain, part of

the basal ganglia, are also vital for reward processing in both NHPs (Mirenowicz and Schultz 1994)

and humans (Drevets et al. 2001; Boileau et al. 2003). These findings demonstrate that NHPs are a

valid model for studying the neuroanatomy and physiology underlying normal behaviors (Sierra-

Mercado et al., 2025).

Decision-making in both animals and humans is shaped by the anticipation of reward and

punishment. For instance, classic human experiments show that people often delay immediate

rewards in favor of larger future rewards (Mischel and Metzner 1962), and that the likelihood of

punishment influences choices (Mischel and Grusec 1967). Similar effects of reward magnitude

(Schultz 2000, 2006) and threat risk (LeDoux 2012) have been observed in animals, indicating that

both factors play a key role in guiding decisions. However, the neurobiology of reward and fear has

mostly been studied separately. To better understand how these elements are integrated during

decision-making, there is a need for paradigms that can be applied to both non-human primates

(NHPs) and humans (Sierra-Mercado et al., 2025).

In the ARC task, both non-human primates (NHPs) and humans can differentiate between varying

levels of reward and aversion. Interestingly, both species display a similar behavior: they

overwhelmingly choose the reward when the risk of punishment is low. Regardless of whether the

reward is small, medium, or large, the likelihood of selecting the reward exceeds 90% for both NHPs

and humans when the punishment risk is minimal. However, as the risk of punishment rises (medium

aversion), smaller rewards are more likely to be rejected in favor of a safer, punishment-free option

(Sierra-Mercado et al., 2025).

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Roles of Uncertainty Avoidance and Long-versus Short-Term Orientation on

Decision Making Style a Literature Study

Fatih Çetin

1)

, Markus A. Launer

2)

and Burcu Tosun

3)

1) Baskent University, Turkiye, Orcid No. 0000-0002-2487-9553

2) Ostfalia University of Applied Sciences and Institut für gemeinnützige Dienstleistungen (non-

profit Organization), Germany, Orcid No. 0000-0001-9384-0807

3) Atilim University, Turkiye, Orcid No. 0000-0002-8030-7066

Abstract

This study examines how cultural dimensions, particularly uncertainty avoidance and long- versus

short-term orientation, influence intuitive decision-making styles in a German sample. Drawing on

theories from cross-cultural psychology and decision-making research, we explore the effects of

these cultural values on rational, holistic, inferential, and emotional decision-making styles. Data

were gathered from 491 German participants through a detailed survey measuring cultural values

and decision-making preferences. Results show that high uncertainty avoidance is associated with

a lower preference for holistic and emotional decision-making. Furthermore, a long-term orientation

is positively linked to analytic decision-making, while a short-term orientation aligns with emotional

and inferential decision-making. These findings highlight the role of cultural context in shaping

decision-making approaches and provide valuable insights for improving decision-making

effectiveness in multicultural settings. Practical implications for organizational practices and

suggestions for future research are also discussed.

Keyword: Uncertainty avoidance, Long-term orientation, Short-term orientation, Decision making

styles, Germany

Introduction Long- versus Short-term Orientation

Culture is defined as "the collective programming of the mind which distinguishes the members of

one human group from another" (Hofstede, 1980, p. 25). Beyond individual traits, human dispositions

and behaviors are shaped by the norms, beliefs, and values of their cultural context (Triandis, 1989).

Additionally, cultural values influence not only behavior but also how individuals perceive themselves

and their social environment (Triandis, 1989). While Hofstede's model is widely recognized, there

are several other significant theories of culture, such as the GLOBE research project and Schwartz's

framework (1994). The GLOBE study (House et al., 2004) provided valuable insights by measuring

culture both in terms of respondents' values (the "should be" dimension) and their perceptions of

how their culture addresses collective challenges (the "actually is" dimension).

According to Hassan et al. (2011), the marketing and management literature has been heavily

debated about the structure of culture, its measurement, and its impact on behavior (e.g., Dwyer et

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259

al., 2005; Kirkman and Shapiro, 2001; Kirkman et al., 2006; Riordan and Vandenberg, 1994; Zhang

et al., 2008). Hofstede (1980) made a significant contribution to this field by developing a theory of

culture that includes four dimensions and creating a method for measuring cultural orientation. This

framework was later expanded to include a fifth dimension, now known as long-term orientation

(LTO) (Hofstede, 2001).

There are numerous definitions and theoretical frameworks across disciplines that examine the

influence of time (see Hirschman, 1987, for a comprehensive review). The two most notable

approaches to understanding time perceptions are those developed by Hofstede (1980, 2001) and

Hall (1959, 1983). Hall's framework distinguishes between polychronic time (a relationship-oriented

perspective) and monochronic time (a unidimensional focus on a single aspect), and this concept

has been further developed to encompass eight distinct types of time.

Many more researchers have researched the temporal frames using words like extended time

horizon (Zellweger, 2007), long-term focus (Narver & Slater, 1990), long-term horizon (James, 1999),

managing for the long run (Miller & Le Breton-Miller, 2005), and long-term orientation (LTO;

Chrisman & Patel, 2012; Gomez-Mejia, Haynes, Nunez-Nickel, Jacobson, & Moyano-Fuentes, 2007;

Zahra, Hayton, & Salvato, 2004).

Introduction Uncertainty Avoidance

Uncertainty is a crucial contextual factor influencing the decision-making processes of multinational

corporations across various types of international operations. According to Sniazhko (2019), the

diverse ways in which uncertainty has been defined and analyzed in the international business

literature have led to a fragmented understanding of multinational corporations behavior and the

impact of uncertainty on international decision-making. Taking a broad perspective on uncertainty,

he conducts a systematic review of the literature to explore how uncertainty is addressed in

international decision-making and to suggest potential directions for future research. He identifies

13 dimensions of uncertainty and eight approaches to managing it (Sniazhko, 2019).

Lipshitz and Strauss (1997) explored three key questions in their research: How do decision-makers

conceptualize uncertainty? How do decision-makers cope with uncertainty? Are there systematic

relationships between various conceptualizations of uncertainty and the different strategies used to

cope with it? The results revealed that decision-makers differentiate between three types of

uncertainty: inadequate understanding, incomplete information, and undifferentiated alternatives

(Lipshitz & Strauss, 1997). Based on their results and insights from earlier studies on naturalistic

decision-making, they hypothesized that heuristic decision-making plays a crucial role. This

approach outlines the strategies decision-makers use to address different types of uncertainty in

real-world settings (Lipshitz and Strauss, 1997).

The interactions between Uncertainty Avoidance and Decision-making is extensive, however the

differentiation in rational and intuitive decision-making is very limited. This needs to be better

understood. In this paper we discuss these relationships and give suggestions on its measurement

for empirical studies.

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Long-term orientation

Venaik, Zhu and Brewer (2013) examined the use of the construct long-term orientation in the

business and management literature.

Long-term orientation by Hofstede

The dimension of long- versus short-term orientation, initially identified by Bond in a study involving

students from 23 countries, was later incorporated by Hofstede as the fifth dimension of national

cultures (Hofstede, 1991; Hofstede & Minkov, 2010).

Hofstede's (2001) Long-Term Orientation (LTO) dimension was initially identified in the Chinese

Culture Connection (1987) study, which was conducted in response to concerns that cultural

questionnaires typically created by Western scholars might be biased by a Western perspective. To

address this, a survey was specifically designed to identify and measure Chinese cultural values

(and their corresponding dimensions) across various countries. While three of the resulting

dimensions aligned with those in Hofstede's original survey, one dimension, termed Confucian Work

Dynamism, did not match any in Hofstede's framework. Consequently, it was added as a new

dimension to his model. Hofstede later decided to rename this dimension to Long-Term Orientation

(LTO) for various reasons (Venaik, Zhu, & Brewer, 2013).

Hofstede (2001) distinguished between short-term orientation and LTO at the national level.

Hofstede's measurement of cultural values has faced criticism from several researchers due to its

lack of robust psychometric properties (Spector et al., 2001), assumptions of unidimensionality

(Bearden et al., 2006b; Gouveia et al., 2003), and its applicability at the individual level (Bearden et

al., 2006b). To address these limitations, Bearden et al. (2006a) proposed a new LTO scale that

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conceptualizes LTO as a two-dimensional construct, allowing it to be measured at the individual level

(Hassan et al., 2011).

Hofstede et al., (2008) also researched the micro-dynamics of trust in a trade relationship, focusing

on one dimension of culture only.

Source Venaik, Zhu and Brewer (2013)

Long-term Orientation by GLOBE

The publication of the GLOBE study has prompted renewed scholarly interest in exploring the nature

of national culture dimensions, particularly those outlined by Hofstede and GLOBE (Brewer and

Venaik, 2010; Maseland and Van Hoorn, 2010; Taras et al., 2010). This development provides

scholars with an opportunity to compare and contrast aspects of both models to either support or

challenge our understanding of national culture. Such comparisons are already appearing in the

literature, including a series of papers by GLOBE and Hofstede themselves that examine their

respective models (Hofstede, 2006; Javidan et al., 2006), as well as an analysis of the uncertainty

avoidance dimension in both frameworks (Venaik and Brewer, 2010). Tung and Verbeke (2010)

advocate for further research in this area, highlighting various important issues to enhance the quality

of cross-cultural research. In their comprehensive review of cross-cultural organizational behavior

research, Tsui et al. (2007, p. 462) emphasize the "critical need for a consolidation of different

cultural frameworks and their measurement." They argue that "the fundamental concept of culture

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262

has not been systematically examined, nor has there been a thorough evaluation of the many cultural

frameworks with overlapping dimensions and inconsistent measurements" (Tsui et al., 2007, p. 460).

There was significant confusion regarding the equivalence of the two dimensions, as reflected in the

differing opinions of their respective authors. Hofstede argues that the dimensions are the same

(Hofstede, 2006), while the GLOBE study maintains that they are distinct (Ashkanasy et al., 2004).

Venaik, Zhu and Brewer (2013) compared the scale by Hofstede and tze GLOBE study:

Source Venaik, Zhu and Brewer (2013)

Long-term orientation in dyadic relationships by Ganesan

Ganesan (1994) examined the role of LTO in dyadic relationships between buyers and sellers. A

retailer's long-term orientation is the perception of interdependence of outcomes in which both a

vendor's out- comes and joint outcomes are expected to benefit the retailer in the long run (Kelley

and Thibaut 1978).

Marketing managers need to understand a customer's time orientation to choose and apply

marketing strategies that align with the customer's time horizons. A lack of understanding in this area

can lead to problems, such as using relationship marketing strategies when transactional marketing

would be more suitable. Ganesan (1994) suggests that a long-term orientation in a buyer-seller

relationship depends on two key factors: mutual dependence and the degree of trust between the

parties (Ganesan, 1994).

Retailers with a short-term orientation are concerned only with the options and outcomes of the

current period, whereas retailers with a long-term orientation focus on achieving future goals and

are concerned with both current and future outcomes.

A. Retailer's long-term orientation

1. We believe that over the long run our relationship with this re- source will be profitable.

2. Maintaining a long-term relationship with this resource is im- portant to us.

3. We focus on long-term goals in this relationship.

4. We are willing to make sacrifices to help this resource from time to time.

5. We are only concerned with our outcomes in this relation- ship. (R)

6. We expect this resource to be working with us for a long time.

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7. Any concessions we make

Long-term orientation by Bearden

Based on a time-focused understanding of long-term orientation (LTO), Bearden et al. (2006a, p.

457) defined LTO as "the cultural value of viewing time holistically, appreciating both the past and

the future, rather than prioritizing actions solely for their immediate or short-term effects." According

to this definition, a high LTO score would indicate that an individual values planning, tradition, hard

work, and perseverance for future benefits (Hassan et al., 2011).

Long-term orientation (LTO) is a significant component of national cultural values, influencing

consumers' decision-making processes. This article outlines the development and validation of a

scale to assess LTO. The scale development process led to a two-factor, eight-item measure

capturing the tradition and planning dimensions of LTO. A series of studies with over 2,000

participants from four different countries demonstrated the scale's psychometric properties, including

its discriminant and convergent validity, as well as its relationship with other key theoretical concepts,

such as consumer frugality, compulsive buying, and ethical values. The measures are suitable for

examining individual differences in LTO both within and across different cultures (Bearden et al.,

2006).

Bearden et al. (2006a) began by generating and refining items while assessing content validity. They

then conducted a series of six empirical studies to evaluate the scale's dimensionality, reliability

(including test-retest reliability), measurement invariance, as well as its convergent, discriminant,

predictive, and nomological validity (Hassan et al., 2011).

According to Bearden et al. (2006), the measurement is:

Please describe your personal orientation

1. I consider traditions to be important

2. Respect for traditions is important

3. Family’s cultural heritage is important

4. I value connections to the past

5. I work hard to obtain future success

6. I find it reasonable to give up the fun in exchange for an improved future condition

7. I think it's important to be persistent

8. I plan for a long- term future

Hassan et al. (2011) noted that while the LTO scale developed by Bearden et al. (2006a) showed

consistent results across different country samples, there is still a need for an independent evaluation

of the scale's psychometric properties and validity across a broader range of countries. Bearden et

al. (2006a) specifically validated their scale in three non-European countries and in Austria,

representing the European Union (EU).

Although Bearden et al. (2006a) included two application studies in their research, empirical studies

examining the correlates of long-term orientation (LTO) remain limited (Taras et al., 2010). Previous

research indicates that culture significantly affects attitudes and behaviors (e.g., Luna et al., 2002;

Miller, 1984; Morris and Peng, 1994; Singh et al., 2006; Taras et al., 2010). Additionally, following

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the value-attitude-behavior hierarchy proposed by Homer and Kahle (1988), there is evidence to

suggest that cultural values are indeed correlated with attitudes (Hassan et al., 2011).

A multi‐country Assessment of the long‐term Orientation Scale by Hassan et al.

Hassan, Shiu and Walsh (2011).find the the scale by Bearden et al. 82006) is recommended for

measuring LTO, though with caution. According to them, additional research is necessary to further

distinguish between the two subscales: tradition and planning. Measuring and gaining a deeper

understanding of cross-cultural differences in customers' LTO can help overcome challenges in

effectively marketing products and services across diverse cultural settings (Hassan et al., 2011).

The Relationship between long-/short-term Orientation and intuitive Decision-Making

There are numerous relationships and interactions between time and decision-making (Ariely &

Zakay, 2001), making it challenging to provide a comprehensive summary of this topic. In this paper,

we will explore several aspects where time and decision-making are intertwined: (a) temporal

perspectives of decisions —the different time orientations decision-makers may adopt and how these

perspectives influence the decision-making process and its outcomes; (b) time as a medium—the

characteristics of decision processes that unfold over time; (c) time as a resource and contextual

factor—the effects of limited time resources and deadlines on decision-making processes and

performance; (d) time as a commodity—where time itself becomes the subject of decision-making

(Ariely & Zakay, 2001),

There have been only a few studies that explore intuition from a cultural and cross-cultural

perspective. Wu (2020) investigated the phenomenon of intuitive decision-making within the asset

management sector by conducting in-depth semi-structured interviews and administering self-

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265

reported cognitive tests among experienced professional fund managers from both China and

Western countries (Wu, 2020).

Khan et al. (2021) examined the impact of heuristic biases, specifically availability bias and

representativeness bias, on investors' decision-making in the Pakistan Stock Exchange. They also

explored the moderating effect of long-term orientation on these investment decisions. They

concentrated on two of the most frequently encountered heuristic-driven biases in decision-making:

availability bias and representativeness bias (Tversky and Kahneman, 1973). These biases were

chosen because their influence on investment decisions extends beyond just common investors;

even professional and experienced investors are susceptible to these heuristic biases (Tversky and

Kahneman, 1974).

 The availability heuristic is a cognitive bias where investors tend to rely on information that

is most readily available to them when assessing an investment opportunity, while

disregarding other potential sources of information. This inclination can lead to irrational

behavior, ultimately impacting investment performance (Folkes, 1988).

 The representativeness heuristic involves the tendency of individuals to interpret a specific

characteristic as representative of the entire subject, regardless of whether that

characteristic is actually relevant to the subject (Khan et al., 2017). According to DeBondt

and Thaler (1995), representativeness is a cognitive shortcut that reflects the extent to

which an event resembles its parent population. This heuristic describes the inclination to

make judgments about a social phenomenon based on stereotypes.

