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Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace

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Abstract

Futurists predict that a third of jobs that exist today could be taken by Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA) by 2025. However, very little is known about how employees perceive these technological advancements in regards to their own jobs and careers, and how they are preparing for these potential changes. A new measure (STARA awareness) was created for this study that captures the extent to which employees feel their job could be replaced by these types of technology. Due to career progression and technology knowledge associated with age, we also tested age as a moderator of STARA. Using a mixed-methods approach on 120 employees, we tested STARA awareness on a range of job and well-being outcomes. Greater STARA awareness was negatively related to organisational commitment and career satisfaction, and positively related to turnover intentions, cynicism, and depression.

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... Third, some studies have focused on the negative impacts of AI development on employees' psychology and behavior. For example, Duan and Guo speculated that many employees may experience disappointment due to unemployment caused by AI [9]; Zhu et al. found that the application of AI trigger employees' negative emotions [10]; Wang et al. found that employees are faced with high job insecurity due to large-scale utilization of AI technology [11]; Patel et al. found that the risk of job automation caused by AI technology harms employees' health [12]; Brougham and Haar [13,14] and Li et al. [15] found that the likelihood of AI impacting employees' career prospects was negatively related to organizational commitment and career satisfaction and positively related to turnover intentions, cynicism, and depression; Zhou et al. speculated that the technical attributes of algorithmic management that integrate big data and AI positively affect employees' sense of unfairness in algorithms, which in turn induces job burnout [16]; and liu et al. speculated that online employment platforms strengthen the labor-process control of platform practitioners through algorithm technology, which makes platform practitioners' work autonomy limited [17]. Fourth, other studies have explored the positive effects of AI development on employees' psychology and behavior. ...
... Negative impacts of AI development on employees' psychology and behavior Triggers employees' negative emotions [10]; increases employee job insecurity [11]; harms employees' health [12]; reduces employees' organizational identity and career satisfaction, and increases their turnover intention, cynicism, and depression [13][14][15] Increases employee disappointment [9]; induces job burnout [16]; strengthens labor-process control [17] Positive impacts of AI development on employees' psychology and behavior Employees thrive at work [18]; which enhances employees' job performance [19] Improves job autonomy [16,20] Our literature review indicates that, despite the negative impacts brought by the development and wide popularization of AI technology on employees, such as the considerable threats to employees' employment, income, and autonomy [9,17], as a new type of intelligence, AI technology not only can improve the production efficiency of different industries and the skill level of employees but also create new industries and jobs [8,9,21]. In the process, those who have mastered the relevant knowledge and skills required in the age of AI are likely to benefit [22,23]. ...
... However, Zhu et al. argued that pursuing improvements to job skills relevant to AI is conducive for employees to eliminate repetitive and complicated work, resulting in a pleasant psychological experience, such as feeling competent and thriving at work [18]. Additionally, Brougham and Haar verified that AI threat perception is negatively associated with career satisfaction [13], which means the inverse is true for AI opportunity perception. These research conclusions are consistent with our findings. ...
Article
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Several previous studies have revealed a positive relationship between artificial intelligence (AI) technology development and employees’ employment, income, and job performance. If individuals can seize the opportunity to master the knowledge and skills relevant to the implementation of AI, they could make career progress and improve their workplace well-being (WWB). Based on the transactional theory of stress and resource conservation theory, we constructed a moderated mediation model to explore the relationship between AI opportunity perception and employees’ WWB and examine the mediating factor of informal learning in the workplace (ILW), as well as the moderating factor of unemployment risk perception (URP). Through a survey of 268 employees, our results showed the following: (1) AI opportunity perception was significantly positively correlated with employees’ WWB; (2) ILW played a mediating role in the positive relationship between AI opportunity perception and employees’ WWB; and (3) URP negatively moderated the mediating relationship of ILW between AI opportunity perception and employees’ WWB. Our research results have a guiding significance for enterprises seeking to promote WWB during AI application.
... That is, employee's turnover intention increases with insufficient levels of support, feedback, recognition, and reward by the organization, and is linked with the anxiety of employment displacement. Brougham and Haar [11] examined the relationship between STARA (e.g., smart technology, AI, robotics, and algorithms) awareness amongst hospitality employees and the job outcomes. They found a significant positive relationship between AI awareness, fear of job loss, organizational commitment, and wellbeing. ...
