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Understanding the Potential Value of Digitization for Business – Quantitative Research Results of European Experts

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There are many drivers known for implementing aspects of digitization in business. While some firms are already successfully integrating the opportunities of digitization into their business processes, others still lack understanding and expertise. The impression is created that some firms rely on the bandwagon effect, i.e. they are doing it because everybody else is doing it! For that reason, the authors design a quantitative study based on a former qualitative research to prove main drivers of successful digitization aspects. Interviews with European experts, collected within the framework of this research, give empirical evidence of six factors (efficiency, innovation, data privacy, mobility, new business models and human integration) influencing the potential value of digitization in business. The research results show significantly that improvements of efficiency and mobility as well as the generation of new business models are main drivers of digitization for business success.
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Understanding the Potential Value of Digitization for
Business – Quantitative Research Results of European
Experts
Christopher Reichstein1, Ralf-Christian Härting1, and Pascal Neumaier2
1 Business Administration, Aalen University of Applied Sciences,
Aalen, Germany
{christopher.reichstein, ralf.haerting}@hs-aalen.de
2 Competence Center for Information Systems, Aalen University of Applied Sciences,
Aalen, Germany
pascal.neumaier@kmu-aalen.de
Abstract. There are many drivers known for implementing aspects of digitization
in business. While some firms are already successfully integrating the
opportunities of digitization into their business processes, others still lack
understanding and expertise. The impression is created that some firms rely on
the bandwagon effect, i.e. they are doing it because everybody else is doing it!
For that reason, the authors design a quantitative study based on a former
qualitative research to prove main drivers of successful digitization aspects.
Interviews with European experts, collected within the framework of this
research, give empirical evidence of six factors (efficiency, innovation, data
privacy, mobility, new business models and human integration) influencing the
potential value of digitization in business. The research results show significantly
that improvements of efficiency and mobility as well as the generation of new
business models are main drivers of digitization for business success.
Keywords: Potentials, Digitization, Business, Strategies, European Experts,
Quantitative Study, Empirical Results.
1 Introduction
Digital transformations have caused a tremendous change of social and business
structures [1]. The expansion of internet technologies enabled an emergence of new
information and communication possibilities. In the course of this, the digital process
affects individuals, as well as companies [2]. Because of the digital transformation,
companies have to adapt to the far-reaching changes. Digital technologies such as Big
Data, Internet of Things, Cloud and Mobile Computing, are changing value creation
processes that in turn enables an emergence of new business models [3]. By new
competitors pushing into the markets, the market situation gets more and more
competitive. In order to remain competitive in future, it is inevitable for companies to
scrutinize their own business model and adapt to new digital requirements [4].
Digitization is not a new term since it has already appeared in the course of the third
industrial revolution as a data conversion process from analog to digital. However, the
understanding of the term digitization has changed. Nowadays, the term is associated
with smart value creation processes using capable information and communication
technologies. Although the term digitization is widely used, there is no consistent
definition in literature. Moreover, main potentials of digitization for business strategies
are not clearly defined yet in order to understand how to use driver of digital processes
for better firm performances.
Thus, this study seeks to verify main potentials of digitization from an enterprise’s
(mostly employees with an IT background) perspective based on a former qualitative
study. These six hypotheses were checked within this quantitative research by in total
216 experts in order to quantify main drivers of digitization potentials for business [5].
The paper is structured as follows: Chapter 2 defines the terms of digitization and its
potentials. Hereafter, the authors are going to describe the research design and methods
in chapter 3 in order to understand among others how data were collected. The study
results are presented in chapter 4 followed by a conclusion of the paper in chapter 5.
2 Definition and Potentials of Digitization
The digital revolution is not a new phenomenon. It has presented new challenges for
companies and society for decades. An example is the electronic information exchange.
It evolved from simple types of notification (e.g. symbols) to complex communication
relations in the form of digital data over the course of time [6].
Along with the change of digital technologies, the understanding of digitization has
been adjusted. As with the industry 4.0 case, the term "digitization" now stands for
intelligent business and value-added processes by using powerful information and
communication technologies such as Big Data, Cloud and Mobile Computing, Internet
of Things or Social Software [7-8]. Thus, digitization is not only the provision of
information, but also the (partial) mapping of value-added processes in electronic form.
In addition to industry 4.0, the conception of digitalization implies:
new approaches to digitization found throughout the industry, particularly in the
consulting and services sector [9-10];
digitization as a driver for the development of new business models with innovative
products [11].
Digitization, according to Kagermann [11], describes the continuous convergence
of the real and virtual world and can be regarded as the main driver of innovations and
changes in all sectors of our economy. According to a former study [12], all operational
as well as functional areas can benefit from digitization. Digitization has an impact on
the existing analogue and / or manual work environment, for instance [13]. The change
in a digital factory or privacy issues exemplifies this. There is an additional influence
on already digitally implemented work areas such as the IT organization [14].
Besides the economy, several other areas make use of digitization aspects. In the
past, cultural goods have undergone a series of digitizing for the sake of protection of
future purposes. [15]. Teaching content at universities is increasingly driven by digital
approaches [16]. The public administration is gaining an increasing amount of digital
access to its stakeholders under the slogan "e-government", too [17].