Pixley (2009) examined the behavior of financial firms with a focus on "temporality" and the

corresponding "emotion-rules," noting that variations in these rules align with organizational

definitions of uncertainty. Firms enforce specific emotion-rules based on national policies, official

responsibilities, and interpretations of each type of risk. In the finance sector, the principle of *caveat

emptor* (buyer or lender distrust) serves as an emotion-rule embedded in screening policies and

data collection procedures to assess credit risks and potential fraud by staff, which can evoke

genuine emotions. Pixley (2009) argues that three time-orientations—past, present, and long-term

future—play crucial roles in shaping emotion-rules. These orientations influence how institutions

construct and frame their strategies to manage uncertainty. Pixley (2009) argues that emotion-rules

and time perspectives are essential in the financial sector because every task is inherently oriented

toward the future. Money, as a social relation extending into the future, is rooted in the structure of

debt, which introduces a higher level of uncertainty than the basic fiduciary duties of banks might

imply. Money is generated through lending and can diminish sharply when bankers experience

panic.

Previous research suggests that time perspective (TP)—the way individuals view the past, present,

and future—is linked to decision-making style. However, no prior study has explored the relationship

between time perspective and decision-making competence. To address this gap, Rönnlund et al.

(2019) examined the associations between the dimensions of the Swedish Zimbardo Time

Perspective Inventory (S-ZTPI) and performance on the Adult Decision-Making Competence (A-

DMC) battery in a sample of older adults.

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Theory Uncertainty Avoidance

Uncertainty and its influence on decision-making is a significant topic that has garnered extensive

research attention within international business studies over the past five decades (Sniazhko, 2019).

Uncertainty, defined as the lack of knowledge regarding the probabilities of future events (Knight,

1921), has been shown to impact various aspects of multinational corporations' operations, including

their speed of international expansion, internationalization strategies, entry mode decisions, and

levels of commitment (e.g., Aharoni, 1966; Aharoni, Tihanyi, & Connelly, 2011; Ahsan & Musteen,

2011; Johanson & Vahlne, 1977; Liesch, Welch, & Buckley, 2011). Because decision-makers cannot

completely eliminate uncertainty, this limitation affects the effectiveness of their decisions,

necessitating the use of strategies to either reduce uncertainty or manage it more effectively.

Today's managers are increasingly required to make decisions using paradigms that differ from

traditional rationality and information-processing models. This is especially true in crisis situations,

where there is limited time and information for evaluating choices. This could be seen as an

Uncertainty. While recent management literature has provided more empirical and theoretical

support for the use of intuition and tacit knowledge in decision-making, the role of emotion has not

been as prominently featured (Sayegh, Anthony & Perrewé, 2004).

To encourage greater consistency in the conceptualization of uncertainty dimensions in future

research, Sniazhko (2019) adopts Miller's (1992) classification of uncertainty. Miller's framework

includes 13 dimensions of uncertainty, which are grouped into three categories: environmental

uncertainty, industry uncertainty, and firm-specific uncertainty. This describes different kind of

Uncertainties in a literature study. The following tables describe these categories as a basis for

further research.

However, Ahnert & Suntrayuth (2015) had difficulties to draw the correlation uncertainity avoidance

and dimension on decision-making in a study comparing Thai and German culture.

Uncertainty Avoidance and Intuition

Sayegh, Anthony & Perrewé (2004) describe management decision theory by introducing a

conceptual model of managerial decision-making that highlights the significance of emotions in the

intuitive decision-making process during crises (Sayegh, Anthony & Perrewé, 2004).

Ahnert and Suntrayuth (2015) compare the results of one of the most common culture models from

Hofstede for the two research relevant countries, Thailand and Germany. The dimension of

uncertainty avoidance reflects the extent to which members of a society feel uneasy in unstructured

situations that are new, unfamiliar, surprising, or unconventional. Germans tend to show a moderate

preference for uncertainty avoidance, being rule-oriented and favoring deductive thinking when

presenting or planning. In line with their low power distance culture, German employees are

expected to justify their decisions independently rather than relying on their superiors' broader

responsibilities (Hofstede, 2001). In contrast, Thai people exhibit a higher need to avoid uncertainty

compared to many other nations (Andrews & Siengthai, 2009). They seek to minimize uncertainty

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by adhering to strict rules, laws, policies, and regulations. Thai society prefers maintaining control to

prevent unexpected situations and is generally resistant to change and risk (Hofstede, 2001; Ahnert

& Suntrayuth, 2015).

Money and Crotts (2003) examine how the cultural dimension of uncertainty (or risk) avoidance is

related to information search behavior, trip planning time horizons, travel party characteristics (such

as group size), and trip specifics (like length of stay). The findings reveal that consumers from

cultures with higher levels of uncertainty avoidance tend to rely on information sources associated

with specific channels, such as travel agents, rather than personal contacts, destination marketing

materials, or mass media. These consumers are also more likely to book prepackaged tours, travel

in larger groups, have shorter stays, and visit fewer destinations on average. Interestingly, contrary

to what might be expected, they do not spend more time deciding to travel or booking their airline

tickets (Money & Crotts, 2003).

The aim of Money and Crotts (2003) is to investigate how culture influences the process and

outcomes of external information search and specific purchase decisions. The cultural dimension

they focus on is Hofstede's (1980) concept of uncertainty avoidance, which measures a society's

tolerance for risk. This dimension is highlighted because previous research has shown it affects

information search behavior (Dawar, Parker, & Price, 1996; Money & Crotts, 2003).

Mmolotsa, G. K. (2022) describes the effect of Uncertainty Avoidance on the relationship between

intuitive decision-making style and take-the-best heuristic use (intuition) in Employee Selection; a

doctoral thesis from Botswana. Bate (2022) describes the nexus between Uncertainty Avoidance

culture and risk-taking behaviour in entrepreneurial firms’ decision-making.

Measuring Uncertainty Avoidance

According to Hofstede uncertainty avoidance can be measured as:

Please describe how you deal with uncertainty

1. It is important to have instructions spelled out in detail so that I always know what I’m

expected to do.

2. It is important to closely follow instructions and procedures.

3. Rules and regulations are important because they inform me of what is expected of me.

4. Standardized work procedures are helpful.

5. Instructions for operations are important.

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Measuring rational and Intuitive Decision-Making

There are different measurement instruments that describe rational and intuitive decision-making

styles. The following list givesd an overview.

 CEST = Cognitive-Experiential Self-Theory (Epstein, 1994)

 REI = Rational Experiential Inventory (Pacini & Epstein, 1999);

 PMPI = Perceived Modes of Processing Inventory (Burns & D’Zurilla, 1999);

 GDMS = General Decision Making Style inventory (Scott & Bruce, 1995);

 PID = Preference for Intuition and Deliberation scale (Betsch, 2004),

 CoSI = Cognitive Style Indicator (Cools & Van den Broeck, 2007).

 TIntS = Types of Intuition Scale (Pretz et al, 2014)

 USID = Unified Scale to Assess Individual Differences in Intuition and Deliberation (Pachur

and Spaar, 2015)

 BEM = Feeling the future (Bem et al., 2015)

 RHIA = Rationality Heuristic Intuition Anticipation (Launer and Svenson, 2022)

 RIDMS-E = Rational and intuitive Decision-Making Style (Launer and Cetin, 2023)

The different measurement instruments measure rational and intuitive decision-making styles in a

dual process approach or three to four different dimensions. The most complete approach is

described by Launer and Cetin (2023). This approach is briefly described here:

To what extend which you would agree that that statement is true for you at your current job? from

1-Definitely false to 5-Definitely true

Analytical

1. Before I make decisions, I usually think carefully first.

2. Instead of acting on the first idea that comes to mind, I carefully consider all my options.

3. I make decisions in a logical and systematic way

Planning

4. I like detailed action plans

5. Following a clear plan in very important to me

6. A good task is a well-planned task

Knowing

7. I study every problem until I understand the underlying logic

8. I enjoy solving problems that require hard thinking

9. I prefer complex problems to simple problems

Holistic unconscious

10. I use my general thought of whole rather the details when to decide

11. Before I decide, I try the understand the big picture of the problem

12. I always use big picture perspective when to decide

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Spontaneous

13. I generally make snap decisions

14. I make quick decisions

15. I typically figure out the way to decide swiftly

Heuristic

16. I make decisions based on my knowledge of human nature.

17. I make decisions based on my life experience.

18. I’ve had enough experience to just know what I need to do most of the time without trying to

figure it out every time

Slow unconscious

19. When I make decisions, I always sleep over it for a night.

20. Over time, I process many different influences on my decision.

21. I usually set aside enough time to think things through carefully and figure out what is the be

thing to do.

Emotional

22. Feelings play a big role in my decisions.

23. I follow my feelings when deciding.

24. Emotions are usually more useful than thoughts for coping.

Body impulses

25. When I make a decision, I trust my inner body feeling and somatic reactions

26. I prefer drawing conclusions based on my feelings, my knowledge of human nature, and my

experience of life

27. I tend to use my gut feeling for my decisions

Mood

28. When I have to take decisions, I feel afraid and/or curiosity in me

29. When I have to make decisions, I feel anger and/or serenity inside me.

30. When I have to decide I feel anger and/or relief in me

Anticipation (Pre-Cognition)

31. I have a premonition of what is going to happen.

32. I can foresee the outcome of a process.

33. I foresee how to decide before I review all aspects

Support by others

34. I need assistance of other people when making important decisions

35. If I have support by others, it is easier for me to make important decisions

36. I like to have someone to steer me in the right direction when I am faced with important

decisions

Later, the authors took out the dimensions body impulses and mood from the inventory.

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Conclusion

There is not much literature on intuitive decision-making and uncertainty avoidance and Long-versus

Short Term orientation in the literature. More studies need to be undertaken to further explore the

connection. In this study we show a brief overview of the literature and draft an inventory on how to

measure uncertainty avoidance and Long- versus Short term orientatiuon in connection with rational

and intuitive decision-making.

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Developing a Concept of Measuring Rational and Intuitive Decision-Making in

China

Marcus T Anthony

1)

, Bo Aquila Yang

2)

and Markus A. Launer

3)

1) Beijing Institute of Technology, China, Orcid No. 0000-0003-0211-2770

2) Beijing Open University, China

3) Ostfalia University of Applied Sciences & Institut für gemeinnützige Dienstleistungen (non-profit

Organization), Germany, Orcid No. 0000-0001-9384-0807

Extended Abstract

Intuition theory has been a subject of extensive research across various disciplines, including

management, sociology, psychology, philosophy, neuroscience, behavioral sciences,

parapsychology, medicine, health sciences, and engineering (Hodgkinson and Sadler-Smith, 2003;

Sinclair & Ashkanasy, 2005; Dane & Prat, 2009; Hogarth, 2010; LeDoux, 1996; Barais et al., 2015;

Craig, 2002; Damasio, 1999; Hodgkinson et al., 2008; Bem et al., 2015; Radin, 2017; Glatzer et al.,

2020; Chlupsa et al., 2021; Cash & Maier, 2021; de Rooij et al., 2021). However, there is no

consensus on its conceptualization and measurement due to its nonconscious nature and the

intricate interactions between cognition and affect.

Intuition is a multifaceted concept that has been defined and studied differently across disciplines

(Anthony, 2008). In management and psychology, it is often described as a rapid, nonconscious,

and holistic decision-making process (Hodgkinson and Sadler-Smith, 2003; Dane & Prat, 2009). In

philosophy, intuition refers to immediate knowledge or insight without conscious reasoning (Sinclair

& Ashkanasy, 2005). In neuroscience, intuition is associated with the fast and automatic processing

of information in the brain (LeDoux, 1996). Parapsychology explores intuition as extrasensory

perception or psychic abilities (Bem et al., 2015; Radin, 2017). The measurement of intuition also

varies across disciplines. In behavioral sciences, researchers have developed scales to assess

intuitive decision-making styles (Hodgkinson et al., 2008). In medicine and health sciences, intuition

is often examined through clinical judgment and diagnostic accuracy (Glatzer et al., 2020; Chlupsa

et al., 2021). Engineering studies focus on intuitive problem-solving and design processes (Cash &

Maier, 2021; de Rooij et al., 2021). The lack of a unified conceptualization and measurement of

intuition across disciplines poses challenges for interdisciplinary research and limits the

comparability of findings. It is crucial to develop a comprehensive understanding of intuition that

integrates various perspectives and establishes common frameworks for its study. Such efforts

would enhance collaboration and knowledge exchange among different scientific fields, leading to a

more holistic understanding of intuition and its practical applications.

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The purpose of this paper is to present the preliminary report on the upcoming paper: “Developing a

Concept of measuring Rational and Intuitive Decision-Making in China – a Concept Study,” written

and conducted by the authors of this presentation. The primary aim of this presentation is to present

the project, its aims and current point of progress, including intentions for conducting and analysing

survey data from China.

This study is designed to introduce an integrated multidisciplinary, multidimensional framework

based on existing, widely accepted studies, with the intention to comprehensively collect data which

incorporates both rational and intuitive decision-making; with four additional dimensions used to

assess the emotional decision-making styles. An important component of the study is to assess the

influence of Chinese culture and history in the expression of these cognitive modalities. It is hoped

that the findings can be used in further studies of decision-making in China.

This paper aims to develop a comprehensive measurement instrument, by combining and dividing

styles from various fields and proposing new styles. The twelve styles proposed are Analytic,

Planning, Knowing, Holistic Unconscious, Spontaneous, Heuristic, Slow Unconscious, Emotions,

Body Impulses, Moods, Anticipation, and Support by Others. Analytic style involves logical

evaluation of alternatives, Planning style is sequential and structured, Knowing style relies on factual

knowledge, Holistic Unconscious style integrates diverse information in a non-analytical manner,

Spontaneous style emphasizes quick decision-making, Heuristic style is experiential and automatic

learning, Slow Unconscious aligns with Unconscious Thought Theory, Emotions style relies on

feelings, Body Impulses style relies on gut feelings, Moods style considers the influence of positive

and negative moods, Anticipation style relies on hunches, and Support by Others style involves

seeking advice.

Another primary aim of the research project is to further understandings regarding whether intuitive

decision making may be different in China compared to other countries and cultures. The intention

is to explore cultural and historical impacts. Therefore, a preliminary component of this project is to

identify the historical role of intuition in several of China’s most important philosophical and spiritual

traditions. The first is Daoism, including the impact of Lao Zi, Zhuang Zi and Wang Bi (Godard, 2014;

Schipper, 1994). The second is Buddhism, most notably impact of the Lankavatara Sutra (Red Pine,

2012); Asvaghosha (Hakeda, 1967); and Zhiyi (1984). Finally, the influence of Confucianism on the

expression of Chinese intuition is identified (Graham, 2001). The impact of such ideas and practices

upon ways of knowing, embodiment shall be explored, as well as the cultivation of wise decision-

making, the practice of virtue, and alignment with the dao (道,the way or path) and qi (气, vital

energy). In Daoist and Confucian traditions, cultivating and refining shen (神, spirit, including

enhanced spiritual consciousness) is essential for developing then intuitive mind. Practices which

can enhance intuition include meditation, mindfulness and self-cultivation, with the aim of quieting

the mind, harmonising inner energies, and connecting with the deeper wisdom of shen. This deep

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connection is seen to enhance intuitive perception, and thus enable a higher dimension of knowledge

than that which can purely be obtained via rationality.

The legacy of these historical aspects will be then traced to assess their impact on current Chinese

society, potentially spanning business, economy, politics and leadership. The purpose of this

conceptual study is based on the methodology of Launer and Cetin (2023), with 12 different types of

decision-making styles: Analytical, Knowing, Planning, Holistic, Spontaneous, experienced-based

Heuristics, Affective (feelings) like Emotions, Body Impulses, Mood as well as Anticipation,

Unconscious Thinking and the Dependence on colleagues. Where necessary, the study may add

additional categories for unique Chinese decision making styles. This concept combines the different

approaches on intuition by CEST, GDMS, REI, PMPI, TIntS, PID, and USID. The goal is to create a

multidimensional, multidisciplinary measurement instrument which fits Chinese culture. The

expected outcome of this study is to establish a new basis for measuring intuition in China.

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A new Dimension on Research based on Hunches, Pre-cognition and Pre-Monition:

a Scale Development Study based on Literature on Anticipation

Mohammad Daud Ali

1)

, Natsuko Uchida

2)

and Markus A. Launer

3)

1) University of Haripur, Pakistan, Orcid No 0000-0001-9630-8656

2) Ferris University, Japan

3) Ostfalia University of Applied Science and Institut für gemeinnützige Dienstleistungen (non-profit

Organization), Germany, Orcid No. 0000-0001-9384-0807

Abstract

The models and measurement instruments on intuition today cannot yet describe all the phenomena

of intuitive decision-making behavior. In recent years, numerous new approaches have been

developed, e.g. based on empathy and translational symmetry, pre-monition, paranormal belief,

hunches or anticipation. Often these para-psychological approaches cannot be scientifically

differentiated from coincidence. In this study, numerous studies will be summarized under the term

anticipation (anticipative Intuition). Intuition based on anticipation is still in the beginning of research.

In intuition measurement instrument, anticipation was included many times as one item called

Hunches. However, this is not just one question but a research universe itselve.