... In analyzing the impact of algorithmic management on turnover intention, it is important to consider other relevant influencing factors. Prior studies show that worker's desire to quit their present job (turnover intention) is positively associated with the degree to which they feel alienated from their workplace [11] and discriminated against [12]. It has been suggested that the implementation of algorithmic management at work may bring about feelings of alienation and loneliness [6], which will cause employees to drift away from their work and thus intend to find a more suitable job. ...
... To achieve the study objectives, an online survey was distributed through Amazon Mechanical Turk in August 2022 targeting hospitality employees residing in the United States by restricting participation to those 18 years or older whose primary work was in the hospitality industry. Validated measures were used to assess all constructs in the hypotheses: STARA [11], work alienation [14], discrimination at work [13], and turnover intention [15]. The survey also included questions about work (e.g., types of work contract, line management, salary) and demographic characteristics (e.g., gender, age, education) to identify potential confounding factors on turnover intention. ...
Chapter
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Employee turnover has been one of the main concerns facing the hospitality industry. This issue seems to be aggravated in artificial intelligence (AI) environment, where AI implementation is associated with pressure, job alienation, and labor replacement, increasing workers’ desire to quit their job. To analyze the relationship between AI awareness, job alienation, discrimination, and turnover intention, an online survey was distributed to hospitality employees ( n = 450). From a series of independent-samples T-tests and regression analyses, this study found employees’ turnover intentions are significantly associated with employees’ concerns of being replaced by AI, perception of job alienation, and workplace discrimination. Importantly, current algorithmically managed workers tend to feel more powerless and discriminated against, and thus have higher turnover intentions. Recommendations for practice and future research are provided.
... In addition, by extension, what might we expect as a reaction from those who have been so replaced? 5 Understanding the sense of replacement as it relates to automation is less straightforward than understanding it in the context of politics. ...
... While there is a dearth of studies aimed at addressing the specific question of the impact of tasks on identity and self-worth, we contend that insofar as occupations are comprised, as we have asserted above, of discernable tasks and their associated roles, it is reasonable to conclude that the loss of such valued tasks and their associated roles would produce negative outcomes even they did not result in overall job loss. Furthermore, beyond these strictly academic considerations of the effects of employment on mental health, identity, and self-esteem, there have also been other texts written in recent years addressing the role of meaningful employment on individuals' sense of selfworth [5,19,22,33]. ...
... While in practice, these ideologies tend to be advocated in tandem, we are focusing here on the former.4 The literature on workers attitudes towards workplace automation includes texts such as Ivanov et al.[20], Nam[28], and Brougham and Haar[5]. ...
Article
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A great deal of theorizing has emerged about the economic ramifications of increased automation. However, significantly less attention has been paid to the potential effects of AI-driven occupational replacement on less measurable metrics—in particular, what it feels like to be replaced. In politics, we see examples of nation-states and extremist groups invoking the concept of replacement as a motivator for political action, unrest, and, at times, violence. In the realm of workplace automation, and in particular, in the case of AI-driven workplace automation, the replacement of human labor with artificial labor is an explicit goal. In this paper, we suggest that, given the effects that the experience of a sense of replacement has in political contexts and the potential for that sense of replacement to motivate unrest and violence, we should be concerned about the widely predicted replacement of workers over the coming decades beyond the potential economic challenges which may arise.
... Critical assets are skilled employees in travel, tourism, and hospitality. However, robots in service areas increase awareness and fears of job loss among employees, or thinking of working with robots (machines) increases negative perception and anxiety toward robots (Brougham and Haar, 2018;Acemoglu and Restrepo, 2018;Granulo et al., 2019;Manthiou et al., 2020). Therefore, we proposed hypothesis 4: ...
... • Two items of robot awareness were taken from Brougham and Haar (2018). ...
... Due to the effectiveness and enlargement in numerous service sectors, tourism, and hospitality sectors, managers focus on considering the customers' demand for service robots and employees' intention toward robots in their organizations (Lin et al., 2021;Kim et al., 2021;Horwitz, 2020). To the extent that mechanical objects such as artificial intelligence, machine learning, and virtual reality, Chatbots accomplish a task more accurately and in comparison with human counterparts' robotic devices do cost lower in sophisticated frontline tasks (Brougham, and Haar, 2018;Ukpabi et al., 2019;Ivanov et al., 2020). However, successful customer support is crucial to assure this innovation for the medium and long term. ...