A consideration of the concept of digitization cannot simply be reduced to
technologies and their potentials for business processes, but must also include all
factors from the social and legal environment. Hence, digitization should be viewed
from a holistic, systemic perspective to be able to consider these factors within its near
entirety [6]. A system, in this context, is a set of elements that consists of
interrelationships [18-19]. Core elements like the infrastructure of new digitization
approaches result from new technologies as well as services and applications. Under
the term "technology", all new developments, i.e. in the areas of "Big Data or Mobile
Computing", can be subsumed. An example for digital services are cloud services, in
particular the "software as a service" model. Digital services offer a wide range of
business-oriented applications from the industrial as well as the service sector [20].
3 Research Design and Methods
Within the framework of a qualitative research in 2016 [5], different factors of the
potential value of digitization in business were identified. This study was based on
empirical data from 72 European experts using the methodology of Grounded Theory.
In this former study, IT experts mentioned six main driver for a successful usage of
digitization aspects for business predominantly. The results of the qualitative survey
enable to extend the current scientific view of the potential value of digitization for
further business strategies. In the following, the study design, research method and data
collection are explained.
3.1 Study Design
To explore the potential value of digitization, the authors designed a quantitative
research study based on the former qualitative research [5].
Fig. 1. Research model
Interviews with European experts, collected within the framework of this research, give
empirical evidence of six factors (efficiency, innovation, data privacy, mobility, new
business models and human integration) that positively influence the potential value of
digitization for business strategies. Further, all influencing factors are encouraged
through specialized literature. Figure 1 shows the developed research model including
six hypotheses.
The potential value of digitization can be defined as the individually perceived
capability of the implementation of digital technologies. Digital technologies enable
the acceleration of processes along the entire value chain, which leads to a reduction of
costs [5], [21]. Therefore, hypothesis 1 was created:
H1: An improvement of efficiency positively influences the potential value of
digitization.
In addition to efficiency improvements, digital technologies also enable companies
to improve their innovation processes [5], [22]. Networking along the value chain
improves the flow of information and shortens innovation cycles [23]. This leads to the
creation of hypothesis 2:
H2: An improvement of innovation processes positively influences the potential
value of digitization.
With an increasing degree of digitization, companies are becoming more and more
dependent on reliable information and communication systems [24]. Due to several risk
through the growing number of cyber-attacks, such as data theft [38] and sabotage [39],
data security will play an increasingly important role in the future [5], [24]. Therefore,
hypothesis 3 was created:
H3: Data security positively influences the potential value of digitization.
Nowadays, more and more companies are using mobile devices, such as
smartphones and tablets [25]. The combination of mobility applications and mobile
internet provides employees a flexible access to information. This can not only increase
productivity, but also enhance employee satisfaction [5], [26-27]. Consequently, this
leads to hypothesis 4:
H4: An improvement of mobility positively influences the potential value of
digitization.
Digital technologies like cloud computing and social media lead to a completely new
set of business models and a change in consumer’s behaviors and expectations [5], [11].
This phenomenon leads to an obsolescence of convectional business models. Adapting
business models allows companies to gain competitive advantage and customer loyalty
[4] that leads to hypothesis 5:
H5: The generation of new business models positively influences the potential
value of digitization.
In addition to changing business models, digitization changes requirement profiles
for employees [28]. The automation degree will rise due to an increase in networking.
On the one hand, this leads to a loss of lower qualified jobs and on the other hand, it
can result in the gain of higher qualified jobs. [29]. While potentially causing a loss in
lower qualified jobs, digitization can increase the number of higher qualified jobs [29].
Hence, companies need to provide further education for employees [28]. Changes
within a company can lead to uncertainties among employees. To avoid resistance,
employees need to be involved in the process of change. To create acceptance among
employees, good communication is inevitable [5] resulting in hypothesis 6:
H6: Human involvement positively influences the potential value of digitization.
In order to examine the impact of the defined determinants on the potential value of
digitization, respondents had to answer on a Likert scale [30] of one to six (1: low to 6:
high) within the online survey. All questions are conceptualized in accordance with
general guidelines of quantitative studies [34]. The supported literature review is
summarized in the following table (Table 1):
Table 1. Summary of literature review
DETERMINANT ITEM AUTHOR
Efficiency Single Item [5], [21]
Innovation Single Item [5], [22-23]
Data security
sabotage & data theft
[5], [24], [38-39]
Mobility
Single Item
[5], [25-27]
New business models Single Item [4-5], [11]
Human involvement Single Item [5], [28-29]
3.2 Research Methods and Data Collection
The quantitative research study is based on a web survey, conducted within German-
speaking countries (Germany, Austria and Switzerland). The study was implemented
via the open source LimeSurvey [31]. A pre-test was carried out to ensure high quality
standards. The main study started in June 2016 and ended in August 2016. The
questionnaire was mainly distributed via email and personal contact to IT manager and
IT experts with instructions to participate in the survey. The interviewers asked that the
survey should only be attended if there was expertise in digitization aspects within the
company. In total, 303 answers were collected. After data cleaning, 216 answers
remained for evaluation. The majority of the participants came from Germany (78.24
%), followed by Switzerland (16.20 %) and Austria (5.56 %). Most of the interviewed
experts are working in the information and communication sector (26.85 %), followed
by those in professional, scientific and technical activities (20.37 %) and manufacturing
(18.52 %). The classification of sectors was based on the European Classification of
Economic Activities (NACE Rev.2). Table 2 shows the number of employees from
participating firms. More than 87 % of all interviewed experts are working in small or
medium sized companies with less than 500 employees.