The purpose of this theory and literature paper is to lay a theoretical foundation for intuition research

based on theories about anticipation and sample inventories such as thze Anormalous Experience

Inventory, the Sheep Goat Scales, Bems Feeling Future, the Paranormal and Supernatural Beliefs

Scale, then study on Paranormal belief and well-being and the Survey of Scientifically Unaccepted

Beliefs. The methodology is a systematic literature study and a sort of a meta analysis based on a

prisma methodology. The result is a foundation for future research on intuition. In Item Selection

Studies and measurement instruments, the intuitive decision-making style intuition should be always

included as an own dimension.

Introduction

The models on intuition today cannot yet describe all the phenomena of intuitive decision-making

behavior. In recent years, numerous new approaches have been developed, e.g. B. based on

empathy and translational symmetry (Heinle, 2016).

Poli (2017) described as seeing and researching the future. Anticipation explores the question of

how different kinds of systems anticipate, and examines the risks and uses of such anticipatory

practices (Poli, 2017; Adams et al, 2009). Anticipation is a ‘Futures Literacy’ as a tool to define the

understanding of anticipatory systems and processes (Miller, 2018). Anticipation is a widely studied

phenomenon within a number of different disciplines, including biology and brain studies, cognitive

and social sciences, engineering and artificial intelligence. There is a need for relying on at least two

different levels of analysis, namely anticipation as an empirical phenomenon and the idea of an

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anticipatory system or the study of the internal structure that a system should possess so that it can

behave in an anticipatory fashion (Poli, 2017). It is also called Sensing the future (Blaikie & Priest,

2019; Schwarzkopf, 2014; Subbotsky, 2013). But also feeling the past (Traxler et al, 2012).

In intuition measurement instruments intuition is described in scales as an affective type of decisions

based on hunches (Scott, Bruce, 1995; Pacini, Epstein, 1999; Pretz et al 2014; Pachur & Spaar,

2015). In this study we enlarge this characteristics to an own dimension called Anticipation (Launer,

2020). The received information in this regard comes from outside the body (Sinclair, 2011, 2014).

Many researchers try to explain atypical or paranormal decision making (Honorton & Ferrari, 1989),

anticipation of solutions, e.g. presentiments of future emotions (Radin, 2004), precognition

(conscious cognitive awareness), premonitionor (affective apprehension) according to Bem et al.

(2015) or anomalous cognition (Bem, 2003), extrasensory perception (ESP) by Thalbourne and

Haraldsson (1980) paranormal belief and experiences (Lange, Thalbourne, 2002), or automatic

evaluation (Ferguson, Zayas, 2009).

Paranormal Beliefs

Studies have reported positive correlations between belief in the paranormal and psychopathological

outcomes (Thalbourne and Storm, 2019; Liu et al., 2021). These include, but are not restricted to,

greater incidence of psychiatric (Dag, 1999; Peltzer, 2002), depressive (Thalbourne and French,

1995), and manic (Thalbourne and French, 1995) symptoms. A commonly cited explanation for these

associations is the psychodynamic functions hypothesis (Irwin, 2009). This proposes that

paranormal belief arises from personal attempts to impose order on the world. Belief in this context

resolves uncertainty by providing meaning and/or the illusion of control (Irwin, 1993, 2003, 2009).

Central to this process is magical ideation, which denotes “belief in forms of causation that by

conventional standards are invalid” (Eckblad and Chapman, 1983, p. 215). Magical ideation often

functions as a coping strategy when individuals believe they lack power (Ofori et al., 2017;

Drinkwater et al., 2019). Consistent with this supposition, McGarry and Newberry (1981) reported

that paranormal believers have a generalised tendency to view the world as unjust, problematic, and

unpredictable (Roe and Bell, 2016; Stone, 2016).

The notion that paranormal belief can in some circumstances provide a sense of control implies that

credence performs an adaptive function (Schumaker, 1987; Dean et al., 2021; Parra and Giudici,

2022). This, however, this is not necessarily the case since psychological benefits are typically

restricted to specific situations (Roe and Bell, 2016). Thus, paranormal belief generally signifies

poorer psychological functioning and is indicative of heightened distress. Though there is scholarly

evidence to support this proposition, it is inconsistent with the high levels of paranormal endorsement

(credence, experience, and ability) observed in non-clinical populations (see Dagnall et al., 2016c;

Williams et al., 2021). This is evidenced by surveys, which report that paranormal belief is common

within contemporary Western societies. For instance, a 2005 Gallup poll (Moore, 2005) found that

three in four Americans acknowledged at least one paranormal belief (Irwin et al., 2012a).

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Recognising the prevalence of paranormal beliefs, it is reasonable to conclude that within general

samples supernatural credence, in the absence of concomitant cognitive-perceptual characteristics,

has a benign (non-threatening) effect on well-being. Thus, paranormal belief is only problematic

when it interacts with psychological factors, which distort perception and mentation (Irwin et al.,

2012a,b). In such instances, paranormal belief may serve as an interpretative lens that structures

cognitions (Drinkwater et al., 2021). This supposition suggests that supernatural credence is

indicative, not determinative of mental state. From this perspective, paranormal belief has only an

indirect effect on well-being via its associations with cognitive-perceptual factors (Irwin, Dagnall &

Drinkwater, 2013).

Radin follows a scientifically well-based explanatory model. He who works as a senior scientist at

the Institute of Noetic Sciences (Radin, 2004a; Radin & Borges, 2009). In various experiments he

was able to prove that people can anticipate the future by measuring skin resistance (lie detector

principle) (Radin, 2004a) and the dilation of pupils (Radin & Borges, 2009).

Recent meta-studies that examined a total of up to 90 experiments and studies with anticipation

(Bem et al., 2015) confirm the effects measured by Radin (Mossbridge et al., 2014; Mossbridge et

al., 2014 and 2015). An individual’s cognitive and affective responses can be influenced by randomly

selected stimulus events that do not occur until after his or her responses have already been made

and recorded, a generalized variant of the phenomenon traditionally denoted by the term

precognition (Bem, 2011; Bem et al, 2015).

Humans continuously evaluate aspects of their environment (people, objects, places) in an automatic

fashion (i.e., unintentionally, rapidly). Such evaluations can be highly adaptive, triggering behavioral

responses away from threats and toward rewards in the environment. Even in the absence of

immediate threats and fleeting rewards, the ability to automatically evaluate aspects of the

environment enables individuals to effortlessly make sense of their world without depleting limited

and valuable cognitive resources (Ferguson & Zayas, 2009).

Psi generally falls into two categories: gathering information from the environment and interaction

with the environment. The former is usually described as ESP, remote viewing, telepathy,

clairvoyance and precognition (May & Marwaha, 2015). The proposition that psi is operative not as

an anomaly but as a normative component of information processing was investigated, focusing on

the normative operation of precognition - called automatic evaluation (Ferguson & Zayas, 2009). the

notion that psi may be able to function without conscious intent and mediate adaptive consequences

is a feature of several theories of psi. In particular, stanford’s “Psi-mediated Instrumental response”

(PMIr) model predicts that psi can operate without conscious awareness, facilitating advantageous

outcomes by triggering preexisting behaviours in response to opportunities or threats in the

environment (Hitchman, 2012; Hitchman, Roe, Sherwood, 2012a and 2012b).

Latest research suggests that belief in the paranormal serves as a mechanism for coping with stress

(Irwin, 1992) and that it is positively associated with high emotional intelligence or EI (Dudley, 2002).

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Therefore, Rogers et al (2006) examinied the extent to which coping strategy predicts, and EI

moderates, belief in the paranormal.

Do individuals who endorse paranormal beliefs differ from those reporting actual precognitive

experiences? A study showed that Extraversion and intuition were associated with precognitive

experience, but not with paranormal belief; dissociative tendencies were related to paranormal belief,

but not precognitive experience (Rattet & Bursik, 2001).

Anticipation has not yet been extensively treated in business administration, psychology and other

sciences. The term comes more from sports psychology. V. m. anticipating moves. The latest work

on this is about the anticipation of soccer goalkeepers by Florian Schulz from the University of

Tübingen (2013). In their meta-analysis “Feeling the future: A meta-analysis of 90 experiments on

the anomalous anticipation of random future events (National Institutes of Health” (2016), Bem,

Tressoldi, Rabeyron and Duggan describe that anticipation is fundamentally possible. Roe,

Grierson,and Lomas (2012) showed two independent replication attempts as well. Maier et al (2014)

showed retroactive avoidance of negative stimuli.

Poli (2017) described as seeing and researching the future. He establishes anticipation of the future

as a legitimate topic of research. It examines anticipatory behavior, id est a behavior that 'uses' the

future in its actual decisional process. Anticipation violates neither the ontological order of time nor

causation. Anticipation explores the question of how different kinds of systems anticipate, and

examines the risks and uses of such anticipatory practices (Poli, 2017; Adams et al, 2009).

Anticipation is a ‘Futures Literacy’ as a tool to define the understanding of anticipatory systems and

processes (Miller, 2018).

Anticipation comes in many different guises. The simplest distinction is between explicit and implicit

anticipation. Explicit anticipations are those of which the system is aware. Implicit anticipations, by

contrast, work below the threshold of awareness. Anticipatory systems show forms of impredicativity,

that is the presence of self-referential cycles in their constitution. The main distinction within self-

referential systems is between incomplete and complete forms of self-reference. Logical forms of

self-reference are typically incomplete because they need an external interpreter (Poli, 2018).

Anticipation in Sports

Anticipation has become an increasingly important research area within sport psychology since its

infancy in the late 1970s. Early work has increased our fundamental understanding of skilled

anticipation in sports and how this skill is developed. With increasing theoretical and practical insights

and concurrent technological advancements, researchers are now able to tackle more detailed

questions with sophisticated methods. Despite this welcomed progress, some fundamental

questions and challenges remain to be addressed, including the (relative) contributions of visual and

motor experience to anticipation, intraindividual and interindividual variation in gaze behaviour, and

the impact of non-kinematic (contextual or situational) information on performance and its interaction

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with advanced kinematic cues during the planning and execution of (re)actions in sport (Loffing &

Cañal-Bruland, 2017).

In sports, the concept of anticipating future moves by people is also called heuristics (Grush, 2004;

Williams, Ward, 2007; Schultz, 2013), however it rather belongs to the heuristic theory (Launer,

2020). However, sports will not be investigated. It can be believed, that anticipation in sports is mainly

based on experience-based and trained heuristics.

Results

Meta Analysis

There are meta level analysis on all king of research regarding anticipation (Nadin, 2010).

A meta-analysis of all forced-choice precognition experiments appearing in English language

journals between 1935 and 1977 was published by Honorton & Ferrari (1989). Their analysis

included 309 experiments conducted by 62 different investigators involving more than 50,000

participants. Honorton and Ferrari reported a small but significant hit rate, Rosenthal effect size z/√n

= .02, Stouffer Z = 6.02, p = 1.1 × 10-9. They concluded that this overall result was unlikely to be

artifactually inflated by the selective reporting of positive results (the so-called file-drawer effect),

calculating that there would have to be 46 unreported studies averaging null results for every

reported study in the meta-analysis to reduce the overall significance of the database to chance

(Honorton & Ferrari, 1989).

A review and meta-analysis of methodological and subject variables influencing the exposure–affect

relationship was performed by Bornstein (1989). It was on studies of the mere exposure effect

published in the 20 years following R. B. Zajonc's (see record 1968-12019-001) seminal monograph.

Stimulus type, stimulus complexity, presentation sequence, exposure duration, stimulus recognition,

age of subject, delay between exposure and ratings, and maximum number of stimulus presentations

all influence the magnitude of the exposure effect. Implications of these findings are discussed in the

context of previous reviews of the literature on exposure effects and with respect to prevailing

theoretical models of the exposure–affect relationship (Bornstein, 1989).

Across 7 experiments (N = 3,289), Galak et al (2012; Galak & Meyvis, 2011) replicate the procedure

of Experiments 8 and 9 from Bem (2011), which had originally demonstrated retroactive facilitation

of recall. We failed to replicate that finding. We further conduct a meta-analysis of all replication

attempts of these experiments and find that the average effect size (d = 0.04) is no different from 0.

We discuss some reasons for differences between the results in this article and those presented in

Bem (2011)

The presentiment effect has now been demonstrated using a variety of physiological indices,

including electrodermal activity, heart rate, blood volume, pupil dilation, electroence philographic

activity, and fMRI measures of brain activity. A meta-analysis of 26 reports of presentiment

experiments published between 1978 and 2010 yielded an average effect size of 0.21, 95% CI =

[0.13, 0.29], combined z = 5.30, p = 5.7 × 10-8. The number of unretrieved experiments averaging

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a null effect that would be required to reduce the effect size to a trivial level was conservatively

calculated to be 87 (Mossbridge et al., 2012; see also, Mossbridge et al., 2014). A critique of this

meta-analysis has been published by Schwarzkopf (2014) and the authors have responded to that

critique (Mossbridge et al., 2015).

The meta analysis by Bem et al (2015) report a meta-analysis of 90 experiments from 33 laboratories

in 14 countries which yielded an overall effect greater than 6 sigma, z = 6.40, p = 1.2 × 10 with an

effect size (Hedges’ g) of 0.09. A Bayesian analysis yielded a Bayes Factor of 5.1 × 10 , greatly

exceeding the criterion value of 100 for “decisive evidence” in support of the experimental

hypothesis. When DJB’s original experiments are excluded, the combined effect size for replications

by independent investigators is 0.06, z = 4.16, p = 1.1 × 10 , and the BF value is 3,853, again

exceeding the criterion for “decisive evidence.” The number of potentially unretrieved experiments

required to reduce the overall effect size of the complete database to a trivial value of 0.01 is 544,

and seven of eight additional statistical tests support the conclusion that the database is not

significantly compromised by either selection bias or by intense “p -hacking”—the selective

suppression of findings or analyses that failed to yield statistical significance. P-curve analysis, a

recently introduced statistical technique, estimates the true effect size of the experiments to be 0.20

for the complete database and 0.24 for the independent replications, virtually identical to the effect

size of DJB’s original experiments (0.22) and the closely related “presentiment” experiments (0.21).

We discuss the controversial status of precognition and other anomalous effects collectively known

as psi (Bem, 2011; Bem et al, 2015).

Experiments

Bem et al, 2015) give an overcview of typical experimenmts done to research anticipation.:

 Retroactive and pre-cognitive priming (Klauer & Musch, 2003; Rabeyron, 2014; Vernon,

2013)

 Time reversed affective processing (Batthyany, 2009; Batthyany & Spajic, 2008; Bierman,

2010; Popa & Batthyany, 2012))

 Retroactive habituation (Bornstein, 1989; Zajonc, 1968; Dijksterhuis & Smith, 2002;

Hadlaczky & Westerlund, 2005; Morris, 2012; Savitsky, 2003; Savva et al, 2004 and 2005;

Starkie, 2009)

 Retroactive facilitation of recall (Bem et al, 2015; Tressoldi & Zanette. 2012; Tressoldi,

Masserdotti, Marana, 2012 and 2013)

In 2011, Bem published a report of nine experiments in the Journal of Personality and Social

Psychology purporting to demonstrate that an individual’s cognitive and affective responses can be

influenced by randomly selected stimulus events that do not occur until after his or her responses

have already been made and recorded, a generalized variant of the phenomenon traditionally

denoted by the term precognition (Bem, 2011, Tressoldi, 2015)

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Two experiments tested time-reversed versions of one of psychology’s oldest and best known

phenomena, the Law of Effect Amendments from Version 1 Updated the P-Curve analysis and its

discussion using the fourth version of the P-Curve algorithm, and updated Figure 2 to reflect this.

We have also added the results of the BF robustness analysis related to the independent

replications, and corrected a typo in the abstract related to the value of the overall BF (Thorndike,

1898). An organism is more likely to repeat responses that have been positively reinforced in the

past than responses that have not been reinforced.

Standardized Emotion Elicitation Databases (SEEDs) allow studying emotions in laboratory settings

by replicating real-life emotions in a controlled environment (Branco et al,2023). In 1993, the

International Affective Picture System (IAPS; Lang, Bradley & Cuthbert, 1997 and 2005; Lang &

Greenwald, 1993) produced a set of more than 1100 digitized photographs that have been rated for

valence and arousal. This is for studying emotions in laboratory settings by replicating real-life

emotions in a controlled environment. Branco et al (2023) show 69 studies done based on IAPS.

Priming experiments have become a staple of cognitive social psychology (Klauer & Musch, 2003).

In a typical affective priming experiment, participants are asked to judge as quickly as they can

whether a photograph is pleasant or unpleasant and their response time is measured. Just before

the picture appears, a positive or negative word (e.g., beautiful, ugly) is flashed briefly on the screen;

this word is called the prime. Individuals typically respond more quickly when the valences of the

prime and the photograph are congruent (both are positive or both are negative) than when they are

incongruent (Klauer & Musch, 2003).