Article
The impact of the pandemic is driving the recent upsurge in service automation and the adoption of service robots in the hospitality industry. As service paradigm and customer expectations shift from conventional customized and personalized services towards a digitalized service environment, such customer orientation may favor using service robots at scales that could render service employees redundant. This study aims to answer the above question by investigating service employees’ perceptions of service robots. Data solicited from 405 service employees in the United States of America via Amazon’s MTurk were analyzed using structural equation modeling. The result revealed that employees’ awareness of adopting and using service robots significantly impacts their perception of robot-induced unemployment. Further, results indicated that the perception of robots’ social skills significantly influences service employees’ perception of robot-induced unemployment. Employee status was found to moderate the relationships mentioned above. Specifically, entry-level employees perceive the unemployment risk more than managers.
... This chapter uses the acronym STARA to represent the technologies adopted by the businesses. STARA represents Smart technology, artificial intelligence, robotics, and algorithms (Brougham & Haar, 2018). As we commonly know, STARA technologies have been adopted in wide-ranging domains and given rise to the fourth industrial revolution (i.e., Industry 4.0) that has so thoroughly altered daily life for people worldwide. ...
... Indeed, few studies (e.g., Brougham & Haar, 2018;Li, Bonn, & Ye, 2019) have examined how employees' awareness of STARA influences their job satisfaction, organizational commitment, turnover intention, and well-being. When they have, evidence from different contexts has been discouraging. ...
... Despite studies that have actively addressed potential changes in the labor market caused by adopting STARA, its consequences for employees in the workplace have not been fully examined. The concept of STARA awareness developed by Brougham and Haar (2018), which captures employees' perceptions of the likelihood that STARA will influence their future job prospects, reflects employees' perceived job insecurity in the face of STARA's adoption. ...
Chapter
Full-text available
This chapter aims to (1) examine the effect of full-time employees’ STARA awareness on innovative work behavioural intentions in US casual dining restaurants; (2) investigate the mediating roles of employees’ challenge–hindrance appraisals of STARA awareness on the relationship between their STARA awareness and innovative work behavioural intentions; (3) compare the group differences between management employees and non-management employees; and (4) provide recommendations for the casual dining restaurants. This chapter employed an online survey to collect data from 609 full-time employees in US casual dining restaurants, including 306 management employees and 303 non-management employees. Partial least squares–structural equation modelling was applied for data analysis. The results reveal that the high levels of employees’ STARA awareness raise innovative work behavioural intentions through the mediations of challenge appraisal of STARA awareness. The proposed conceptual framework and empirical findings in this chapter enrich the literature of cognitive appraisal theory, transactional model and stress, two-dimensional stressor framework, and person-environment fit theory. Employees’ challenge appraisal of STARA awareness makes the job insecurity stressor to drive innovative work behavioural intentions. As STARA adoption deepens in casual dining restaurants, managers need to be aware of full-time employees’ stress and psychological responses towards STARA adoption. Restaurants are suggested to provide employees with adequate resources and support to help employees’ professional competency growth. The capable employees will appraise the job insecurity stressor induced by STARA adoption as an opportunity and be motivated to perform innovatively in the workplace. The casual dining restaurants may enjoy a competitive advantage in the market through value-added innovative activities.
... AI in service AI technology is revolutionizing service innovation and, therefore, is increasingly applied in service hospitality industry to improve market competitiveness. As seen in hotels, restaurants, and airports, AI guidance robots greet and serve customers, whereas AI chatbots in the hospitality industry provide automated responses to customer inquiries (Brougham & Haar, 2018). AI robots are also used to clean and deliver objects, not only to attract customers and enhance service innovation but also to improve efficiency and corporate profits (Belanche et al., 2020b;Huang & Rust, 2018. ...
... However, research in this direction is still relatively scarce and requires further discussion. The AI introduced by enterprises has squeezed the living space of frontline employees, and the human-machine conflict has gradually come to the fore (Brougham & Haar, 2018). Exploring the relationship between AI and frontline employees has become a popular topic in academia. ...
... The STARA theory was proposed based on the micro-level, focusing on the negative impact of technologies, such as smart technology, artificial intelligence, robotics, and algorithms (Brougham & Haar, 2018). When new technologies (e.g. ...