Table 2. Number of employees per firm
Employees
abs.
in %
0-4
72
33.33 %
5-9
27
12.50 %
10-19
26
12.04 %
20-99
39
18.06 %
100-499
24
11.11 %
500-4,999
15
6.94 %
5,000-10,000
5
2.31 %
>10,000
8
3.70 %
The study was evaluated by using a structural equation modeling (SEM) with Partial
Least Squares (PLS) approach to visualize the relationship between different variables
[32]. In general, the tool Smart PLS is used to calculate the direct effects of the found
dependent variables in literature on the dependent variable “potential value of
digitizationas it is particularly suitable for smaller sample sizes [32]. In addition, SEM
is a suitable method for this research to test the fit of a causal model with empirical data
and new developed scales [33-34]. The Smart PLS approach focusses on a partial least
squares regression based on sum-scores and significances are calculated via
bootstrapping. The non-parametric procedure called bootstrapping allows testing the
statistical significance of various PLS-SEM results like path coefficients, Cronbach’s
Alpha and R² values [35]. It has to be noticed that there is no need to calculate metrics
like Cronbach’s Alpha (CA) or Average Variance Extracted (AVE) in case of single
item sets. Furthermore, single item sets are not only allowed but also common in
information systems research [35].
For multi-item measures (like the determinant “data security”) common quality
criteria such as Cronbach’s Alpha (CA), Average Variance Extracted (AVE) and
Composite Reliability (CR) are calculated to ensure good psychometric properties of
the model. Accordingly, the authors examined reliability and validity to ensure a high
quality of the measurement model and its constructs by considering the recommended
threshold of .50 for Cronbach’s Alpha (for new and developed scales), .50 for Average
Variance Extracted, and .60 for Composite Reliability [37, 40].
4 Results
Figure 3 shows the results after analyzing the data via SmartPLS. Further details to
measures, measurement, composite reliability (CR), Average Variance Extracted
(AVE), and Cronbach’s Alpha (CA) are shown in Table 4 (see Appendix).
With a coefficient of determination (R²) of 0.385 the model can be regarded as
sufficient according to Chin [33]. All constructs exceeds the recommended threshold
for the common quality criteria like CR, AVE and CA as mentioned in chapter 3.
Regarding Hypothesis 1, (An Improvement of Efficiency Positively Influences
the Potential Value of Digitization) the results of the SEM show that efficiency
positively affects (+0.456) the potential value of digitization on a high significance
level (p = 0.00 < 0.01). Therefore, the hypothesis can be confirmed. This underlines
that companies can increase their efficiency by digitizing their value creation processes.
The influence of enhanced innovation processes on the potential value of digitization
was discussed in Hypothesis 2 (An Improvement of Innovation Processes Positively
Influences the Potential Value of Digitization). With a value of +0.095, a positive
influence could be proven. However, the influence is not significant (p = 0.153 > 0.1)
which leads to the rejection of the hypothesis.
Hypothesis 3 (Data Security Positively Influences the Potential Value of
Digitization) investigates the influence of data security on the potential value of
digitization. Based on the results, the hypothesis had to be rejected due to a negative
value (-0.035). A possible reason for the negative value could be attributed to
companies estimating their data privacy adequately and, as a result, not feeling
threatened by the emerging risks of digitization.
The evaluation of Hypothesis 4 (An Improvement of Mobility Positively
Influences the Potential Value of Digitization) shows a positive (+0.094) and
significant (p = 0.098 < 0.1) effect of enhanced mobility on the potential value of
digitization. Hence, the hypothesis can be confirmed. In addition, the survey revealed
that more than 89 % of the companies are using mobile computing applications.
Fig. 2. Structural equation model with coefficients
Furthermore, about 70 % are using cloud computing. Companies are able to increase
their mobility by using these technologies.
The influence of new business models on the potential value of digitization was
discussed in Hypothesis 5 (The Generation of New Business Models Positively
Influences the Potential Value of Digitization). In accordance to the SEM results, a
positive (+0.130) and significant effect (p = 0.048 < 0.05) could be detected. Therefore,
the hypothesis can be confirmed as well. The survey further showed that more than 50
% of the participants have already changed their own business model because of the
digital transformation while others (22 %) are planning to change their business model
in the future.