“Presentiment” experiments were pioneered by Radin (1997) and Bierman (Bierman & Radin, 1997)

in which physiological indices of participants’ emotional arousal are continuously monitored as they

view a series of pictures on a computer screen. Dean Radin follows a scientifically well-based

explanatory model. Dean Radin, who works as a senior scientist at the Institute of Noetic Sciences

(Radin, 2004a; Radin & Borges, 2009) researched XXXX. In various experiments he was able to

prove that people can anticipate the future by measuring skin resistance (lie detector principle)

(Radin, 2004a) and the dilation of pupils (Radin & Borges, 2009).

Using a non-intentional precognition test paradigm luck beliefs were explored as predictors of psi in

a series of three experiments (Luke, Delanoy & Sherwood, 2008; Luke, Roe & Davison, 2008). In

addition, the experiments were designed to explore aspects of Stanford’s (e.g., 1990) ‘psi-mediated

instrumental response’ (PMIR) model, within which the notion fits quite neatly that luckiness may

ordinarily be used euphemistically to account for everyday unconscious psi. The current study

describes a basic replication of the non-intentional precognition effect and compares it to intentional

precognition (Luke & Morin, 2009; Luke & Roe, 2008a and 2008b)

Two of Bem’s time-reversed experiments tested whether rehearsing a set of words makes them

easier to recall even if the rehearsal takes place after the recall test is administered (Retroactive

facilitation of recall; Bem et al, 2015). Bem published more experiments in the Parapsychological

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Association (Bem, 2003; Bem, 2005; Bem, 2008). As a result, replications of the experiments began

to appear as early as 2001 (as reported in Moulton & Kosslyn, 2011).

Critique on Anticipation

Bem’s experiments have been extensively debated and critiqued. The first published critique

appeared in the same issue of the journal as Bem’s original article (Wagenmakers et al., 2011).

These authors argued that a Bayesian analysis of Bem’s results did not support his psi-positive

conclusions and recommended that all research psychologists abandon frequentist analyses in favor

of Bayesian ones. Bem et al. (2011) replied to Wagenmakers et al., criticizing the particular Bayesian

analysis they had used and demonstrating that a more reasonable Bayesian analysis yields the

same conclusions as Bem’s original frequentist analysis. In a similar critique, Rouder & Morey (2011)

also advocated a Bayesian approach, criticizing the analyses of both Bem and Wagenmakers et al.

(Bem et al, 2015). Platzer (2011) showed the failure to replicate Bem (2011) Experiment 9

(Milyavsky, 2010). Ritchie, Wiseman, and French (2012) showed in failing the future three

unsuccessful attempts to replicate Bem’s ‘retroactive facilitation of recall’ effect as well as Robinson

(2011) with a failed replication of Retroactive Facilitation of Memory Recall.

Developing an Inventory

The Anomalous Experiences Inventory (AEI; Gallagher, Kumar, & Pekala, 1994) narrows the scope

of the Mental Experience Inventory (MEI; Kumar & Pekala, 1992) by excluding items that do not

directly pertain to anomalous and paranormal beliefs and experiences (e.g., introspection,

daydreaming, fantasizing); and it also expands the scope of the measure by including a broader

range of items concerning anomalous and paranormal beliefs and experiences. Items to assess past

and present experiences and beliefs about one's own paranormal abilities (e.g., I am able to move

or influence objects with the force of my mind alone") were added. Five subscales were confirmed:

anomalous experiences, beliefs, powers of the mind, fear, and drug use. The measure consists of

98, 70, 57, or 30 items for which participants indicate whether the item is true or false. The AEI's five

subscales fared well with respect to both reliability and validity. The KR-20 values ranged between

.64 and .85 for the five scales. The AEI's experiences, beliefs, and abilities subscales were

significantly correlated with the global paranormal measures of Richards, Tobacyk, and Davis et al.

Considered together they were significantly correlated with four of Tobacyk's paranormal belief

subscales. The AEI's fear and drug use subscales correlated less well with other anomalous/

paranormal measures. The AEI subscales showed some convergent validity when correlated with

selected personality measures. The AEI's experiences, beliefs, and abilities subscale, as expected,

correlated significantly with traits that are related to experience seeking and fantasy proneness. The

drug use scale also showed evidence of convergent validity when correlated with sensation-seeking

measures (Gallagher, Kumar & Pekala, 1994)

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Paranormal Belief

1. I have extrasensory perception and have mastered psychokinesis

2. I often have so-called déja vu experiences

3. My conscious feelings expand beyond my body

4. I often have psychological borderline experiences

5. I dream some professional decisions in advance

6. I receive messages from outside that help me with professional decisions

7. I have had near-death experiences that affect me professionally

Abnormal abilities?

8. I have extra-physical experiences and experiences

9. I have mystical experiences that support me professionally

10. I have out-of-body experiences

11. I have past life memories

12. I can communicate with deceased people and ask them for advice

13. I have apparitions that guide me

14. Forces from outside influence me

15. For professional decisions I usually use the cards

16. For professional decisions I use astrology and my horoscope.

17. My horoscope describes my professional decisions

18. For professional decisions I read / classify from the palm of my hand

19. I have abnormal abilities

20. I can influence professional decisions by focusing on them

21. I can influence my state of consciousness

22. I have supernatural abilities

23. I can see professional decisions in the distance

24. I can recognise people's auras

25. I am a medium and let it guide my decisions

26. I can leave my body and look at decisions from the outside

27. I can influence other people's decisions if I concentrate on them

28. I can explore my decisions under hypnosis

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The Revised Paranormal Belief Scale (RPBS, Tobacyk, 2004) is a widely used measure of

paranormal belief. The instrument comprises 26 statements (e.g., “The number 13 is unlucky”).

Participants respond using a seven-point Likert scale (1 = strongly disagree to 7 = strongly agree).

Consistent with Rasch, scaling scores were converted to 0–6 (see Irwin, 2009). Higher scores in

dicate greater belief in the paranormal. The RPBS has established psychometric properties (i.e.,

validity and reliability) (Drinkwater et al., 2017). In this study, the RPBS demonstrated excellent

omega (ω = 0.96) and alpha (α = 0.95) reliability.

Bem Feeling the Future Inventory

AN01_01 Bei beruflichen Entscheidungen spüre ich in meinem Körper Informationen, die lokal

nicht vorhanden sind

AN01_02 Ich spüre Informationen, die nicht physiologisch oder biologisch erklärbar sind

AN01_03 Ich habe telepathische Fähigkeiten

AN01_04 Ich kann die Gedanken anderer Menschen spüren

AN01_05 Ich kann Informationen aus meinem Umfeld wahrnehmen

AN01_06 Ich kann Informationen aus dem Universum wahrnehmen

AN01_07 Ich kann Informationen wahrnehmen ausserhlab der typischen menschlichen Sinne

AN01_08 Ich kann präkognitiv Reize erkennen

AN01_09 Ich kann präkognitive negative Reize vermeiden

AN01_10 Göttliche Eingebungen helfen mir bei beruflichen Entscheidungen

AN01_11 Ich erhalte Stimmulierungen von außen, die mir bei beruflichen Entscheidungen

helfen

The phrase 'the Australian Sheep-Goat Scale', or ASGS for short, refers to a item inventory (or family

of measures) of belief in various aspects of the paranormal, such as the extrasensory perception

(ESP), life after death (LAD), and psychokinesis (PK). The term 'sheep' is used for 'believer' in some

aspect of psychic phenomena, while 'goat' is used for 'disbeliever'. Paranormal phenomena have in

common the fact that they contradict C. D. Broad's (1978) Basic Limiting Principles about the

existence and operation of mind in the mathematico-physical world, and are therefore in some sense

anti-scientific. This paper describes the evolution of the ASGS from a 10-item instrument to an 18-

item measure. Since the beginnings of the ASGS in 1976, versions of the scale have been

administered frequently, and a summary is here provided of relevant empirical findings, both

parapsychological and psychological. Finally, a new and improved 26-item version of the scale is

offered, based upon, and named for, attitude towards the Basic Limiting Principles (Thalbourne,

2010).

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Survey of Scientifically Unaccepted Beliefs

Irwin and Marks (2013) reported the psychometric development of new measure of paranormal and

related beliefs. Based on a constructive review of the limitations of current self-report questionnaires

several criteria were formulated for development of the new measure. One of the key criteria was

that items had to meet an explicit definition of scientifically unaccepted beliefs, thereby allowing

inclusion in the new measure of a broad range of paranormal beliefs, traditional religious beliefs,

urban myths, and similar beliefs currently not accepted by the scientific mainstream. The new Survey

of Scientifically Unaccepted Beliefs is commended to researchers for its distinctive conceptual

perspective, its elegant psychometric structure, and its sophisticated psychometric properties.

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Dean, Akhtar, Gale, Irvine, Wiseman, and Laws (2021) developmed a Paranormal and Supernatural

Beliefs Scale using classical and modern test theory. Classical test theory methods (including

exploratory factor analysis and principal components analysis) reduced the scale to 14 items and

one overarching factor: Supernatural Beliefs. The factor demonstrated high internal reliability, with

an excellent test–retest reliability for the total scale. Modern test theory methods (Rasch analysis

using a rating scale model) reduced the scale to 13 items with a four-point response format. The

Rasch scale was found to be most effective at differentiating between individuals with moderate-high

levels of paranormal beliefs, and differential item functioning analysis indicated that the Rasch scale

represents a valid measure of belief in paranormal phenomena (Dean et al, 2021). This goes along

with the objective measurement of paranormal belief by Lange, Irwin & Houran (2001).

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The study on Paranormal belief and well-being

The study of Dagnall, Denovan & Drinkwater (2022) and Irwin, Dagnall & Drinkwater, 2013)

examined variations in well-being as a function of the interaction between paranormal belief and

psychopathology-related constructs. A United Kingdom-based, general sample of 4,402

respondents completed self-report measures assessing paranormal belief, psychopathology

(schizotypy, depression, manic experience, and depressive experience), and well-being (perceived

stress, somatic complaints, and life satisfaction).

Q1. I have had a dream about something of which I was previously unaware, and subsequently the

dream turned out to be accurate.

Yes, and it must have been an instance of telepathy or esp

Yes, but it was probably just a coincidence or unwitting insight

No

Q2. I have stared at the back of someone’s head and eventually they turned around and looked at

me.

Yes, and it must have been an instance of telepathy or esp

Yes, but it was probably just a coincidence or something else I did

No

Q3. Sometimes I’ve been thinking of a person I haven’t heard from in ages, and later in the day I

received a phone call, email or letter from that very person.

Yes, and it must have been an instance of telepathy or esp

Yes, but it was probably just a coincidence or rational expectation

No

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Q4. With someone I know intimately I sometimes know what they are about to say before they say

it.

Yes, and it must have been an instance of telepathy or esp

Yes, but it was probably just a lucky guess based on my familiarity with them

No

Q5. On at least one occasion I‘ve had the impression of a figure nearby, yet nobody could possibly

have been there.

Yes, and it must have been an experience of an apparition or ghost

Yes, but it was probably just an illusion or misperception

No

Q6. I have become aware of a scent in a room, yet there was nothing there that could have that

smell.

Yes, and it must have been an instance of an apparition or esp

Yes, but it was probably just an illusion or physiological anomaly

No

Q7. I have had an impression that a specific event was occurring at some distant location and

subsequently the impression turned out to have been accurate.

Yes, and it must have been an instance of clairvoyance or esp

Yes, but it was probably just a coincidence or rational expectation

No

Q8. I have seen an envelope of light around a person, and the color of the light depended on that

person’s mood or wellbeing.

Yes, and it must have been an instance paranormal aura perception

Yes, but it was probably just an illusion or physiological anomaly in me

No

Q9. I have accurately foretold a future event when I could not possibly have known it would occur.

Yes, and it must have been a case of a premonition or esp

Yes, but it was probably just good judgment or a coincidence

No

Q10. I have seen a pet become excited shortly before its owner arrived back home.

Yes, and it must have been an instance of telepathy or esp

Yes, but it was probably just the pet having learned when its owner would return or using its

acute hearing to detect the owner’s approach

No

Q11. On at least one occasion I have had the impression that I, my perceiving self, was

outside my physical body and seeing the vicinity from an external vantage point.

Yes, and it must have been a paranormal separation of mind from body

Yes, but it was probably just an illusion or misperception

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No

Q12. On at least one occasion I have had the impression I was in direct contact with the spirit of a

deceased person.

Yes, and it must have been an instance of channeling or paranormal communication with a

discarnate being

Yes, but it was probably just an illusion or wishful fantasy

No

Q13. I have had the experience of being healed by another person using only the power of their

mind.

Yes, and it must have been a case of psychic healing

Yes, but it was probably just an effect of suggestibility

No

Q14. On at least one occasion an object near me unaccountably moved or fell at the very time a

loved one was undergoing a trauma at a distant location.

Yes, and it must have been an example of paranormal action or psychokinesis

Yes, but it was probably just a coincidence or a minor earth tremor

No

Q15. I have seen (in person or on television) a psychic levitate an object.

Yes, and it must have been an instance of paranormal action or psychokinesis

Yes, but it was probably just a conjurer’s trick

No

Q16. In a life-threatening situation I have had the impression that my disembodied “self” was moving

along a tunnel toward a light.

Yes, and it must have been an instance of spiritual transfer to an after-death world

Yes, but it was probably just an illusion, perhaps induced by sudden physiological changes

No

Q17. When I was a child I thought I had lived as a different person in another time and place.

Yes, and it must have been an instance of reincarnation

Yes, but it was probably just an illusion or wishful fantasy

No

Q18. I have inherent abilities that neither of my (biological) parents possessed.

Yes, and these abilities I must have possessed in a previous lifetime or incarnation

Yes, probably because my life experience has differed from that of my parents

No, or don’t know

Q19. While alone in bed at night I have felt someone or something touch me, but when I switched

on the light there was nobody else there.

Yes, and it must have been an instance of a ghost or a demon

Yes, but it was probably just an illusion or dream, perhaps caused by anxiety

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No

Q20. In magazines I read, the horoscope for my star sign usually turns out to be accurate.

Yes, because astronomical phenomena have paranormal influences on human life

Yes, but astrologers’ statements are often true of anyone, regardless of star sign

No, or don’t know

In the study of Launer and Cetin (2023), anticipation was reduced to three important questions.

Anticipation (Pre-Cognition):

 I have a premonition of what is going to happen.

 I can foresee the outcome of a process.

 I foresee how to decide before I review all aspects

The common item selection studies mentioned anticipation in terms of

- Experiental Hunches in REI by Pacini / Epstein (1999)

- Emotional Hunches in PMPI by Burns / D´Zurilla (1999)

- Affective Hunches in TIntS by Pretz et al (2014)

- Affective Hunches by USID by Pachur / Spaar (2015)

The typical items is:

 I believe in trusting my hunches

Conclusion

The study shows the theory and items for empirical studies for the anticipative intuition based on the

concepts of hunches, pre-cognition, and pre-monition. It can be used in future studies.

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Diversity and Women Empowerment

Econometric Analysis of Gender Presence and Performance of Women in the

Workplace in Cameroon (Sub-Saharan Africa)

Jam Jude Ngong

and Kristine Joy S. Simpao

Keimyung University, South Korea, Orcid No. 0009-0002-1888-0029

Abstract

This study research paper investigates how gender discrimination affects corporate performance in

Cameroon. Data from the Cameroon Enterprise Survey in 2016 by the World Bank Group and data

collected from March 6 to 23rd, 2023, in Douala and Yaoundé, as well as 757 managers' responses,

were utilized. The analysis focused on three organizational levels: employees, management, and

business ownership. This study used a mixed method of descriptive and econometric analysis. The

results of this study revealed a positive and significant relationship between the presence of women

in the workforce and performance. This result is attributed to the improvement in the performance of

enterprises with appreciable participation of women in the workforce, management, and ownership

levels, specifically in the tourism industry, arts and crafts, textiles, general merchandising, and

distribution, which require less training and funding, which are the principal factors of discrimination

against women and girls in Cameroon. Furthermore, the turnover of businesses owned and

managed by women and those owned/operated by men shows successful growth compared to

companies of similar sizes.

Key Words: gender equality, corporate performance, business. econometric analysis

Introduction

A growing emphasis on Corporate Social Responsibility (C.S.R.) highlights the professional equality

between men and women in the corporate world. Owing to the complexity of the workplace, diversity

and inclusion have been questioned. This study argues that gender equality has become a moral

and strategic necessity for corporate competition. The compelling evidence from our research leaves

no doubt about the strategic advantage that gender equality can bring to corporate performance.