Article
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The widespread use of artificial intelligence (AI) technology in the service industry has made the conflict between service robots and frontline employees a hot topic. While research shows that the adoption of service robots may have a negative impact on employees’ psychology and behavior, little is known about its effects on frontline employee’ service sabotage. The current study explores the influencing mechanism of service sabotage in the context of AI introduction based on the STARA theory and conservation of resource theory. The results reveal that: (1) Frontline employee’s AI awareness direclty affects service sabotage; (2) Organization-based self-esteem plays a partial mediating role between AI awareness and service sabotage; (3) Perceived organizational support weakens the effect of AI awareness on service sabotage.
... This business output will be the value delivery to the society as well as adds more investment and collaboration with the 4IR ecosystem. The Fourth Industrial Revolution Industry 4.0 implements cutting-edge IT solutions in all parts of manufacturing, enabling not just customer-specific goods but also whole value chains (Brasseur et al., 2017;Brougham & Haar, 2018). Utilizing new information and communication technologies and open innovation, it is feasible to tailor manufacturing more precisely to consumer demands while retaining low prices, high quality, and high efficiency (Deloitte, 2020;Khan et al., 2021) this leads the value delivery to the society shown in figure 3. To do this, businesses collaborate with network partners to create cyber-physical systems. ...
... In contrast, a rise in production rate as a result of industrial automation would be accompanied with greater resource and energy consumption as well as increasing environmental problems (Beier et al., 2017;Liu and Bae, 2018). From the standpoint of societal development, digital transformation and industrial reorganisation are anticipated to significant (Benedikt & Osborne, 2016;Brougham & Haar, 2018). ...
Article
Full-text available
Industry 4.0 (The 4th Industrial Revolution – 4IR) is an emerging ecosystem based on a connection between machines and humans. I4.0 has delivered new production technologies that maximize output while maximizing resource use. An increasing number of companies are reaping the benefits of technological advancements. I4.0 has the potential to provide sustainable industrial value creation across social, economic, and environmental aspects by enhancing resource efficiency. Human advancement, resource utilization, and commercial relationships all fall under the umbrella of sustainable development (SD). Traditional business problem-solving methodologies are being challenged by the I4.0 notion of sustainability, which calls for a shift toward a more systematic and quantifiable approach to dealing with sustainable development. Transformational business models include the triple bottom line and take into account many stakeholders as well as the wider community and environment. social, economic, and mental environment make up the three pillars of long-term viability. It is vital for business models in transforming to value delivery processes for sustainability, making them significant drivers of competitive advantage and overall SD. The paper focus is on the tools and procedures utilized to conduct a thorough examination of these components. This study proposes a quantifiable 4IR framework to map the broad spectrum of sustainable development. This framework is linked with the existing industry 4.0 environment and quantifiable sustainable nodes to measure businesses in the digital era that are potential for sustainable development.
... Artificial intelligence, robotics, algorithms, and other technology advancements have initiated workplace changes, and it has been expected that there would be a growing effect of technology advancement on workplaces [15]. As technology advancement can have a broad impact on workplaces in various ways, we define technology-related workplace changes as adoption or significant changes in information and communication devices, ways of working, and products or services. ...
... As technology advancement can have a broad impact on workplaces in various ways, we define technology-related workplace changes as adoption or significant changes in information and communication devices, ways of working, and products or services. For example, many retail stores have adopted self-checkout systems to replace human employees as they are more cost-efficient [15]. Some experts have predicted that the rapid adoption of new technologies in the workplace will lead to a rise in unemployment (e.g., [16]) and heightened fears of unemployment and financial insecurity (e.g., [17]). ...
Article
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While technological advancements have proliferated in our daily lives, they also pose threats to the job security of employees. Despite these growing concerns about technology-related job insecurity, little research has been carried out on the antecedents and outcomes of tech-related job insecurity. Using a cross-sectional, nationally representative survey sample of 28,989 Korean workers drawn from the Korean Working Conditions Survey, we examined the impacts of technology advancements on employee perceptions of technology-related qualitative job insecurity (i.e., perceived technology-related threat to the continued existence of valued job features) and subsequent effects on employees' work (i.e., work engagement, job satisfaction), health (i.e., sleep), and life (i.e., work-to-family conflict) outcomes. Furthermore, we investigated the extent to which employer-provided (versus self-funded) training buffers the adverse impacts of technology advancements and associated job insecurity. The path analysis results showed more technology changes were associated with higher job insecurity, which subsequently related to adverse outcomes. While employer-provided training helped workers to reduce the negative impacts of tech changes on job insecurity, workers who paid for their training reported more adverse outcomes in face of job insecurity. We discuss these results in light of the job demands-resources theory and practical implications to buffer the adverse impacts of technology advancements.