The results of Hypothesis 6 (Human Involvement Positively Influences the
Potential Value of Digitization) show a positive effect (+0.072) of human
involvement on the potential value of digitization. The influence, however, is not
significant (p = 0.272 > 0.1). Therefore, the hypothesis must be rejected. More than 63
% of the participants thought that employees show a medium or high level of
acceptance regarding the emerging digital technologies. More than 51 % estimated that
employees will not lose their jobs because of the digitization.
Important values of the SEM regarding path coefficients, t-statistics and p-values are
shown in Table 3. For single-item sets, which are widely used in research, there is no
need to calculate metrics like Cronbach’s alpha [35]. The potential of digitization is
shortened as PD.
Table 3. SEM Coefficients
Hypo-
thesis
SEM-Path Path
T
Statistic
Significance
(P Values)
H1 Efficiency PD +0.456 6.108 0.000
H2 Innovation PD +0.095 1.430 0.153
H3 Data Security PD -0.035 0.626 0.531
H4 Mobility PD +0.094 1.657 0.098
H5 New business models PD +0.130 1.982 0.048
H6 Human involvement PD +0.072 1.099 0.272
5 Conclusion
In future, the digital transformation will continue to change business in all areas and
sectors worldwide [36]. For companies, it is inevitable to adapt to the far-reaching
changes caused by digitization. The term digitization already appeared in the course of
the third industrial revolution and was seen as a conversion process from analog to
digital. It is associated with smart value creation processes using capable information
and communication technologies. Thus, digitization aspects become far more complex
and definitions regarding the term of digitization have changed at a tearing pace.
In the course of this, firms have to decide on their own how to benefit from new
technologies caused by digitization. The results within this research, however,
empirically show six hypotheses (efficiency, innovation, data privacy, mobility, new
business models and human integration) which can be used to underline the potential
value of digitization aspects within firms. Thus, digitization can help companies to
significantly increase their efficiency. In addition, new business models arise through
digitization and enable new possibilities to satisfy changing customer requirements.
Furthermore, companies can enhance their mobility by using digital technologies like
mobile computing and cloud computing. Despite the increasing numbers of cyber-
attacks, like data theft and sabotage, it is surprising that data security has no significant
influence on the potential value of digitization within this examination. Although the
improvement of innovation processes, as well as human integration both do not have a
significant influence on the potential value of digitization within this study, the overall
research results show tremendous arguments to integrate digitization technologies
within business processes.
As with all studies, there are some limitations to consider. The sample size, the
investigation period from June to August 2016 and the geographical area of German-
speaking countries limit the research. In addition, the research only investigated the
direct effect of determinants found through literature on the cross-industry potential
value of digitization. The authors recommend to extend the model for future research
by operationalizing control variables in order to shrink possible disturbing errors. For
instance, it might be possible that firm and/or industry specifics effect the potential
value of digitization.
Regarding the theoretical implications of this study, scientists should finally extend
these parameters for further investigations in order to optimize the measurement model.
In particular, it would be useful to focus on further quality criteria as mentioned to
evaluate the model with respect to reliability and validity. Further exploration of this
study may assist in the intention of a better understanding regarding the term
digitization and the main potentials of digitization for business. With respect to
practical implications, managers as well as (IT) consultants can use these study results
to argue why to integrate digitization aspects in order to optimize business processes
and to enhance business strategies.
References
1. Prins, C., Broeders, D., Griffioen, H., Keizer, A.-G., Keymolen, E.: iGovernment.
Amsterdam University Press, Amsterdam (2011).
2. Boes, A.: Dienstleistung in der digitalen Gesellschaft: Beiträge zur
Dienstleistungstagung des BMBF im Wissenschaftsjahr 2014. Campus, Frankfurt
am Main (2014).
3. Bundesministerium für Wirtschaft und Energie: Zukunftschance
4. Digitalisierung Ein Wegweiser. http://www.mittelstand-
digital.de/MD/Redaktion/DE/PDF/broschuere-zukunftschance-
digitalisierung,property=pdf,bereich=md,sprache=de,rwb=true.pdf, last accessed
2017/07/21.
5. Härting, R., Reichstein, C., Jozinović, P.: The Potential Value of Digitization for
Business Insights from German-speaking Experts, in: Eibl M, Gaedke M.:
Informatik 2017, 47. Jahrestagung der Gesellschaft für Informatik, Lecture Notes
in Informatics (LNI), Gesellschaft für Informatik, Bonn (2017).
6. Härting, R.: Elektronischer Geschäftsverkehr aus Sicht privater Haushalte. Gabler,
Wiesbaden (2000).
7. Schmidt, R., Möhring M., Härting, R., Reichstein, C., Neumaier, P., Jozinović, J.:
Industry 4.0 Potentials for Creating Smart Products: Empirical Research Results,
in: Abramowicz, W., Kokkinaki, A. (2015): 18th International Conference on
Business In-formation Systems, Lecture Notes in Business Information Processing,
Springer, Volume 208, pp. 16-27 (2015).
8. Härting, R., Schmidt, R., Möhring, M., Reichstein, C., Neumaier, P., Jozinović, P.:
Nutzenpotenziale von Industrie 4.0: Einblicke in aktuelle Studienergebnisse.
Books on Demand, Norderstedt (2015).