The International Labor Organization narrated in its Global Wage Report 2018/19 that women earn

20% less than men do globally (International Labor Organization, 2018). Moreover, women's labor

force participation rate is 26.5 percent lower than men's. Women are underrepresented in C.E.O.

(chief executive officer) positions and board seats despite several studies signifying a robust positive

correlation between gender diversity in the corporate world (Taghizadeh-Hesary et al., 2019). This

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study further reinforces this correlation by highlighting the significant Impact of gender diversity on

corporate performance.

Globalization has created genuine concern for interacting with organizations (businesses) and their

environment. Corporate Social Responsibility has been the emphasis that brings to light the

professional equality between men and women in the corporate world. Indeed, several empirical

investigations, particularly in developing countries such as Cameroon, have highlighted the effects

of gender equality through women's participation in the prosperity of businesses. Thus, gender

equality is imperative for corporate competition. One study shows that if a company reduces

obstacles to women's ascension in business, it will benefit growth, performance, and productivity

(Burke & Davidson, 1994). Gender equality can be an economic and managerial issue beyond being

a factor of social dynamism. There has been an increasing debate on the qualities of feminine

behavior as a vector of collective performance in businesses. However, there has always been a

stereotype that a man will earn for the family, and a woman, on the other hand, is expected to stay

indoors looking after the family responsibilities. After a long struggle, women were considered only

to look after the family.

Today, female entrepreneurs make up about one-third of the world's entrepreneurs; however, in

Africa, the situation still needs to be more encouraging for female entrepreneurs than for men,

considering the worse conditions in Cameroon. Indeed, the stereotype belief that women are to take

care of family responsibilities only has created gender disparity in enterprises between women and

men, most of which are in terms of the functions they perform, the sector of activity, or the wage rate

and compensation they receive. According to data, women constitute one-third of the world's

workforce, about 46%, compared to 72% of men, according to the International Labour Organization

(I.L.O.) 2016. In sub-Saharan Africa, there is a global gap of 17 percentage points between the

participation rate in the active population of women and that of men, which are 53% and 70%,

respectively (World Bank, 2015). In Cameroon, the results of the second General Census of

Enterprises, known in French as Recensement Genrale des entreprise 2eme edition (RGE-2),

conducted in 2016 by the National Institute of Statistics (I.N.S.), indicate that compared to men,

women are still less likely to be employed in companies. In a country like Cameroon, with a female

population of over 51%, only 43% of women are engaged in companies, and only 44% hold a

permanent job. This difference in participation is also noticeable when examining business size.

Cameroon, a patriarchal society, has a ratio of one woman to six men in large businesses and a ratio

of one woman to two men in small and medium-sized enterprises. A look at entrepreneurship reveals

more gender disparities in Cameroonian companies (62.8% of businesses are created by men

compared to only 37.2% by women).

Regarding management, 57.3% of the companies are run by men and 42.7% by women. Gender

attitudes and practices in Cameroon's labor market are rooted in the traditional patriarchal system.

They are reinforced by modern legal and political instruments that limit women's economic

advancement. Although the employment trends of women have improved (RGE2), the sociological,

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legal, and cultural burdens still relegate Cameroonian women to second place by reducing their

activities, primarily to fulfill family commitments and maternity constraints. A solid cultural attachment

is observed in these areas compared to urbanities due to the progressive enlightenment of females

and the significant emergence of government policies; prejudices, traditions, and customs still limit

women's employment in companies, their promotion to managerial positions, and even the

ownership of startups and the creation of enterprises. Beyond these socio-cultural barriers are

economic barriers, including lack of equity (in terms of training) and lack of access to institutional

credit, severely limiting women's entrepreneurship in Cameroon. These barriers amply testify to the

persistence of disparities in participation by gender in the labor market in general and in business in

Cameroon. For the proper functioning and participation of all Cameroonians in the economic

development of Cameroon, it is essential to nurture and encourage potential without gender

discrimination.

Cameroon, a patriarchal society, has a ratio of one woman to six men in large businesses and a ratio

of one woman to two men in small and medium-sized enterprises. A look at entrepreneurship reveals

more gender disparities in Cameroonian companies (62.8% of businesses are created by men

compared to only 37.2% by women). Regarding management, 57.3% of the companies are run by

men, and women run 42.7%. Gender attitudes and practices in the labor market in Cameroon are

rooted in the traditional patriarchal system that limits the economic advancement of women. Although

the employment trends of women have improved (RGE2), the sociological and cultural burdens still

relegate Cameroonian women to second place by reducing their activities, primarily to fulfill family

commitments and maternity constraints. Robust cultural attachment was observed in rural areas

compared to urban cities.

Government policies, prejudices, traditions, and customs limit women's employment in companies

and promotion to managerial positions. Beyond these socio-cultural barriers are economic barriers,

including a lack of equity and access to institutional credit, severely limiting women's

entrepreneurship in Cameroon. These barriers amply testify to the persistence of disparities in

participation by gender in the labor market in general and in business in Cameroon (I.M.F. Report,

2015).

Public authorities have made efforts in favor of gender equality and the advancement of women to

achieve not only Millennium Development Goals 1 and 3 (M.D.G.s) but, more generally, Objectives

5 and 101 of the Sustainable Development Goals (S.D.G.s) adopted by the General Assembly of the

United Nations, aimed at ensuring equal opportunities between women and men in all sectors,

particularly in the field of employment, despite a set of legal and regulatory mechanisms, consisting

not only of national legislation but also of international and regional legal instruments aimed at

promoting and protecting women's rights in the labor market and income-generating activities.

Professional equality remains challenging for Cameroonian authorities, who continue developing

strategies to encourage more women to participate in business. From this perspective, an action

plan for the development of female entrepreneurship (PAN-DEV) will be published under the aegis

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of the Ministry for the Promotion of Women and the Family, known by its French acronym

(MINPROFF) (Efogo & Timba, 2015), meaning Ministere de Promotion de la femme et de la famile

created in 2004 to encourage and promote women's participation in the social, economic, and

political life of the country, acknowledging their potential. In addition to these government structures,

informal structures such as tontines (community, business, or friends) and professional

environments (colleagues, customers, and suppliers) support female entrepreneurship in Cameroon.

These initiatives are strictly private and benefit from little or no government support.

This work seeks to attempt an answer to the following research questions.

1) How do women as part of the workforce in a business affect the performance?

2) How do women in management positions influence performance?

3) Are there differences in performance gaps between male-owned and female-owned

enterprises of similar size?

4) What econometric analysis model is recommended to affirm the association between gender

equality and corporate performance?

The following are the hypothesis statements of the study:

H1: If gender-based discrimination is resolved, corporate performance improves.

H2: Equal training and funding access for female entrepreneurs can improve corporate

performance.

H3: Do female entrepreneurs perform better than male entrepreneurs at an equal level?

Methodology

This study used a descriptive and causal-comparative research design to analyze the effect of

gender discrimination on employee performance in selected sectors in Douala, Yaoundé, and

Cameroon. A descriptive study was undertaken to explain the variables and their characteristics that

affect corporate performance through a questionnaire and econometric analysis.

The causal-comparative design examines the potential causes for observed differences among

existing groups (Fulmer, 2018) and determines whether the independent variable affects the

dependent variable (Jason & Rumrill, 2004). The cause-and-effect relationship between this study's

dependent and independent variables was analyzed using causal analysis.

Data from Kiva and USAID on global gender lens investing were utilized to verify the first hypothesis

(H1: if gender discrimination is resolved, corporate performance can improve) and the second

hypothesis (H2: equal access to female entrepreneur training and funding can improve corporate

performance).

The analytical approach inspired by the works of William H. Greene and F & D, while taking into

consideration the context of sub-Saharan Africa (Cameroon), was adopted to verify the first

hypothesis (H1): If gender-based discrimination is resolved, then corporate performance will

improve) Moreover, the second hypothesis (H2 equal access to training and funding of female

entrepreneurs can enhance corporate version). However, this approach does not make it easy to

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affirm with certainty that gender equality is the cause of the company's positive performance; it only

makes it possible to establish a clear link between the feminization of the company and its

performance.

A total of 757 managers from seven (7) selected industries from Doula and Yaoundé were chosen

as the study's respondents. These respondents were chosen based on their visibly established

enterprises, imperative registration on the trade and personal property credit register, and

registration in the taxation department. Some are members of enterprises in Cameroon known in

French as "Groupement International du Cameroun" (GICAM). Thus, the respondents were

sufficiently representative. The industries are brewery, arts, craft, livestock and fishery, General

Merchandise, banking, microfinance, insurance, hair salons, fashion, and Leisure and Tourism.

The data presented in this work were derived from research inquiries conducted in Douala and

Yaoundé of the Republic of Cameroon from March 6 to March 23, 2023. According to the general

Census of Enterprises (R.G.E.) conducted by the National Institute of Statistics (I.N.S.) in 2009, more

than 60% of the total number of enterprises in Cameroon are found in Douala and Yaoundé. These

two cities are the political capital (Yaoundé) and the economic capital (Douala) of Cameroon. This

figure provides a consequential image of the financial presentations of enterprises in Cameroon. It

also provides an idea of the demographic presentation of the country, with these two cities having a

population of over 9 million or approximately ¾ of the country's total population (about 25 million).

We interviewed 757 enterprises in different sectors and industries in the country. Our objective was

based on the budget and time required to conduct this study. According to data from the National

Statistics Institute, approximately 35.1% of enterprises are in Douala and 23.9% in Yaoundé.

Table 1.0: Respondents Population

Industry/subsector

Douala

Yaoundé

Total

Brewery

51

40

91

Arts & craft

75

40

115

Livestock & fishery 30 10 40

General Merchandising

150

115

265

Banking, microfinance &

Insurance

15 10 25

Hair salon & fashion

60

55

115

Leisure & tourism 46 60 106

Results and Discussion

The data were processed using frequency statistics, and thematic analysis was employed to

identify the relationship between gender equality and corporate performance. The models are the

most appropriate for use because they perfectly link various economic variables to each other. This

model provides a formal approach to estimating how a change in the explanatory variable affects

the explained variable, the dependent variable, considering the Impact of all other determinants of

the dependent variable—a linear regression model for the variables in this study as defined.

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Y=αX + ε

Y= independent variable (business performance)

X= vector of the dependent variable (gender inequality)

α= vector associated with the parameter to estimate

𝜀= error margin or residue

The following equation specifies the basic econometric model presented above.

𝛾= 𝜋+∝ 𝑥+∝ 𝑉𝐹 +𝜀

𝑦= Profit margins and returns on investments represent business performance variables.

∝ 𝑥= Exponential variable of sex gender discrimination of females.

∝ 𝑉. F. Vector of fixed or control variables.

ε= error terms.

The measures of the variables are mentioned above and explained in detail below. See the section

devoted to explaining or describing this study's variables.

The 3rd hypothesis (H3: Turnover between men-owned businesses and women-owned businesses

shows successful growth when comparing companies of similar sizes) can be verified by adopting

Robert W. Fairlie and Alicia M. Robb (2008) and Essus et al. (2018) to explain the performance gap

between female- and male-owned businesses of similar sizes in the Cameroonian context. The

standard blinder Oaxaca decomposition is used with the marginal effect from the logit specifications

for closure, profitability, and employability coefficients for linear log sales specifications. These

methods can be criticized for their lack of preference and the impossibility of establishing a coherent

relationship between the standards and nature of average-based analysis. However, the technique

produces very robust results that favor its wide use in exploring certain factors to explain inequalities

related to wages, employment, and productivity, as well as the production gap between men and

women in the labor market (Oaxaca, 1973; Fortin, 2011)

Therefore, we can estimate the performance matrix of female-owned businesses as follows:

(𝑥 + 𝑎)=  

𝑥𝑎





𝑌 = 𝛽 +  𝛽



 × + ∈

Y= log of business performance held by women

𝛽= vector of the coefficient to be estimated.

X= matrix of the explanatory or independent variable restrained in the model specifications

𝜖= error term

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Description of Variables

Response or Dependent Variable.

Business performance is the dependent variable in this study. Business performance is usually

measured using indicators such as return on assets (ROA), return on equity (R.O.E.), return on sales

(R.O.S.), profit margin, revenue, and revenue others (Kim et al., 2020).

The key performance indicators gauge a company's overall long-term performance. They help

determine strategic, financial, and operational achievements compared with businesses of the same

size and sector. Large companies' performance indicators are often measured regarding return on

investment, profit margins, and revenue.

Return on assets (ROA), return on equity (R.O.E.), and return on sales (R.O.S.) are criticized

because they present performance of the past, which is somehow good if the present concerns, such

as profit margin, return on investments, revenue, growth in turnover, and employment as short-term

and long-term performance. These performance indicators are easy to obtain and facilitate

accessibility of business performance information. These variables are considered objective

performance indicators (Delmar, 1997), and they are also regarded as indicators of entrepreneurial

success, according to Dunkelberge and Cooper (1982). The data presented in this study provides

information on the profit margin, return on investments, employee growth, and annual turnover. A

business with temporary part-time or seasonal jobs was challenging to differentiate from this study

because of its economic level. Difficulties accessing information on employees, annual sales, and

total assets seem complicated due to tax evasion; companies keep this information confidential and

secret.

Accessing this information was impossible because it cannot be found online and can only be

obtained from the financial departments of various companies. Due to complicated tax policies,

companies and businesses keep this information secret to avoid increased taxes. It becomes difficult

to calculate the performance measures of most companies with certainty. Due to administrative

tolerance and a lack of transparency in the archives of social security funds, it is difficult to know the

exact number of employees in companies/businesses.

Explanatory or Independent Variables

The main aim of this work is women's participation and its Impact on business performance in

Cameroon. In other words, we examine the Impact of gender discrimination on corporate

performance. The analysis can be observed at various levels: the significant elements of

discrimination, the effects of these discriminations on performance, and the gap between male- and

female-owned businesses. Differences exist between people's behaviors, and how these behaviors

affect business performance remains an object of debate. Social science considers gender

differences in behavior as a vector of collective business success and can favor access to career

evolution and acquisition of experience (Del Giudice, 2015). Access to credit and training are the

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316

variables that indicate whether credit is obtained to fund the business and whether the employee or

the management has the required training. The indicator of a company that benefited from credit

could be 1, and 0 for those that did not. Unlike male-owned businesses, female-owned businesses

usually face difficulties obtaining credit from institutions during their startup, survival, and growth

stages. Due to these difficulties, examining the variables concerning self-financing companies using

the owners' funds is imperative. The employees' and management's training and skills are

independent of this study, as they constitute an element of discrimination.

The physical presence of women is essential for business performance because of the difference in

behavior between women and men, which is visible and has been an object of debate in the social

sciences. Most social science studies have established that the differences in behavior between

women and men are significant vectors for collective success in an organization. In this study, the

presence of women was an essential aspect of business. Certain feminine qualities could also

influence a company's collective performance. This feminine quality has been considered in several

studies to contribute to women's teamwork performance, which is one of the essential aspects of

company performance. These feminine qualities can be a leg for those who think gender equality

could impact corporate performance. The education and funding of female entrepreneurs in

Cameroon could boost the economy's emergence.

Here, the variables of the workers' and management's training and skills are independent of this

study, as they constitute discrimination.

Fixed or control variables

The control variable was something held constant. This section tries to identify and explain the fixed

variables used in this study. In the context of Cameroon, gender discrimination and business

performance could have several selected or control variables, such as professional experience, age

of the company, political policy, registration, and others.

According to the human capital theory, resources and skills are essential for business performance.

The professional experience of management and workers is an important variable in this study; the

accumulation of experience and knowledge by management and employees is essential for the

company's performance. The works of (Westphal and Zajac, 1995, and Terjesen et al. 2008) opine

that women can accumulate valuable experience as managers of small and medium-sized

enterprises. Knowledge and understanding of the employee and the manager, especially

participation in performance, are usually measured by annual profit margin, company sales growth,

and others. Increasing the professional experience and knowledge of the executive leads to

improved performance. Another fixed variable is the age of the business, which is the time the

industry has been operating. The company's age is an essential variable in business performance

(M'hamid et al., 2011).

Business size was also a variable that should be considered in this study. The number of employees

measures a company's operating capital and financial capacity. The feminine quality of

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317

accountability places women in an advantageous position to run and manage large companies. Big

companies rely on responsibility for better performance. Companies in some sectors require more

guilt than others do. Thus, the sector in which the business operates is a valuable fixed variable that

can affect performance. The significant rise in the involvement of women and girls in the corporate

world in Cameroon over the past few years is a testament to the government's proactive measures

and the emergence of rights groups. These entities have been instrumental in raising awareness

about the crucial role of women and girls in the country's economic growth. The age of a business

is a crucial fixed variable that warrants investigation when analyzing a company's performance. This

factor can provide valuable insights into the company's growth trajectory and potential for success.