... Whereas automation implies that machines take over a human task, augmentation means that humans collaborate closely with machines to perform a task (Langer and Landers, 2021). Despite the predictions by many business people and academics, employees do not in general see these novel technologies as a threat to their career (Brougham and Haar, 2018). ...
... In line with previous work in different industries (Brougham and Haar, 2018), teachers were not concerned about being replaced by novel technologies. The general sentiment toward . ...
Article
Full-text available
Novel learning technologies have potential in reshaping the teaching profession by automating some parts of the work. However, teachers' perspectives toward automation have generally been critical. In the present study, we examine Finnish education practitioners' thoughts on adaptive learning technologies and their impact on the teaching profession. Using thematic and epistemic network analysis (ENA), we analyzed 114 social media posts. Supportive posts connected technological capabilities and self-directed or self-regulated learning, emphasizing that technology can also guide and support students. Critical posts connected human presence, educational arrangements, and pupil diversity and equality, emphasizing the importance of teachers' presence in addressing pupils' varying needs. Overall, the role of a human teacher was seen as necessary even with adaptive learning technologies available. Our findings reveal themes relevant when discussing the development of adaptive learning technologies and their potential impact on the teaching profession. Moreover, our findings increase the understanding of how supportive and critical argumentation on technology differ.
... AI and big data could affect non-pecuniary aspects that shape employees' well-being (Kaplan and Schulhofer-Wohl, 2018; Schwabe and Castellacci, 2020) such as expectations, job prospects, career satisfaction, mental health and stress (Brougham and Haar, 2018). When a firm considers the adoption of automation technologies, employees begin to fear that they may become unemployed and face financial difficulties (Schwabe and Castellacci, 2020). ...
... When a firm considers the adoption of automation technologies, employees begin to fear that they may become unemployed and face financial difficulties (Schwabe and Castellacci, 2020). Such uncertainty reduces job satisfaction (Erdogan et al., 2012;Schwabe and Castellacci, 2020) as employees perceive themselves to be undervalued and unappreciated by the employer (Brougham and Haar, 2018;Meyer et al., 1993). Long-term job insecurity can also negatively affect an employee's mental health and increase the probability of psychological stress, nervousness and burnout (Abeliansky and Beulmann, 2019; Chen et al., 2004;Dekker and Schaufeli, 1995). ...
... Consequently, it is worth stating that many physical therapy practices might be susceptible to automation by AI technologies. In the study by Brougham and Haar [12], futurists are quoted as predicting that a third of the jobs that exist today could be taken by smart technology, artificial intelligence, robotics, and algorithms by 2025. ...
... The survey was developed through deep searching in the literature [2,12] and feedback from physical therapy experts. The face validity and content validity of the survey [17,18] were established by inviting 8 PTs who were experts in the field of rehabilitation and survey studies to review and rate each item of the survey for its appropriateness, clarity, ordering, and construct. ...
Article
Full-text available
Background: The use of artificial intelligence (AI) in the field of rehabilitation is growing rapidly. Therefore, there is a need to understand how physical therapists (PTs) perceive AI technologies in clinical practice. Objective: This study aimed to investigate the knowledge and attitude of PTs regarding AI applications in rehabilitation based on multiple explanatory factors. Methods: A web-based Google Form survey, which was divided into 4 sections, was used to collect the data. A total of 317 PTs participated voluntarily in the study. Results: The PTs' knowledge about AI applications in rehabilitation was lower than their knowledge about AI in general. We found a statistically significant difference in the PTs' knowledge regarding AI applications in the rehabilitation field based on sex (odds ratio [OR] 2.43, 95% CI 1.53-3.87; P<.001). In addition, experience (OR 1.79, 95% CI 1.11-2.87; P=.02) and educational qualification (OR 1.68, 95% CI 1.05-2.70; P=.03) were found to be significant predictors of knowledge about AI applications. PTs who work in the nonacademic sector and who had <10 years of experience had positive attitudes regarding AI. Conclusions: AI technologies have been integrated into many physical therapy practices through the automation of clinical tasks. Therefore, PTs are encouraged to take advantage of the widespread development of AI technologies and enrich their knowledge about, and enhance their practice with, AI applications.
... Esta preocupación trae consecuencias negativas el rol de la conciencia de los empleados sobre la inteligencia artificial Revista Facultad de Ciencias Económicas ■ Vol. 30(1) para los individuos como depresión, indiferencia, reducción de compromiso organizacional y baja satisfacción (Brougham y Haar, 2018). ...