9. Loebbecke, C., & Picot, A.: Reflections on societal and business model
transformation arising from digitization and big data analytics: A research agenda.
The Journal of Strategic Information Systems, 24(3), pp. 149-157 (2015).
10. Kagermann, H.: Change Through Digitization Value Creation in the Age of
Industry 4.0. In: Albach, H., Meffert, H., Pinkwart, A., Reichwald, R. (eds.):
Management of Permanent Change, pp. 2345. Springer,Wiesbaden (2015).
11. Tilson, D., Lyytinen, K., Sørensen, C.: Digital Infrastructures: The Missing IS
Research Agenda. Information Systems Research 21(4), pp. 748759 (2010).
12. Schröder, C., Schlepphorst, S., Kay, R: Relevance of the Digitalization for the
German Mittelstand (IfM), Bonn (2015).
13. Kuhlmann, M., Schumann, M.: Digitalisierung fordert Demokratisierung der
Arbeitswelt heraus. In: Hoffman, R., Bogedan C. (eds.): Arbeit der Zukunft:
Möglichkeiten nutzen-Grenzen setzen, pp. 122140. Frankfurt/New York (2015).
14. Brettreich-Teichmann, W., Grötecke, J.: Wohin treibt die Digitalisierung die IT-
Organisation? HMD Praxis der Wirtschaftsinformatik 53(1), 12 (2016).
Weber, A.: Die Digitalisierung des Kulturerbes der Deutschen aus dem östlichen
Europa, https://opus4.kobv.de/opus4-bib-info/frontdoor/index/index/docId/1579,
last accessed 2017/07/23.
15. Uskov, V., Howlett, R.J., Jain, L.C.: Smart Education and e-Learning. Springer
Wien (2016).
16. Chun, S. A., Shulman, S., Sandoval, R., Hovy, E.: Government 2.0: Making
connections between citizens, data and government. Information Polity 15(1), 19
(2010).
17. Bertalanffy, L. v.: General System Theory. George Braziller, New York (1968)
18. Roland K.: Modelling Ontology Use for Information Systems. Springer, Wien
(1973).
19. Härting, R., Mohl, M., Bader, S.: Digitalisierung als Treiber für Marketing 4.0. In:
Härting, R. (ed.): Industrie 4.0 und Digitalisierung Innovative Geschäftsmodelle
wagen! Tagungsband, 8. Transfertag, Aalen 2016, pp. 134150. Books On
Demand, Norderstedt (2016).
20. Agarwal, R., Gao, G., DesRoches, C., Jha, A.K.: The Digital Transformation of
Healthcare: Current Status and the Road Ahead. Information Systems Research
21(4), pp. 796809 (2010).
21. Nambisan, S.: Information Technology and Product / Service Innovation: A Brief
Assessment and Some Suggestions for Future Research. Journal of the Association
for Information Systems 14 Special issue, pp. 215226 (2013).
22. Dellarocas, C.: The digitization of word of mouth: Promise and challenges of
online feedback mechanisms. Management science, 49(10), pp. 1407-1424 (2003).
23. Lusch, R. F., Vargo, S. L., Tanniru, M.: Service, value networks and learning.
Journal of the academy of marketing science, 38(1), pp. 19-31 (2010).
24. Keuper, F., Hamidian, K., Verwaayen, E., Kalinowski, T., Kraijo, C.:
Digitalisierung und Innovation: Planung Entstehung
Entwicklungsperspektiven. Springer Gabler, Wiesbaden (2013).
25. McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D.: Big data.
The management revolution. Harvard Bus Rev, 90(10), pp. 61-67 (2012).
26. Knoll, M., Meinhardt, S.: Mobile Computing: Grundlagen Prozesse und
Plattformen Branchen und Anwendungsszenarien. Springer Vieweg, Wiesbaden
(2016).
27. Sabbagh, K., Friedrich, R. O. M. A. N., El-Darwiche, B. A. H. J. A. T., Singh, M.
I. L. I. N. D., & Koster, A. L. E. X.: Digitization for economic growth and job
creation: Regional and industry perspective. The global information technology
report, 35-42 (2013).
28. Frey, C.B., Osborne, M.A.,
http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employ
ment.pdf, last accessed 2017/07/24.
29. Babbie, E.: The practice of social research. Cengage Learning, Boston (2012)
30. LimeSurvey GmbH, https://www.limesurvey.org/de/, last accessed 2017/05/21.
31. Hooper, D., Coughlan, J., Mullen, M.: Structural equation modelling: guidelines
for determining model fit. Electronic Journal of Business Research Methods 6(1),
53–60 (2008).
32. Wong, K.K.-K.: Partial least squares structural equation modeling (PLS-SEM)
techniques using SmartPLS. Mark. Bull. 24, pp. 1–32 (2013).
33. Chin, W.W.: The partial least squares approach to structural equation modeling.
Mod. Methods Bus. Res. 295, pp. 295336 (1998).
34. Hewson C., Yule, P., Laurent, D., Vogel, C.: Internet research methods: A practical
guide for the social and behavioural sciences. Sage, London/Thousand Oaks/New
Dehli (2003).