The official registration of the company, losses due to theft, investment in security, power outage,

possession of an electricity generator, and advice on the management of activities are all

dichotomous control variables used in this analysis.

Discussion

Profile of Respondents

There were 450 enterprises owned or managed by men and 307 enterprises owned and controlled

by women. The ages ranged from 17 to 60 for men and between 16 and 62 for women, with a total

of 757, commonly 51.5% single and 27% married.

In Cameroon, traditional African marriages are the predominant mode of marriage. Most marriages

in Cameroon are not registered in the civil status registry and are thus considered free unions. This

is because of the cumbersome procedure for registering marriages in the civil status registry.

However, the government occasionally organizes collective marriages to encourage free unions to

register their marriages. It explains The marital status of the respondents figured in question 3 of the

questionnaire, with the respondents having to choose whether they were single (120 respondents),

married (205 respondents), divorced (42 respondents), widowers (0 respondents), or free union (390

respondents).

Respondents' educational attainment was 28%, and they had the highest diploma. Due to the

stereotypical nature of Cameroonian society, women and girls do not have access to education as

their male counterparts do. The research reveals that most interviewees have yet to reach their

education level, as most have just gone through primary school. Two thousand ten of those

interviewed had no level of education: 167 went through elementary school, 188 went through middle

school, ninety-eight through high school, and 94 went through higher education. A business's

performance and operating mode would be much better with formal education. Most women in

Cameroon companies serve as a workforce, and their recruitment is based on tribal lineage,

sociological acquaintances, and family ties. Education and training are usually minor priorities when

working in or managing a business in Cameroon. There is a tradition of training a child of the family

or the village in the trade in which one operates to pass down the experience and knowledge to the

child within a period of usually seven years and then settles the child by opening the same kind of

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business for him to establish him as a compensation for serving the master for seven years.

Influences children to join their relatives and tribes' men in the cities immediately after elementary

studies to indulge in businesses, abandoning formal education. However, formal education is

necessary in highly skilled sectors like banking, insurance, engineering, and other industries. Thus,

such practices are infrequent in these sectors, although traces of tribalism and other

counterproductive attitudes can still be found.

The data indicate that the business owner or manager has acquired complementary training. The

results revealed that none (0%) of those interviewed had acquired professional training. In

comparison, 230 (31%) had apprenticeship training or apprentices in the enterprises where they

worked, and 25 (3%) had formal training in secretarial, electricity, engineering, and others. In

comparison, 502 (66%) samples did not undergo training.

Degree of interference of the family in the enterprise.

The Degree to which family members interfere in the enterprise can be seen in multiple ways,

either by financing, which is usually not the case, or by dependence upon the business as a source

of support (Qiu & Freel, 2019). This indicator affects men as they are usually the breadwinner of their

families. Families depend on the business's profits for their livelihood, making it difficult for owners

to plow back profits, thereby increasing performance. In most cases, women are more likely to push

back profits, making their performance higher than their male counterparts.

Impact of environment on performance

The environment here refers to extended families, friends, neighbors, and the community in which

they operate. Some settings have a positive impact on performance, whereas others harm it. Those

working in a vulnerable and underprivileged environment turn to conducting more corporate social

responsibilities and spending more money on charity and social activities without profit. In contrast,

middle—or upper-class people pay less for social activities and plow back profits.

Zone inquiry

This indicates the geographical zone in which the interviews were conducted. The areas of inquiry

in this study were Douala and Yaoundé. According to data from the general census of enterprises in

2006, these two cities constituted approximately 60% of the total number of registered enterprises

in Cameroon. Yaoundé is Cameroon’s political capital, while Douala is Cameroon’s economic

capital.

Subsector.

It is part of a more significant sector, a branch of the industry. For example, the general

merchandising sector may consist of retailers specializing in selling different items, such as

groceries, furniture, and other commodities.

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Employee Apprentice.

The questionnaire survey indicated that most of the enterprises interviewed operated in the fields of

brewery, arts and craft, livestock and fishery, general merchandising, banking and finance, hair

salons, fashion, leisure, and tourism—employee apprenticeship, which is the process of acquiring

acquisition valuable experience in a particular domain to gain expertise. Most of the sectors of the

Cameroonian economy require practical knowledge and expertise to be able to perform. Employees

must undergo apprenticeships in industries such as hair salons. In this situation, the employee must

sometimes pay the employer for training in banking and finance, tourism, leisure, insurance, brewery,

and other related industries. The employer benefits by equipping the employee with the necessary

skills to perform, sponsoring the employee's apprenticeship, and making it easier to acquire the

skills. Women are often excluded from internships in the enterprises mentioned above because of

family constraints and maternity holidays; meanwhile, they are the dominant apprentices in

enterprises where apprenticeship is paid.

This affirmation can be verified in the study of informal vocational training and sustainable livelihood

skills among unemployed youth in low-income countries: insights from a SWOT analysis of tailoring

apprenticeships in Cameroon by Ijang Bih Ngyah and Etta Mercy Aki.

Access to Bank Loans.

This question aims to determine the frequency with which enterprises go for bank loans and how

accessible these loans are to enterprises. The most common conditions for obtaining a bank loan in

Cameroon are providing collateral or having a guarantor ("shorter"). Valuable collateral securities for

bank loans are landed and have movable properties, e.g., cars. Women need more access to land

properties, making it extremely difficult to obtain independent bank loans. Thus, they require

approval from their husbands, who are loan guarantors. Unmarried women are required to bring a

family member or relative with stable employment, and, in most cases, the bank will require the

guarantor's salary to pass through their bank for the duration of the loan. Obtaining bank loans is

cumbersome for female entrepreneurs, especially startups. Sometimes, bank loans for small and

medium-sized enterprises do not excite 12 monthly installments.

However, the need for external funding has imposed a sense of community cooperation among

startups. These startups come together and contribute a certain amount monthly to fund one

member. This funding will rotate until all members are equally supported. This process of community

funding is known as the tontine in Cameroonian jargon.

In very few cases, startups or enterprises receive funding from non-governmental organizations,

goodwill individuals, and charity organizations. These findings are usually scarce and apply to

enterprises in the agricultural sector. In sporadic cases, enterprises attempting to go bankrupt can

benefit from this funding. Related studies on this effect could examine credit access in Cameroon

and diaspora investors' access to bank credit in Cameroon.

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320

Client's accessibility behavior.

This question aims to determine the enterprise's accessibility to clients or potential clients. It seeks

to determine how the position of the business location influences the performance. Certain

enterprises, like the tourism and leisure industries, do not have problems establishing their

enterprises. What is of prime importance to them is the advertisement and quality of services they

offer; meanwhile, in other sectors such as general merchandising, location, and accessibility are

very important because regardless no of the quality of the product and service provided, if the

business location is not accessible to clients, potential clients will not come. Table of correlation

between the presence of women workforce and management/ownership and performance.

Table 2.0: Correlation between the presence of women workforce and management/ownership and

performance.

Performance Indicators

Workforce

Manager/ Owner

Women Men Women Men

Return on assets (ROA).

200/307

239/450

188/307

300/450

Return on sales (R.O.S.). 200/307 239/450 188/307 300/450

Return on equity (R.O.E.).

200/307

239/450

188/307

300/450

Profit margin.

0 0 0 0

Funding.

0

87/307

450/450

Complementary training 169/757 437/757 106/307 317/450

Data analysis and performance indices (P.I.) presentation per company category.

This part of the study compares companies/businesses owned by women and men in selected

sectors in which data were collected. The sectors chosen were general merchandising and

distribution, arts and crafts, and tourism and leisure.

The data demonstrate that these sectors were selected based on their popularity in Cameroonian

society: general merchandising and distribution (265 samples), arts and crafts (115 models), and

tourism and leisure (106 pieces).

The table below shows the comparison, with sex and performance indices (second.) as the main

variables and classified from first to fourth. The first category represents 𝑜𝑛𝑒 ≤ 𝑃𝐼𝑓𝑜𝑢𝑟𝑡ℎ5, 2nd

category 1.5 ≤ 𝑃𝐼 ≤ 2, 3rd category, 2 ≤ 𝑃𝐼 ≤2.5, 4th category, 2.5 ≤ 𝑃𝐼 ≤ 3. The various categories

of performance indices are based on return on assets, equity, sales, and profit margins. The profit

margin is the most common indicator measured in finance. Employee growth and stock are also

indicators of interest. Due to difficulties evaluating other growth aspects, we emphasize the profit

margin in financial terms. Category 1 enterprises have a profit margin between USD 2000 and USD

3000. By contrast, category two enterprises have a profit margin between USD 3000 and USD 4000.

Category 3 enterprises have a profit margin between USD 4000 to USD 5000, and Category 4

enterprises have a profit margin between USD 5000 to USD 6000. The sex remained male and

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female, while the performance indices were evaluated on a scale from 1 to 3. The tables are

presented in Tables 1 and 2,3,4, with Table 4 demonstrating the percentage of the general data

collected and Table 1,2,3 representing the selected sectors' data. Table of Sex Variables and

Performance Indices per category in the Distribution and General Commerce industry.

Table 3: General Merchandising/performance indices (P.I.) 265 samples

1st 2nd 3rd 4th Total

Sex

Male

0.0

34

85

12

131

Female 0.0 51 75 8 134

Total

0.0

109

136

20

265

The above table indicates that of the 265 enterprises interviewed, none made a profit, as shown by

the monthly performance indices of USD 2000 to USD 3000. Thus, 0.0%. This observation could

explain why general merchandising requires enormous capital to run businesses and operate

efficiently in this sector. The targets in this sector were enterprises registered in the trade and

registry. In that access, essential information on return on sales, return on assets, return on equity,

and other factors was provided. This can be easily obtained. The figures were obtained by finding

the percentage of each category from the total number of male and female-owed/managed

enterprises in the performance category, as shown in the table above. On the other hand, there were

34 male-owned or managed enterprises for the second category, 85 for the third category, and 12

for the fourth category. On the other hand, the female-owned or ordered enterprises for the second

category, seventy-five for the third category, and 8 for the fourth category, which makes a total of

134 enterprises in this sector managed by women against 131 operated by men.

Table 4.0: Performance indices per category for Arts and crafts, 115 samples

1st 2nd 3rd 4th Total

Sex

Male

17

24

49

0

52

Female 8 40 15 0 63

Total

25

64

26

0

115

The total number of enterprises interviewed in the arts and craft sector was 115, 52 of which were

managed/owned by men, while sixty-three were held/managed by females. None of the enterprises

in this sector made a monthly profit margin of USD 5000. For this sector's male-owned or managed

enterprises, Category 1 had 17 enterprises, Category 2 had 24, and Category 3 had 49 enterprises.

On the other hand, for female-owned or managed enterprises, the first category had eight

enterprises, the second had 40, and the 3rd 15, making 63 enterprises owned/operated by females.

Table 5.

Performance indices per category for the tourism and leisure industry (106 samples).

1

st

2

nd

3

rd

4

th

Total

Sex

Male

3

16

33

3

55

Female

3

20

23

5

51

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322

Total

6

36

56

8

106

The above figures are obtained by calculating the sum of each variable's sex and performance

indices from the indicated sector or industry from the data collected. A simple addition of the total

will give 100%. The calculations were performed to minimize the error margin.

A table of the performance indices of the total number of questionnaires collected in the field shows

the overall performance of the companies or enterprises concerning the gender of the owner or

manager. For the first category, there is a relative increase in the performance of male-

owed/managed companies. However, as the class increases, we observe a rapid change in business

performance, favoring female-owned/operated businesses. This indicates that if female-owned

businesses are funded or have access to funding and adequate training, they can perform better.

With limited training and lack of access to funding, female-owned/managed businesses of

comparable size to male-owned/managed businesses still stand out, irrespective of the numerous

discriminations they face. The table below demonstrates the performance indices per category of

the questionnaires and data collected in the field.

Table 6.

General performance indices of the questionnaires studied (757 samples)

1st 2nd 3rd 4th

Sex Male 1.7

%

34.5

%

54.8

%

9.0

%

Female 1.0

%

26.2

%

57.1

%

15.7

%

Total 1.4

%

31.0

%

55.8

%

11.8

%

Conclusion and Recommendation

Thus, there is a positive and meaningful relationship between the presence of women in the

workforce and performance. There is also a positive and meaningful relationship between the

presence of women in management positions, board of directors, and company performance. The

turnover of businesses owned and managed by women and those owned/operated by men shows

successful growth compared to similar companies.

Therefore, this study recommends improving women's, girls', and female entrepreneurs' access to

training and funding to equip them with the necessary skills to enhance their performance. Gender

awareness needs to be improved to reduce the stereotypes and macho mindsets that make men

uncomfortable working under women's management.

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Financial Literacy in Investment Decisions of Working Womem

Jasveen Kaur and Ishma Gupta

Guru Nanak Dev University, India, Orcid No. 0009-0003-2887-3524

Introduction

Financial literacy is more essential than ever in an era of swift technological advancement,

globalization, and fluctuating economies (Valladares, 2020). Financial resilience and well-being are

largely dependent on financial literacy, which is commonly understood to be the capacity to

comprehend and manage one's finances (Kumar et al., 2023). It covers a broad spectrum of skills

and information, such as retirement planning, debt management, investing, saving, and budgeting

(Sahadeo, 2018). Despite its significance, research shows that a large section of the world's

population lacks adequate financial literacy, which has negative effects on people individually, in

families, and on society at large (Garg & Singh, 2018).

Financial literacy includes a deeper comprehension of intricate financial terms and their practical

applications (Matheson, 2019). It goes beyond simply knowing how to calculate interest rates and

balance a checkbook. It entails understanding the effects of financial actions, weighing the benefits

and risks, and making well-informed decisions consistent with one's beliefs and financial objectives

(Kumar et al., 2023). Furthermore, financial literacy encompasses broader societal variables,

including economic policies, regulatory frameworks, and access to financial products, in addition to

individual behavior (Stolper & Walter, 2017).

Gender differences are especially evident in the area of financial literacy. Several studies have

demonstrated that women generally have lower financial literacy skills than males (Lusardi, 2019).

There are ample reasons for this gender disparity in financial literacy, including access to financial

resources, educational opportunities, and cultural norms. Also, it is vital to address women's literacy

because they frequently confront particular financial obstacles, such as the gender wage gap,

caregiving obligations, and longer expectancies of life (Ophir & Polos, 2022).

Improving the financial literacy of women serves as a vehicle for social advancement and gender

equality alongwith economic empowerment (Ndung’u, 2021). Women who possess the knowledge

and abilities to handle their money wisely will find it easier to become financially independent, pursue

job possibilities, and provide for their family (LeBaron et al., 2018). Women who possess financial

literacy are also better equipped to speak up for their rights, take part in economic decision-making,

and remove structural obstacles that prevent them from being financially included (Klapper &

Lusardi, 2020).

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Financial literacy is a problem that needs to be solved in a multidimensional way that includes

community empowerment, policy interventions, and education (Goyal & Kumar, 2021). Building

basic knowledge and abilities is facilitated by educational initiatives, which can range from adult

financial literacy programs to curriculum based in schools (Totenhagen et al., 2015). Filling the

gender gap in financial literacy also requires actions to promote gender-sensitive policies, expand

financial inclusion, and make cheap financial services accessible (Sharma, 2020).

Financial literacy is essential to both societal advancement and economic empowerment.

Individuals, especially women, are better able to make decisions that improve their financial well-

being and contribute to greater economic stability when they have the information and abilities to

successfully manage the complexity of personal finance. Financial literacy enables people to take

charge of their financial destinies, pursue their goals, and overcome economic challenges—from

budgeting and saving to investing and retirement planning. More gender equality and economic

opportunity can also be fostered by tackling the gender gap in financial knowledge and supporting

inclusive educational programs. Hence, financial literacy investments are a means to a more robust,

equitable, and prosperous society for all, as well as an investment in personal prosperity. The

rationale for this research lies in the critical relevance of financial literacy in navigating today's

complex economic landscape. It is imperative to tackle the pervasive deficiency of financial literacy,

especially among females, in order to promote personal welfare, social progress, and financial

stability. Through a variety of strategies, such as education and policy interventions, the research

tends to increase financial literacy and empower people while promoting a more just and prosperous

society.

Review of Literature

Scholars have focused a great deal of attention on the importance of financial literacy in achieving

economic empowerment, and a growing body of research has examined how it influences financial

decisions and behaviors across a range of populations. Dam & Hotwani (2018) developed a thorough

scale that incorporates important components such as risk assessment, retirement planning,

financial planning, and investment planning, providing a strong instrument for assessing financial

literacy. Their methodical strategy to the development and improvement of items produced a

trustworthy instrument for additional scholarly research.

Building on this basis, Grohmann (2018) investigated the degree of financial literacy in urban Asia,

paying particular attention to Bangkok's middle-class citizens. The study revealed a noteworthy

paradox: although the average level of financial literacy was on par with industrialized nations, there

existed a large disparity in the comprehension of intricate financial ideas. This discrepancy

emphasizes how important it is to raise financial literacy in order to make better financial decisions.