... 30(1) estas nuevas adaptaciones. La conciencia acerca de la inteligencia artificial y la robotización se refiere al nivel en que estos consideran que tales elementos afectan sus perspectivas profesionales y sus empleos actuales (Arias-Pérez y Vélez-Jaramillo, 2021; Li et al., 2019); además, las ven como amenazas para su trabajo actual o inclusive para su industria, lo que incrementa la resistencia interna a las tecnologías nuevas que provienen de conocimientos externos (Brougham y Haar, 2018;Lichtenthaler, 2019). ...
Article
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A escala mundial las empresas siguen avanzando en la implementación de inteligencia artificial y robotización para el desarrollo tecnológico y la innovación de productos y servicios; sin embargo, para lograrlo con éxito se encuentran con obstáculos internos, como el sabotaje de conocimientos y el síndrome no inventado aquí, que perjudican el desarrollo de nuevos productos. Este estudio analiza la relación entre el sabotaje de conocimientos, el síndrome no inventado aquí y el desempeño innovador y el efecto moderador de la conciencia en torno a la inteligencia artificial y a la robotización. El testeo del modelo de investigación se realizó mediante ecuaciones estructurales en una muestra de empresas manufactureras de media y baja tecnologías y de servicios de Medellín. Se identificó que el síndrome no inventado aquí influye positivamente en el sabotaje de conocimientos y este actúa negativamente sobre el desempeño innovador. Los hallazgos incrementan la literatura sobre un tema emergente en Colombia como el sabotaje de conocimiento e incentiva las investigaciones alrededor del efecto de la inteligencia artificial y la robotización.
... Nevertheless, new technology has become one of the aspects which create stress on employees in making much negative impact on work relations, employee relations, a feeling towards employment insecurity and also towards the turnover and less motivation and ambiguity of career growth as well (Brougham & Haar, 2018). In current scenario, the new technological trends have added a stress factor to their usual stressors such as family, work life etc, in making them adopted towards the changing technological arena. ...
... Moreover, the researchers have identified that, there are negative effects created by the emerging smart technology in the several key outcome of h=jobs including organizational commitment, career satisfaction, etc. this is enhanced when the employees have awareness on technology, it creates negative relationship. This is further highlighted through the study of Brougham and Haar (2018) discovering that employees' smart technological awareness exhibited a significantly positive effect on intention to turnover. ...
Conference Paper
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This empirical study analyzes the relationship between high tech exports and unemployment. The study is conducted only thirteen years for the period of 2007 – 2019. The data set of high technology exports (% of manufactured exports) and unemployment total (labor force (percentage) – modeled International Labor Organization (ILO) estimate) was gathered from The World Bank. We use covariance analysis, correlation analysis, and cointegration to achieve the goals of this study. The Matrix form of Covariance analysis and Ellipse, Kernel fit of correlation analysis were used it. It was found there is no significant direction between high technology exports and unemployment total. The Augmented Dicky Fuller test has confirmed that those variables were stationary at logarithm first difference. At the same time, the residual series was non-stationary at level form. Therefore, the researcher concludes that there is no long-run relationship between high technology exports and unemployment and the changes in high-tech exports do not affect unemployment worldwide. So, researchers need to find other technical indicators for how to determinant unemployment. Future studies want to find short-run and causality between those two variables and want to include more.
... The acronym STARA (Smart Technology, Artificial Intelligence, Robotics, and Algorithms) is used in some management disciplines to capture the range of digitally enabled technologies, devices, software, systems, and platforms that are affecting employment (Brougham & Haar, 2018). We discuss first the smart physical systems that feature in the digitally connected supply chain, specifically Smart Factories, Smart Warehouses, and Smart Logistics. ...
... There are many challenges in identifying where to apply and how to exploit these approaches to improve business operations and drive innovative strategies (Björkdahl, 2020;Janssen et al., 2017;Kiron & Schrage, 2019). There are significant concerns on ethicality and trust in AI (Ashoori & Weisz, 2019), and the implications for people in such systems (Brougham & Haar, 2018). These aspects need to be part of broader social, political, and economic debates (Dafoe et al., 2021) as digitalization of the supply chain continues. ...