35. Ringle, C.M., Sarstedt, M., Straub, D.: A critical look at the use of PLS-SEM in
MIS Quarterly. MIS Quarterly 36(1), iiixiv (2012).
36. PricewaterhouseCoopers AG: Die Digitalisierung verändert Unternehmen welt-
weit und branchenübergreifend. http://www.pwc.de/de/digitale-transfor-
mation/die-digitalisierung-veraendert-unternehmen-weltweit-und-branchenueber-
greifend.html, last accessed 2017/01/21.
37. Homburg, C., & Baumgartner, H.: Beurteilung von Kausalmodellen:
Bestandsaufnahme und Anwendungsempfehlungen, Marketing Zeitschrift für
Forschung und Praxis, 17, 3, pp. 162-176 (1995).
38. Sen, R., & Borle, S.: Estimating the contextual risk of data breach: An empirical
approach. Journal of Management Information Systems, 32(2), pp. 314-341 (2015).
39. Kagermann, H.: Change through digitizationValue creation in the age of
Industry 4.0. In Management of permanent change (pp. 23-45). Springer Gabler,
Wiesbaden (2015).
40. Bagozzi, R. P., & Yi, Y.: On the evaluation of structural equation models. Journal
of the academy of marketing science, 16(1), pp. 74-94 (1988).
Appendix
Table 4. Measures, measurement, composite reliability (CR), Average Variance Extracted
(AVE), and Cronbach’s Alpha (CA)
Measures Measurement CR AVE CA
Efficiency
How do you estimate the potential benefits of
digitalization with regard to increased
efficiency in companies generally?
Single Item n/a n/a n/a
Innovation
How do you assess the potential benefits of
digitization for optimizing innovation processes
in companies in general?
Single Item
n/a
n/a
n/a
Data Security
How high do you estimate the following risks
of digitization in companies in general?
sabotage
data theft
formative
measurement .93 .87 .86
Mobility
How do you estimate the potential benefits of
digitalisation with regard to increase the
mobility of companies in general?
Single Item
n/a
n/a
n/a
New business models
How do you estimate the potential benefits of
digitalization in terms of the emergence of new
business models?
Single Item n/a n/a n/a
Human involvement
How do you estimate the acceptance of
employees with regard to the emerging digital
technologies in your company?
Single Item
n/a
n/a
n/a
Potential Value of Digitization
How do you generally assess the potential
benefits of digitization in companies?
Single Item n/a n/a n/a
... As shown in Figure 2, the study identifies 9 main drivers for industrial development in the digital age [12]. Another study, published by Reichstein et al., claims that "firms must decide on their own how to benefit from new technologies caused by digitization" [13] (p. 294). ...
... Another study, published by Reichstein et al., claims that "firms must decide on their own how to benefit from new technologies caused by digitization" [13] (p. 294). Based on online interviews with more than 200 experts from the ITC sector (mainly from SMEs) within German-speaking countries (Germany, Austria and Switzerland), they tested six hypotheses regarding the impact of "efficiency, innovation, data privacy, mobility, new business models and human integration on the potential value of digitization aspects within firms" [13] (p. 289). ...
... Based on online interviews with more than 200 experts from the ITC sector (mainly from SMEs) within German-speaking countries (Germany, Austria and Switzerland), they tested six hypotheses regarding the impact of "efficiency, innovation, data privacy, mobility, new business models and human integration on the potential value of digitization aspects within firms" [13] (p. 289). In their study, Reichstein et al. have identified six working hypotheses: (1) "An improvement of efficiency positively influences the potential value of digitization" [13] (p. 289); (2) "An improvement of innovation processes positively influences the potential value of digitization" [13] (p. 289); (3) "Data security positively influences the potential value of digitization" [13] (p. 290); (4) "An improvement of mobility positively influences the potential value of digitization" [13] (p. 290); (5) "The generation of new business models positively influences the potential value of digitization" [13] (p. 290); (6) "Human involvement positively influences the potential value of digitization" [13] (p. 291). ...
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Increases in productivity and competitiveness of an economy are based mostly on the actions of companies in terms of providing technical capital to workers and of operations efficiency (management, financial, recruitment, finding markets and suppliers, internal and external communication, etc.) through digitalization. This paper deals with the way in which the economies and companies in Central and Eastern European (CEE) countries manage to adapt to the trend that started, mostly after 2000, in digitalization; also, it analyzes the extent to which an increase in the degree of business upgrading via integrating digital technology into the business model leads to a surge in economic performances (productivity, exports) and, consequently, to a greater attractivity to foreign capital flows.
... Digitalization creates new business processes and models, i.e., the creation of new products, and services (Koivisto, 2020). Digital strategy has a significant impact on an organization including effects on the business model, operational model, organization structures, and the resources of the organization (Reichstein C. H., 2018). Often the terms digital transformation and digitalization are used interchangeably (Reis, 2018). ...