Similar to this, Gangwar & Singh (2018) looked at the socioeconomic factors that influence adult

Indian financial literacy. Their research revealed the glaring differences in financial literacy between

various demographic groups and made a compelling case for focused interventions, especially for

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the less fortunate. Gupta & Gupta (2018), whose study of rural Himachal Pradesh residents

demonstrated how financial literacy influences investment decisions, further supported the

significance of customized financial education by highlighting the need for specialized efforts to

improve understanding and decision-making processes in these communities.

As evidenced by Mudzingiri et al. (2018), who looked at the variables influencing university students'

financial behavior in South Africa, the importance of financial literacy transcends these situations.

Their study provided important insights on how to help young adults to become financially literate by

demonstrating the impact of risk perceptions and confidence levels on financial decision-making.

Similar to this, Morgan & Trinh (2019) provided information on the financial literacy levels in Vietnam

and Cambodia, highlighting the need for targeted interventions for vulnerable people and exposing

the demographic and socioeconomic determinants influencing literacy outcomes. Santini et al.'s

(2019) meta-analysis, which examined the causes and effects of financial literacy by discovering

interactions between variables like gender, education, and financial behavior, contributes to this

expanding conversation. This study has shown to be essential in comprehending the complex nature

of financial literacy. Zulaithi et al.'s (2020) study on the financial behaviors of secondary school

teachers in Jakarta, Indonesia, highlights the wider implications of raising financial literacy at all

societal levels by demonstrating the favorable effects of financial literacy on investing and budgeting

decisions. Azeez and Akhtar's (2021) research concentrated on digital financial literacy in rural India,

namely in the district of Aligarh. They showed that demographic characteristics are important in

determining one's understanding of digital finance. Their conclusions serve as a foundation for

actions meant to fill in current knowledge gaps. Similarly, Brochado & Mendes (2021) provided a

methodological road map for further research in this field with their systematic review, which

emphasized the crucial connection between financial literacy and saves behavior.

Matey et al. (2021) further underscore the transformative potential of financial literacy programs by

examining the impact of financial literacy instruction on the social and economic well-being of

Ghanaian teachers. Their research provided useful advice for upcoming treatments and showed the

significant influence that financial literacy can have on financial management abilities. By examining

the cultural aspects of financial literacy, namely the gender gap in China's urban and rural areas,

Preston et al. (2023) broadened the discussion and demonstrated the significant impact of cultural

elements on financial literacy outcomes. Oppong et al. (2023) looked at the relationship between

investment decisions, personal finance management, and financial literacy among Ghanaian private

sector workers, delving deeper into the African setting. Their results indicated positive correlations

between these characteristics, endorsing all-encompassing programs meant to foster inclusive

economic growth and individual empowerment. With her research on the influence of financial

literacy on Sri Lankan undergraduate students' investment decisions, Kumari (2020) made a further

contribution to this topic by highlighting the necessity of extensive educational programs to promote

well-informed financial decision-making. Last but not least, Singh & Raheja (2019) examined

academicians' investing choices in Jalandhar, India, pinpointing the critical elements that influence

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financial behavior, from investment knowledge to governmental regulations. Policymakers and

educators can use their findings as a reference to better understand how financial literacy affects

investment outcomes.

When combined, these studies show how complex financial literacy is and how it affects financial

well-being and empowerment in a variety of contexts. In Southeast Asia's metropolitan areas as well

as rural India and Africa, financial literacy is still essential for attaining just and sustainable economic

growth.

Research Gap

There may not be many studies that explicitly address the financial literacy relevance in the life of

working women, despite the necessity of financial literacy being recognized more and more.

Research that has already been done may focus mostly on larger demographics or certain groups,

which leaves a gap in one’s knowledge of the demands and difficulties working women have.

Research frequently draws attention to the disparities in literacy between the genders, with research

showing that women typically have lower levels than males. It's possible that not enough research

has been done on the financial literacy of working women in particular, or how their financial

responsibilities and employment status relate to their financial literacy and decision-making.

Although a lot of study has been done on the connection between investing decisions and financial

literacy, there might not be enough information to apply to the particular situations faced by working

women. When creating tailored interventions and financial education programs to meet the needs of

this group, it is essential to comprehend how financial literacy influences investment decisions.

Working women frequently balance a variety of duties and obligations, such as managing finances,

advancing their careers, and providing care for their families. When considering variables like risk

tolerance, investment preferences, and long-term financial goals, there can be subtle differences in

how their levels of financial literacy translate into investing decisions. These differences deserve

more research.

In order to advance gender equality and economic empowerment, it is imperative that the research

gap in financial literacy and investment decisions among working women be addressed.

Policymakers, companies, and financial institutions can create plans to assist working women in

reaching financial stability and independence by knowing the obstacles to financial literacy and the

effects on investment behavior.

Methodology

The first objective is to assess the value that financial literacy holds for working women. It entails

determining the degree of comprehension and expertise that women have in relation to financial

matters. It tries to gauge their learning of financial planning, debt management, investing, saving,

and budgeting.

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The second objective is to determine the impact of financial literacy on investment decisions of

working women. It focuses on investigating how it influences the investment decisions made by

women. It involves analyzing whether those with higher financial literacy tend to make more informed

and effective investment choices compared to those with lower financial literacy. The objective will

help learn more about the connection between working women's investment activity and their

financial literacy by looking at this influence.

The present paper's research technique takes a methodical approach to exploring and developing

theoretical frameworks pertinent to the subject matter. The first step in answering the research

question is to perform a thorough evaluation of literature, which has included theoretical works,

empirical studies, and scholarly discourse. A critical synthesis has then been conducted to develop

a theoretical framework that expands on and integrates preexisting ideas to offer a novel opinion on

the topic being studied. Throughout this process, theoretical reasoning, comparative analysis, and,

when possible, the examination of empirical evidence have been used to iteratively refine the

theoretical framework. Throughout the research process, careful attention has been paid to

transparency and rigor, with a focus on clearly articulating the rationale.

Discussion

The first objective of assessing the significance of financial literacy in working women’s life aimed to

provide insights into their comprehension and proficiency regarding various financial matters. The

assessment encompassed key areas such as financial planning, debt management, investing,

saving, and budgeting.

The findings revealed a spectrum of financial literacy among the working women. Some participants

demonstrated a strong understanding and capability in managing their finances, while others

exhibited limited knowledge in certain areas (Klapper & Lusardi, 2020). Financial planning emerged

as a critical aspect, with varying levels of proficiency observed among participants. Those with a

higher degree of financial literacy seemed to have well-defined financial goals and strategies to

achieve them (Singla & Mallik, 2021). On the other hand, individuals with lower financial literacy

levels may lack a structured approach to financial planning, potentially impacting their long-term

financial stability (Setyorini et al., 2021). Debt management is another significant dimension of

financial literacy assessed. Participants who are more financially literate have exhibited better

management of debt, including understanding interest rates, repayment schedules, and strategies

for debt reduction (Baidoo et al., 2020). In contrast, those with lesser levels may struggle to

effectively manage debt, leading to potential financial strain (Rahman et al., 2021). Investing

knowledge varied among participants, with some demonstrating a grasp of investment principles

such as risk and return, asset allocation, and diversification (Nofsinger, 2017). Conversely, others

showed limited understanding of investment options and associated risks, highlighting the need for

education in this area (Atkinson et al., 2015). Saving habits have also been evaluated, with financially

literate individuals demonstrating the ability to allocate resources effectively towards savings goals

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(Mohammed et al., 2018). In contrast, those with lower financial literacy levels may face challenges

in prioritizing savings and building emergency funds (Hilgert et al., 2023). Budgeting skills varied

among participants, with some demonstrating proficiency in creating and adhering to a budget to

manage expenses effectively (Barr & McClellan, 2018). However, others exhibited difficulties in

budgeting, leading to potential overspending and financial instability.

The findings suggest less literacy of finance in women is heterogeneous, with some individuals

possessing strong knowledge and skills, while others exhibit gaps in understanding finance related

concepts and practices. The varying levels underscores the importance of targeted interventions to

enhance financial education and empowerment among working women (Birochi & Pozzebon, 2016).

By addressing knowledge gaps and providing resources for skill development, organizations and

policymakers can support women in achieving financial independence and security. Furthermore,

the findings emphasize the need for tailored financial literacy programs that address the specific

needs and challenges faced by working women. These programs should focus on building

foundational knowledge in areas such as financial planning, debt management, investing, saving,

and budgeting, thereby equipping women with the tools and confidence for taking well informed

decisions (Sherraden et al., 2018).

Overall, enhancing financial literacy is crucial for promoting economic empowerment, reducing

financial vulnerability, and fostering long-term financial well-being. By investing in financial education

initiatives, stakeholders can empower women to control their own financial futures and achieve their

goals.

The second objective tends to examine the impact of financial literacy on investment decisions of

working women. The preferences of working women in terms of investments are greatly influenced

by their financial literacy magnitude. Higher literacy is associated with a more likelihood of having a

diverse investment portfolio, which consists of a range of assets like stocks, bonds, mutual funds,

and real estate (Fong et al., 2021). They are aware of the significance of distributing risk and long-

term return maximization. Women who lack financial literacy, on the other hand, might prefer to

adhere to safer but lower-yielding investment options or might decide not to invest at all because

they lack knowledge or confidence (Baker et al., 2020). Working women who are financially

knowledgeable are frequently driven by long-term financial objectives like saving for retirement,

building wealth, and becoming financially independent. They understand that investment can help

them increase their wealth and stabilize their finances (Haabazoka, 2019). They also recognize how

inflation affects their savings and look for investment possibilities that outpace inflation for

maintaining their money over time. Conversely, individuals with less financial literacy could invest

only for unexpected expenses or pressing necessities rather than having a long-term plan for

accumulating wealth (Ward & Lynch Jr, 2019). Working women who are financially literate frequently

consult a range of sources when making investing decisions. These could include books, seminars,

workshops, credible financial websites, and guidance from financial experts like planners and

advisors (Crawley, 2012). They recognize that before making any investment decisions, careful

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investigation and due diligence are necessary. Additionally, they may leverage financial news and

analysis to stay informed about market trends and economic indicators that could impact their

investments (Raza et al., 2023). Conversely, women with lower financial literacy may rely on limited

or unreliable sources of information, such as friends, family, or hearsay, which may not provide them

with the necessary knowledge to make informed decisions (Munakampe et al., 2018).

The goal of assessing how working women's financial literacy affects their investment decisions

illuminates the vital role that financial education plays in enabling women to make wise and

successful investment decisions. Policymakers, educators, and financial institutions can create

focused strategies to increase financial literacy among women and thereby improve their financial

well-being and economic empowerment by understanding how financial literacy influences

investment preferences, reasons for investing, and sources of information (Assefa & Rao, 2018).

Additionally, one can close the gender gap in investment participation and assist women in reaching

their long-term financial objectives by supporting financial literacy efforts designed specifically to

address the requirements and obstacles faced by working women.

Conclusion

The study's finding highlights the vitality that financial literacy holds and its significant influence on

their financial empowerment and well-being. This study highlights the diverse range of financial

knowledge and its consequences for women's financial prospects.

The results show that working women have varying degrees of financial literacy; some have gaps in

their knowledge of important topics, while others show great financial management skills. In order to

close knowledge gaps and improve financial empowerment, specific interventions are required in a

number of critical areas, including budgeting, debt management, investing, saving, and financial

planning.

Furthermore, the study emphasizes how important financial literacy is in influencing working

women's investing preferences and decision-making. Long-term financial objectives, a more

diversified investment portfolio, and well-informed decision-making are all correlated with higher

financial literacy. Initiatives for targeted financial education can enable women to accomplish their

financial goals and successfully negotiate challenging financial environments.

The implications drawn from this study emphasize the necessity of targeted interventions,

collaboration among stakeholders, and ongoing assessment of financial literacy programs. By

prioritizing financial education, policymakers, educators, financial institutions, employers, and

community organizations can support working women in achieving greater financial resilience,

independence, and prosperity.

In essence, addressing the research gap is not only a matter of economic imperative but also a

fundamental step towards fostering gender equality and inclusive economic growth. Through

financial empowerment and education, we can build a more just and successful society that benefits

everyone.

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331

Implications

The research's conclusion throw light on the varied state of working women's financial literacy and

its significant ramifications for their financial empowerment and well-being. As covered in the

sections before it, the evaluation showed that participants' understanding and skill in important areas

like budgeting, debt management, investing, saving, and financial planning varied widely. These

discoveries highlight how crucial it is to implement focused interventions meant to improve working

women's financial empowerment and education. This segment delves into the consequences of the

discoveries and provide feasible approaches for interested parties to tackle the recognized obstacles

and prospects. By leveraging these implications, policymakers, educators, financial institutions,

employers, and community organizations can collaborate to foster a more financially resilient and

empowered female workforce.

Programs for financial education that are specifically designed are necessary, as seen by the

disparities. Financial planning, debt management, investing, saving, and budgeting are just some

areas where these programs ought to be tailored to the unique demands and difficulties that women

encounter (Dwiastanti, 2015). Targeted interventions should be implemented by organizations and

policymakers to improve working women's financial empowerment and literacy. Through knowledge

gaps and skill development resources, these interventions can assist women in achieving increased

stability and independence (Woodgate et al., 2017).

Working women can reduce risk and increase long-term profits by diversifying their investing

portfolios. Initiatives taken should place a strong emphasis on the value of asset allocation and

inform women about possibilities for investing that go beyond standard savings accounts (Lusardi &

Mitchell, 2014). The financial education motive should be to help working women see their financial

objectives from a long-term perspective. Prioritizing goals like retirement savings, wealth

accumulation, and financial independence can encourage women to make well-informed investing

choices that are consistent with their long-term goals (Tomar et al., 2021).

Enabling working women to obtain trustworthy financial information and advice is crucial for them to

make well-informed investment choices. This entails making use of tools like financial websites,

books, seminars, workshops, and the expert counsel of financial planners and counselors (Archuleta

et al., 2021). Closing the gender gap in investment participation can be achieved by initiatives aimed

at raising working women's financial literacy. Financial literacy programs support greater gender

equality and economic empowerment by giving women the information and self-assurance to invest

(Andriamahery & Qamruzzaman, 2022).

To support financial literacy initiatives for working women, stakeholders such as legislators,

educators, financial institutions, employers, and community organizations should cooperate

together. Stakeholders can develop comprehensive plans to enhance women's financial

empowerment and well-being by combining their resources and expertise (World Health

Organization, 2018). It is imperative to consistently assess the efficacy of financial literacy initiatives

for employed women and modify them in response to feedback and changing need. Through

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constant adaptation to evolving situations and new obstacles, interested parties may guarantee that

their work stays significant and applicable in the long run (Latapí Agudelo et al., 2019). Stakeholders

may enhance their literacy, confidence, and empowerment of women by putting these implications

into practice. This will ultimately lead to better financial outcomes and increased economic stability

(Wangui, 2018).

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Zulaihati, S., Susanti, S., & Widyastuti, U. (2020). Teachers’ financial literacy: Does it impact on

financial behaviour?. Management Science Letters, 10(3), 653-658.

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Diversity-Equality-Inclusion Practices in Small and Medium-Sized Companies: a

Study in 4 Countries

Tauno Kekäle

University of Vaasa. Finland, Orcid No. 0000-0002-6086-2687

Extended Abstract

Every individual deserves equal opportunities and equitable treatment in the workplace, regardless

of their gender, race, ethnicity, religion, age, sexual orientation, or other differences.

It is, however, generally stated that many small and medium-sized companies (later SMEs) still lack

the knowledge and resources to implement and monitor diversity, equality and inclusion of their staff

(later DEI) effectively. Thus, suppliers to big companies that will need to report corporate social

responsibility among other issues already by 2026 (or latest by 2029 for smaller companies; Allgeier

and Fellmann, 2023) due to the Corporate Sustainability Reporting Directive would have no

knowledge, skills, abilities, or resources to adopt the directive in practice or adhere to the national

laws that are issued in relation to it.

In the SME context where resources are scarce and every headcount matters to maintain

profitability, some paths such as e g utilisation of mentors to universally help with these issues is

hard (Clarke-Sather, et al, 2011). Thus, we need to identify the elements of the specific SME context

in Europe, as to realize what are the potential bottlenecks when managing DEI and what could be

the untapped opportunities (O’Donovan, 2017; Masocha, 2019). Moreover, it would be important to

simulate in practice the DEI management process, so that it would feel real, acceptable, and integral

to European SMEs.