Book
The Digital Supply Chain is a thorough investigation of the underpinning technologies, systems, platforms and models that enable the design, management, and control of digitally connected supply chains. The book examines the origin, emergence and building blocks of the Digital Supply Chain, showing how and where the virtual and physical supply chain worlds interact. It reviews the enabling technologies that underpin digitally controlled supply chains and examines how the discipline of supply chain management is affected by enhanced digital connectivity, discussing purchasing and procurement, supply chain traceability, performance management, and supply chain cyber security. The book provides a rich set of cases on current digital practices and challenges across a range of industrial and business sectors including the retail, textiles and clothing, the automotive industry, food, shipping and international logistics, and SMEs. It concludes with research frontiers, discussing network science for supply chain analysis, challenges in Blockchain applications and in digital supply chain surveillance, as well as the need to re-conceptualize supply chain strategies for digitally transformed supply chains.
... As a result of these types of innovation, it is impossible to imagine prolonging workers in certain positions due to cost advantages. In addition, recent debates emphasize the importance of teams to collaborate digitally and interdependently on set tasks, and for industrial psychologists to develop competencies fundamental to the STARA model, to catalyze innovation initiatives and reduce turnover expectations (Brougham and Haar, 2018;Ding, 2021;Ogbeibu et al., 2021a). ...
... In addition, STARA could have a substantial impact on healthcare (Bloss, 2011;Lorentziadis, 2014), education (for example, through web-based learning), transportation, and farming. In general, STARA threatens to eliminate 47% of occupations (Brougham and Haar, 2018). ...
Article
Full-text available
In the Fourth Industrial Revolution (4IR), STARA (smart technology, artificial intelligence, robotics, and algorithms) is predicted to replace a third of the jobs that exist today. Almost twice as many current work tasks will be handled by robots. It is forecast that by 2025, 85 million jobs may be displaced by a shift in the division of labor between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines and algorithms. Industrial psychologists are playing an increasingly important role in the workplace due to these trends from a strategic intelligence perspective. The objective of this article is to present a critical review of industrial psychologists in future workplaces in the context of the 4IR-STARA. A competence model is posed for industrial psychologists to perform a strategic intelligence role in organizations in the 4IR.
... The acronym STARA (Smart Technology, Artificial Intelligence, Robotics, and Algorithms) is used in some management disciplines to capture the range of digitally enabled technologies, devices, software, systems, and platforms that are affecting employment (Brougham & Haar, 2018). We discuss first the smart physical systems that feature in the digitally connected supply chain, specifically Smart Factories, Smart Warehouses, and Smart Logistics. ...
... There are many challenges in identifying where to apply and how to exploit these approaches to improve business operations and drive innovative strategies (Björkdahl, 2020;Janssen et al., 2017;Kiron & Schrage, 2019). There are significant concerns on ethicality and trust in AI (Ashoori & Weisz, 2019), and the implications for people in such systems (Brougham & Haar, 2018). These aspects need to be part of broader social, political, and economic debates (Dafoe et al., 2021) as digitalization of the supply chain continues. ...
Chapter
Advances in technology, rapid globalization, trade liberalization, and increased regulation have shaped supply chains in the last four decades. We examine the impact of digitalization on contemporary and future supply chains. Digitalization potentially enables a strong digital thread connecting and mirroring an entire physical supply chain. We provide an overview of the principal technologies and systems enabling the Digital Supply Chain, including Smart Factories, Smart Warehouses, Smart Logistics, Cloud-based systems, and digital platforms. We discuss the computational engines enabled by Analytics, Data Science, and Artificial Intelligence and the emerging technologies likely to influence future supply chains—Blockchain, Digital Twins, Internet of Things, 5G, Edge, and Fog computing. The technologies offering the most promise in linking the virtual and physical worlds to improve supply chain performance are noted. We describe an evolving spectrum from digitally immature to digitally enabled and digitally transformed supply chains. We provide both narrow and broad definitions for future Digital Supply Chains. The transformative effects of the digitalization of supply chains will affect supply systems in diverse ways. Data-rich supply chain ecosystems will provide many new opportunities but will also give rise to many challenges that require continued analysis and evaluation by researchers and practitioners.
... Digitalization refers to digital technologies to change a business model and provide managers with new value-producing resources (Annarelli et al., 2021). Digital businesses based on platforms, big data (BD), machine learning, robots, artificial intelligence (AI), metaverse, and algorithms are reshaping the concept of managerial work because they are altering the practices and processes of human decision-making (Sidner et al., 2005;Brougham and Haar, 2018;Sohn and Kwon, 2020). Digital technologies can take over repetitive, complicated, or heavy tasks, which leaves managers to focus more on cognitively or mentally demanding decisions (Demerouti, 2022). ...