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One of the most important measures of a company's growth and financial success is its level of digital maturity. Digitization is becoming increasingly vital for businesses in the modern day. Companies frequently want information regarding their existing level of digitalization or, at the very least, their potential for digitalization. Enterprise Architectures can assist a company's information structures in displaying integrated information models and can investigate whether existing company architectures already contain maturity models for determining the degree of digitization, or if such models can be integrated with the help of enterprise architecture frameworks. The objective of this paper is to research if the maturity models are already considered in enterprise architecture and to propose a prototype construct to an enterprise architecture model, with the addition of a business model canvas as a tool to improve the digital maturity.
... Digitalization is a key driver of transformation processes and of great relevance to companies [3]. In general, digitalization includes intelligent business processes and the use of efficient and new technology concepts such as Big Data, Cloud and Mobile Computing or Internet of Things [4]. As digital transformation can be considered the currently dominating type of business transformation, IT components play an essential role. ...
Article
Digital transformation has an increasing influence on business processes and new business models. A successful digital transformation in enterprises requires a holistic IT infrastructure in order to meet changing business requirements. Enterprises face the challenge of combining business and IT to benefit from existing technological attainments in the digital age. As Enterprise Architecture Management (EAM) is supposed to support companies’ transformation processes, it has consequently moved into the focus of large companies and small and medium-sized enterprises. Previous studies have considered the benefits of EAM taking not into account factors regarding the digital transformation process. The present study is therefore intended to close this gap. This article builds on a conceptual model based on a qualitative design with case studies. It presents a quantitative study that investigates the empirical relation between several indicators and the dependent variable “Benefits of EAM” in the digital transformation process. The results show that the indicators “IT Landscape”, “Internal Business” and “EAM Establishment” positively and significantly influence the benefits of EAM in the digital transformation process.
... Rauter R., et al. [15] studied the impact of digitization on innovative business models, changing company values, and analyzed the challenges posed by business digitalization. Reichstein C., et al. [16] conducted the research of the digitization impact on the innovation performance, data privacy, mobility and new business models. The above scholars have made a significant contribution to the development of theoretical foundations of digitization; however, there is still a need to systematize features of the economic activity and managing businesses under the influence of digitization. ...
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Global digitization forces modern enterprises to respond to the rapid changes in the external environment and adapt to it. As a result, existing business models are being transformed in the areas of production, promotion, communication, calculations, interaction with partners and consumers. In this context, there is growing scientific interest in exploring theoretical and practical aspects of the economy digitization and its impact on the peculiarities of the economic entities functioning. Features of functioning of classical and digital economic entities on the basis of criterion approach have been investigated, using the following criteria: factors of production, form of business organization, location of workplace, production outcome, economic processes, connection with on-demand economy, methods of payment, relations with other enterprises, professions enhancing the image of the enterprise, communication method between employees, saving and processing of information, company promotion tools and consumer communication. The main statistical indicators of the digitalization impact on the activity of enterprises in the world and in Ukraine in 2018 have been analyzed. The feasibility of using digital economy tools has been outlined. Advantages and disadvantages of the impact of digital transformation space on the enterprise have been identified.
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Economy and society today face a multitude of complex challenges (“grand challenges”) like climate change, demographic change, urbanization, or digitalization, which create a constant demand for new technologies, services, business models, and consequently innovative solutions. In this light, the mobility sector has undergone a great change over the past few years, which is formed by digital technologies on a large scale. Against this background, this article will demonstrate, based on the example of the iCity research project, to what extent the research design of transdisciplinary living labs can serve as a basis for the development of innovative and sustainable mobility solutions. At the same time, the influence of digitalization which plays a major role in developing real implementable solutions for such challenges will be examined.
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Provides a nontechnical introduction to the partial least squares (PLS) approach. As a logical base for comparison, the PLS approach for structural path estimation is contrasted to the covariance-based approach. In so doing, a set of considerations are then provided with the goal of helping the reader understand the conditions under which it might be reasonable or even more appropriate to employ this technique. This chapter builds up from various simple 2 latent variable models to a more complex one. The formal PLS model is provided along with a discussion of the properties of its estimates. An empirical example is provided as a basis for highlighting the various analytic considerations when using PLS and the set of tests that one can employ is assessing the validity of a PLS-based model. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Die Digitalisierung ist einer der Megatrends und Innovationstreiber des 21. Jahrhunderts. Namhafte Autoren aus Wissenschaft und Praxis diskutieren aktuelle Konzepte, Strategien und Instrumente zum Aufbau „digitaler Ökosysteme“ und nachhaltiger Wettbewerbsvorteile in der „digitalen Welt“. Zahlreiche Interviews mit Persönlichkeiten und Entscheidungsträgern aus der digitalen Welt geben dem Leser zudem interessante Einblicke in den Entwicklungsstand, die Erfolgsfaktoren, die zukünftigen Herausforderungen und die angedachten bzw. bereits in Umsetzung befindlichen Initiativen. Der Inhalt • Strategische Stoßrichtungen und Geschäftsmodelle in der Digital Economy • Auswirkungen und Potenziale der Digitalisierung in unterschiedlichen Branchen • Technologische Trends in der Digital Economy • Innovationsentwicklung und -management in der Digital Economy Die Zielgruppen • Praktiker, insbesondere aus den Bereichen Unternehmensplanung, Strategie, E-Business, New Media • Dozenten und Studenten aus den Bereichen E-Business und Unternehmensführung Die Herausgeber Prof. Dr. Frank Keuper ist Inhaber des Lehrstuhls für Betriebswirtschaftslehre, insbesondere Konvergenzmanagement und Strategisches Management, an der Steinbeis-Hochschule Berlin. Weiterhin ist er Direktor des Steinbeis Center of Strategic Management. Kiumars Hamidian ist Geschäftsführer und Partner bei der BearingPoint GmbH und verantwortet firmenweit die Service Line IT Advisory mit den Schwerpunkten IT-Strategie und Application Transformation Services. Eric Verwaayen ist Partner bei der BearingPoint GmbH im Bereich IT Advisory mit dem Schwerpunkt auf Application Transformation und Platforms. Torsten Kalinowski ist Senior Manager bei der BearingPoint GmbH im Bereich IT Advisory mit dem Schwerpunkt auf Application Transformation. Christian Kraijo ist Senior Consultant bei der BearingPoint GmbH im Bereich Marketing, Sales & Customer Services mit dem Schwerpunkt auf Automotive After-Sales und Digitalisierung.