In a recent project we are conducting surveys about the DEI issues that underrepresented groups

face, and about the nature of the SMEs who struggle the most to understand and implement DEI

management. The joint report should identify gaps in different stakeholder groups’ perspectives,

name the major bottlenecks which make DEI management in the SMEs complex (Lopez-Torres,

2023), and set priorities to be developed in DEI management (Mansell et al., 2023). The blueprint

will go through the extensive revision and critique by various SMEs, academics, and under-

represented groups participating in the project, to ensure that it entirely meets SME and expectations

in different countries.

With the first survey we study SME perspectives on DEI, and best practices and challenges SMEs

face in DEI management. The second survey, for the under-represented groups, will answer the

second research question How do SME characteristics affect their sustainability actions in relation

to diversity, equity, and inclusion ensure equity and inclusion at work. The two surveys are made in

four countries: Finland, Lithuania, Austria, and Germany.

The first survey to the SMEs consisted of 39 questions, and the dependent variables have been

chosen to affirm diversity, equity, and inclusion related practices. These variables are composite

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variables which have been formed from sets of questions and response options by calculating the

means of the variables. These should help us answer the first research question How do SME

characteristics affect their sustainability actions in relation to diversity, equity, and inclusion. A total

of 120 responses from the four countries were gathered during the summer of 2024. This sample

size could be argued to be a statistically unviable representation of the population of the SMEs

(altogether more than 4.6 million SMEs exist in these four countries), and the results should thus be

interpreted with caution (Zondervan-Zwijnenburg and Rijshouwer, 2022).

An interesting trend was however found when comparing company size within the SME sample with

the tendency of having DEI practices in place. The results, despite the weaknesses of the study this

far, indicate that as firm size decreases, companies are more likely to adopt equity-related practices.

In other words, medium-sized firms are less likely to adopt various DEI practices than small and

micro-sized firms.

A second survey, to help us gain understanding about what are the DEI related challenges that

underrepresented groups are facing when seeking employment or at work in European SMEs, has

also been conducted in the same countries. Here, the survey gathered a total of 288 responses, and

the analysis is ongoing (together with some qualitative data gathering); some indicative results will

be presented in the conference.

As the SMEs constitute the backbone of the EU economy, the problems SMEs face that are related

to social responsibility remain unsolved, partly due to lack of tools to educate graduates that could

lead the change towards inclusion. Together, these studies will be used to generate a framework for

a digital tool create at least a shared DEI standard around which the SMEs could develop their

internal processes and strategies when implementing ESG requirements for social responsibility. A

tool that resonates with the realities of the SMEs within the EU, and that could be used by the

educators in their programs to develop graduates with the needed skills, may ensure that social

challenges within the EU would be addressed through a holistic and achievable manner.

References

Allgeier, S., & Feldmann, R. (2023). CSRD Sustainability Reporting For Non-listed SMEs: European

Regulators Remain Challenged. European Company and Financial law Review, 20(3), 438-446.

Clarke-Sather, A. R., Hutchins, M. J., Zhang, Q., Gershenson, J. K., & Sutherland, J. W. (2011).

Development of social, environmental, and economic indicators for a small/medium

enterprise. International Journal of Accounting and Information Management, 19(3), 247-266.

Lopez-Torres, G. C. (2023). The impact of SMEs’ sustainability on competitiveness. Measuring

Business Excellence, 27(1), 107-120. https://doi.org/10.1108/MBE-12-2021-0144

Mansell, P., Philbin, S. P., & Konstantinou, E. (2020). Redefining the Use of Sustainable

Development Goals at the Organisation and Project Levels — A Survey of Engineers.

Administrative Sciences, 10(55), 1-39.

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Masocha, R. (2019). Social sustainability practices on small businesses in developing economies: A

case of South Africa. Sustainability 2019, 11, 3257.

O’Donovan, D. (2017). Diversity and Inclusion in the Workplace. In Machado, C. and Davim, J. P.

(Eds.), Organizational Behaviour and Human Resource Management: A Guide to a

Specialized MBA Course (pp.73-89). Springer.

Zondervan-Zwijnenburg, M., & Rijshouwer, D. (2020). Testing Replication With Small Samples.

Applications to ANOVA. In van de Schoot, R., & Miočevic, M. (Eds.), Small Sample Size

Solutions. A Guide for Applied Researchers and Practitioners (pp. 173-174). Routledge.

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Women in Digital: A Comparative Analysis of EU and Türkiye

Özlem Genç

1)

, Olcay Ceran Arslan

1)

, Batuhan Özkanlı

2)

and Özlem Atay

1)

1) Ankara University, Turkiye, Orcid No. 0000-0001-6253-1120, 0000-0002-2114-4076 and 0000-

0002-2563-825x

2) Loughborough University, United Kingdom, Orcid No. 0009-0006-2262-9039

Purpose

The aim of this study is to evaluate the role and participation of women in the EU and Türkiye. We

examined the correlation between internet usage rates and women working in the field of information

and communication technologies (ICT) to analyse digital transformation process. In this context, the

situation of Turkish women in ICT sector is compared with EU countries.

Theoretical Framework

Within the framework of the EU's "2030 Digital Compass" and the DESI data, the impact of digital

transformation on human capital will be analyzed. In particular, the role of digital literacy in

contributing to a qualified workforce in the digital economy is discussed, and strategies and policies

aimed at increasing women's participation in the digital economy will be evaluated. In this context,

the digital performance of EU countries is examined, and recommendations will be developed

regarding women's contributions to the digital transformation process. In addition to the relation

between women's participation in the ICT sector, their internet use in Türkiye has also been

investigated. For tech careers, access to the internet serving is a key factor in developing the digital

literacy, skills, and opportunities.

The study differs from other work in the field in terms of the methodology, subject and comparison.

Defining the correlation between the internet usage and gaining ICT speciality to see the effect on

human capital makes the research unique. The sections that emphasize the importance of women's

participation in the digital economy and evaluate the impact of the EU's digital transformation are

notable. Specifically, the part that highlights the weak and strong relationships between women's

internet usage and their employment as ICT specialists which are different according to country

groups and the analysis stressing the necessity of education, awareness, and breaking societal

prejudices to strengthen this connection, stand out. The findings of the article conclude that

correlation between internet usages is meaningful if education, policies on raising awareness and

breaking social prejudices prevail in both EU and Türkiye.

Methodology

To determine the role of women in the digital transformation process, which is the focus of the study,

DESI data is used. First, the study will assess whether the internet usage rate, one of the most

important indicators of digital literacy, is a metric for digital transformation and its role in influencing

the qualified human capital that creates added value. For this, a correlation between the internet

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usage rate and women working as ICT specialists is examined. Sustainable digital transformation

will only be possible with a workforce that has the potential to create innovative value. The impact of

basic digital literacy on the development of human capital capable of driving digital transformation is

explored. The correlation is measured using the Python programming language, coded in Jupiter

Notebook. To ensure a sound evaluation, all EU countries is examined, followed by an analysis of

the 13 member states that joined after 2004, which have more heterogeneous economic and social

structures. Additionally, a literature review on the status and development of human capital in the

digital world is conducted to support the evaluation.

Results

In the EU as a whole, the Pearson correlation coefficient between women's internet usage rates and

the percentage of women working as ICT specialists is 0.59. This indicates a positive and statistically

significant relationship between the two variables. On the other hand, in the 13 countries that joined

after 2004, this coefficient is calculated to be 0.28, indicating a weak relationship. This means that

there is not a strong connection between internet usage and the percentage of women in the ICT

field in these countries. This means, women’s ability to specialize in the ICT field is linked not only

to internet usage but also to education and qualified human resources. This situation highlights the

influence of socio-economic differences. In addition breaking stereotypes to strengthen women's

roles in the digital economy by pursuing studies in STEM (Science, Technology, Engineering, and

Mathematics) fields from an early age. The EU aims to increase digital literacy and train highly

qualified digital specialists by 2030. Inclusive education policies and strategic approaches to digital

skills are emphasized in this context. It is evident that future policies should focus on these elements.

DESI data is used to analyse the woman in digital EU. The use of estimated values for certain

countries in DESI may not fully capture all aspects of the digital transformation process. Within DESI,

“Women in Digital” index is used to measure women's participation in digital transformation that may

not fully reflect the social and economic differences between countries. There are significant

differences in the levels of digitalization among EU member states. Countries that joined the EU after

2004, in particular, have more heterogeneous social and economic structures compared to other

member countries which affect the consistency of the correlation analyses change the findings which

let us make implications from a wider perspective.

Discussion and Conclusions

Sustainable digital transformation will only be possible with a workforce that has the potential to

create innovative value and women inclusion in human capital. First, DESI data should continue to

monitor women’s contributions and participation in the digital transformation process, guiding

policies to analyse whether gender equality is being achieved in countries' digital transformation

processes. There should be concrete steps in areas such as digital literacy, education, labour

policies, and cultural change: To increase women's digital skills, greater investment should be made

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in STEM fields. In addition, gender equality strategies should be developed to increase female

representation at the management level. The EU can introduce mandatory quotas, laws, and

regulations to ensure gender equality in member countries.

As a conclusion, the emphasis on how digital skills should not solely rely on internet usage, along

with the importance of education, in this process, represents the original insights of the text. The

analysis that underlines women's equal participation in the digital economy as a strategic component

of the EU's 2030 Digital Compass goals, and the need for increased investments in gender equality-

focused education and infrastructure to achieve these targets, is an original assessment of the

article. In Türkiye, the participation of women in the ICT sector has been a topic of increasing focus

in recent years. Although the country has made some strides toward greater gender equality in

various fields, including education and the labour market, women are still underrepresented in the

ICT sector, which is a growing and vital part of the Turkish economy. Factors like socio-economic

status, geographical location, education, and cultural norms influence both internet use and

participation in ICT, highlighting the need for policies and programs that address these barriers to

foster greater inclusion of women in the digital economy both in Türkiye and EU-13 similarly.

Keywords: Women in Digital, EU, Türkiye, Digitalisation in Human Capital, Gender

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Exploring the Possibilities of Manufacturing in Programming Education for Women

Natsumi Kurosawa, Yuna Miyashiro and Natsuko Uchida

Ferris University, Yokohama, Japan

Introduction

In recent years, with the advancement of technology, programming skills have become increasingly

in demand. In Japan, programming education has been made compulsory in elementary schools

since 2020 and in high schools since 2022. However, in university education, a significant number

of students are from the pre-curriculum reform era and lack programming experience or have a

negative attitude towards it. This is particularly true for students in liberal arts universities, who tend

to have a stronger resistance to programming.

Furthermore, for female students like myself, there is a common stereotype that "programming is for

men," and many women feel resistant to learning programming due to their perceived lack of

mathematical ability.

In this study, based on my own experience as a programming novice, we will concretely demonstrate

how female students who are hesitant about programming have changed their attitudes towards

programming through creative activities such as embroidery. Additionally, we will discuss the

importance of programming education in higher education.

Materials and Teaching Methods

Scratch and Overview of the Classes

In this study, we used Scratch (https://scratch.mit.edu/), a visual programming language. Scratch

allows users to program by combining blocks, making it easy for beginners to learn. It is particularly

suitable for creating animations and games and is widely used in educational settings. In this study,

we analyzed the programming learning process in two types of classes.

Class A: Information Literacy Basics

Purpose: To acquire basic knowledge of programming

Content: Pair programming for animation creation. Learn control structures (sequential,

branching, repetition), create storyboards, and translate them into programming.

Class B: Introduction to Computer Science

Purpose: To acquire basic knowledge of programming

Content: Individual embroidery production. Learn control structures and create embroidery

data using Scratch extensions. Actually, embroider using a computer sewing machine.

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Class A: Animation Production

In Class A, students worked in pairs to create animations. First, they created storyboards to plan

the overall composition and movement of each scene in detail. Then, they used Scratch to program

based on the storyboard. Through pair work, they cultivated communication skills, problem-solving

abilities, and experienced the fun of programming.

Class B: Embroidery Production

In Class B, students used the Scratch extension (https://scratch.sugiura-lab.jp/) to create

embroidery data. This extension allows you to convert shapes created in Scratch into data that can

be sewn by a digital embroidery machine. Students created original embroidery works by

programming in Scratch based on their own drawings. By combining programming and handicrafts,

they stimulated new creativity and increased their motivation to learn.

Practical Examples

Class A: The Very Hungry Caterpillar Animation

Second author created an animation of "The Very Hungry Caterpillar," a picture book I loved as a

child, using Scratch. To reproduce the world of the picture book, we used blocks such as "move 5

steps" and "repeat 5 times" to create smooth movements for the caterpillar.

When creating scenes where the caterpillar eats various foods, we created a program for eating one

food and registered it as a "block definition." This allowed me to efficiently create scenes where the

caterpillar eats the remaining foods, significantly reducing the amount of work.

Working in pairs was a very valuable experience. Thanks to my partner's ideas, we were able to

create a more creative animation where the caterpillar changed color depending on the fruit it ate.

Also, by discussing with my partner, I was able to improve my communication skills.

We were motivated to take the next step and wanted to challenge myself with more advanced

programming.

Embroidery Production

In embroidery production, as with animation production, first author first drew a design of the

embroidery we wanted to create and created a detailed design. Based on this design, we created a

Scratch program.

The big difference from animation is that since we were actually sewing with an embroidery machine,

we needed to simulate the movement of the needle more precisely. For example, depending on the

shape you draw, you need to consider the movement of the needle. You need to consider where to

insert the needle, where to remove it, and how to move it. You also need to set the stitch type and

size in detail.

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We challenged ourselves to create a star. As shown in the Figure 1, we created a star by repeating

an isosceles triangle six times. We used the "repeat" block to create the program efficiently.

Then, we tried to create a hemp leaf pattern by adding multiple straight lines to the star. However,

we found that there was a big difference between the display on the screen and the actual

embroidery result. In particular, the thread was concentrated in the center, making it look bad and

causing problems such as the thread bunching up or the needle breaking. From this experience, we

learned that it is very important in programming to compare the simulation on the screen with the

actual output and correct the differences.

We were able to easily understand and use the "repeat" control structure. However, we did not fully

understand how to use "branching" and in what situations.

Advanced Learning

Although the class was limited in time, we delved deeper into Scratch programming after exhibiting

my work at the school festival. Initially, we were only drawing simple shapes, but we gradually

became curious about "what would happen if we combined various shapes," and we began to

experiment.

In particular, understanding the concept of variables greatly expanded my programming capabilities.

By using variables, we could easily modify specific parts of the program, allowing me to experiment

efficiently. For example, by defining the size of a triangle as a variable, we could use the same

program to draw triangles of various sizes.

Figure 1 How to make code

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We were also able to express complex patterns with a small amount of code by combining repetition

and variables. For example, in a program that draws a continuous sequence of triangles, we were

able to create a dynamically changing pattern by gradually changing the size of the triangle using a

variable.

However, we encountered a new challenge when combining variables and repetition. Specifically, it

was difficult to build an appropriate program structure when dynamically changing the value of a

variable while performing a repetitive process. To solve this problem, we searched for a way to

manipulate variables inside a block definition and eventually found a solution.

Through this production activity, we realized the flexibility and expressive power of programming. In

particular, we learned that the combination of variables and repetition is a powerful tool in

programming. In the future, we would like to learn more complex algorithms and create more

advanced works.

Conclusion

Through programming learning, I realized that programming is not difficult at all, but rather a fun way

to cultivate creativity. In particular, I am convinced that visual programming languages like Scratch

can significantly lower the barrier to entry for programming beginners.

Combining embroidery, a handicraft that has been popular among women for a long time, with

programming was a very valuable experience for me. Embroidery is a craft that requires a sense of

beauty and meticulous attention to detail. By combining programming and embroidery, I was able to

cultivate both logical thinking and aesthetic sense.

For students who did not have the opportunity to learn programming in high school or who gave up

on learning programming once, Scratch is a great starting point to step back into the world of

programming. Also, for women who are interested in embroidery, programming may open up new

possibilities for them to realize their own designs.

Through this learning, I realized the importance of having a solid understanding of the fundamentals

of programming. By having a solid foundation, you can challenge yourself with more complex

programs and, if problems arise, you can identify the cause and solve it.

Furthermore, learning programming not only cultivates logical thinking and problem-solving skills but

also improves self-esteem. The sense of accomplishment when a program you created works as

intended and is actually realized as embroidery is a great joy and further motivates you to learn.

From this experience, I believe that the use of visual programming languages like Scratch in

programming education is very effective in increasing students' motivation to learn and overcoming

their fear of programming. In particular, by combining elements that women are interested in, such

as embroidery, it has the potential to encourage more women to participate in the world of

programming.

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Thank you Note by Editor

Thank you very much to all particiapnts of CoSiM 2024

Markus Launer

Conference Proceeding of the 8th international online Conference on Contemporary Studies in Management (CoSiM), CoSiM Journal No 4, Institut für gemeinnützige Dienstleistungen, Germany

Abstract

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