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Das Herausgeberwerk zeigt, welche Auswirkungen der Einsatz von mobilen Endgeräten auf betriebliche Abläufe hat und wie Anwendungsszenarien in verschiedenen Branchen aussehen können. Hierzu werden u. a. Beispiele aus dem Personalmanagement und dem Gesundheitswesen vorgestellt. Experten aus Wissenschaft und Praxis diskutieren Fragen rund um das Mobile Enterprise ebenso, wie die Gestaltung mobiler Prozesse im ERP und mobiles e-Learning. Dieser Band bietet damit all jenen Lesern und Wissenschaftlern neue Einsichten, die sich für das Thema mobile Anwendungen umfassend interessieren. Der Inhalt Mobile Enterprise – Sichere mobile Unternehmensanwendungen – Sicherer Einsatz mobiler Endgeräte im Unternehmen – Mobile Prozesse im ERP – Mobile Device Management – Mobile Anwendungen im Personalmanagement – Mobile Anwendungen im Gesundheitswesen – Mobile Contracting – Mobile e-Learning Die Zielgruppen - IT-Fach- und Führungskräfte - Lehrende und Studierende der (Wirtschafts-)Informatik Die Herausgeber Prof. Dr. Matthias Knoll, CISA, ist seit 2006 Professor für Betriebswirtschaftslehre an der Hochschule Darmstadt. Sein Lehrgebiet ist die betriebliche Informationsverarbeitung mit den Schwerpunkten IT-GRC-Management, IT-Prüfung, IT-Controlling und Data-Warehousing/BI. Bis zur Berufung an die Hochschule Darmstadt war er im IT-Bereich bei einem großen Finanzdienstleister tätig. Seit 2011 ist er Mitherausgeber der HMD, aus der die vorliegende Reihe „Edition HMD“ hervorgegangen ist. Dipl. Kfm. Stefan Meinhardt, ist seit 1988 Mitarbeiter der SAP SE in Walldorf. Als Prokurist und Geschäftsbereichsleiter im Bereich SAP Global Service und Support verantwortet er aktuell die Industrien: Konsumgüter, Chemie, Pharma, Energieversorgung, Telco, Medien sowie alle Services-Branchen. In seiner langjährigen Karriere bei SAP hat er bereits eine Vielzahl von Fach- und Führungsaufgaben in der Entwicklung, im Service und im Vertrieb wahrgenommen. Seit 1997 ist er Mitherausgeber der HMD.
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In der Diskussion um den elektronischen Geschäftsverkehr stehen vor allem zwei Punkte im Vordergrund: das Schaffen von Effizienzvorteilen gegenüber dem traditionellen Handel und das Erschließen neuer Märkte durch Zusatzdienste. Die Erwartungen der Konsumenten finden dagegen wenig Beachtung. Ralf-Christian Härting untersucht auf informationsökonomischer Basis Chancen und Risiken des elektronischen Geschäftsverkehrs aus der Sicht privater Haushalte und leitet Anforderungen an eine konsumentengerechte Realisierung ab. Der zunehmende Einfluss von Transaktionskosten und die Orientierung an den Bedürfnissen der Verbraucher spielen dabei eine wichtige Rolle.
Chapter
Digitization—the continuing convergence of the real and the virtual worlds will be the main driver of innovation and change in all sectors of our economy. The exponentially growing amount of data and the convergence of different affordable technologies that came along with the definite establishment of Information and Communication Technology are transforming all areas of the economy. In Germany, the Internet of Things, Data and Services plays a vital role in mastering the energy transformation, in developing a sustainable mobility and logistics sector, in providing enhanced health care and in securing a competitive position for the leading manufacturing industry. This article discusses the impact, challenges and opportunities of digitization and concludes with examples of recommended policy action. The two key instruments for enhanced value creation in the Age of Industrie 4.0 are platform-based cooperation and a dual innovation strategy.