Article
Full-text available
Unlike much research on work engagement, there is not much literature focused on managers that discuss their job demands and resources related to digital challenges in today’s organizations. Grounded in the JD-R model and considering the current digital world context, we build four research propositions and offer a work engagement framework that considers the boundary conditions of digital managerial tasks. Our conceptual framework relates the new job demands and resources to digital managerial tasks: digital adoption tasks and digital business model tasks. This conceptual article has theoretical and practical implications for organizational psychology, organizational behavior, and strategic management scholars and practitioners interested in studying managers’ work engagement and digital managerial tasks.
... According to studies, industry 4.0 substantially influences the recruiting industry. In Industry 4.0, robotic systems, autonomous machines, and intelligent devices replace people in various tasks, including inventory monitoring, quality management, and product distribution [28,60]. Furthermore, Industry 4.0 technologies support the TBL ideas through enhanced productivity, monitoring of energy usage, reduced resource consumption, a secure work environment, higher staff satisfaction, and new employment development [61]. ...
Chapter
Recently, Industry 4.0 adoption has gained greater visibility and importance due to its implications for achieving sustainability. However, the lack of studies on adopting Industry 4.0 in Small and Medium Enterprises (SMEs) has motivated the present research to investigate how SMEs integrate digital technologies with their conventional processes to achieve sustainability. To this end, indicators of Industry 4.0 adoption in SMEs were figured out through a literature review; consequently, a novel assessment method under Fermatean fuzzy sets was developed to evaluate five SMEs concerning the identified indicators. To be more specific, the proposed method, firstly, determines the objective weight of the identified indicators using FF-CRITIC; secondly, it evaluates SMEs using FF-TOPSIS. The results indicated that the most critical indicator is “flexible and agile production” out of sixteen identified indicators. Furthermore, a sensitivity analysis was done to evaluate the sensitivity of the proposed method concerning the weight changes.KeywordsSMEsSmart technologiesDigital technologiesAgile manufacturingDigital transformation
... These disruptions might lead to significant impacts on job creation and retention as many roles will have to be re-designed to accommodate the knowledge and skills that embrace these new technologies. Implementing AI within organisations can also lead to lower levels of employee confidence and engagement, if managed improperly (Brougham and Haar, 2018). ...
Article
Artificial Intelligence (AI) is a highly disruptive technology that will have major effects on the business world over the coming years. It has the potential to allow companies to achieve major efficiency gains and a more productive workforce through automating existing processes, providing deeper levels of analytics, providing better customer support, and increasing security. On the other hand, it may lead to lower staff levels and a drop in existing employee morale. Given the complexities of these projects, AI will only benefit organisations if they understand its capabilities in addition to its shortcomings. This investigation addresses the predicted impact on skills, roles and employee morale of artificial intelligence on the workforce of the future as AI continues to become more prevalent in our society. We investigate these impacts of AI specifically across four key industries by engaging in interviews with experts in the field to answer two research questions: (i) What are the core impacts of introducing AI systems in the workplace?, and; (ii) How can organisations develop AI projects for successful transformation? The inclusion strategy for this research were professionals who were highly knowledgeable in the area, and from our findings we were able to identify several impacts that AI made to companies developing these projects; namely employment levels, workforce morale, and process efficiency. With these insights, we subsequently developed a roadmap which contains the recommended steps and decisions that are necessary for successfully introducing AI to an organisation. This roadmap visualises the key decisions and steps that are critical for any AI based initiative for organisations, which will provide practitioners with a higher level of understanding of what is expected, in addition to enabling more effective collaboration with the system developers. Furthermore, this roadmap allows organisations to take a positive and proactive approach to designing these systems with their workforce in mind and to prepares them for the implications with the development, deployment, and use of these AI systems.
... Brougham proposed the extent to which employees expect the new generation of artificial intelligence technologies such as intelligent technology, artificial intelligence, robots, and algorithms to change some workplaces and jobs in the future, namely artificial intelligence awareness. Artificial intelligence awareness refers to the awareness that artificial intelligence machines such as robots and algorithm-management may replace existing jobs in the future, which reflects the uncertain situation harmful to employees [4]. Artificial intelligence awareness is a measure that captures the extent to which employees believe that their job security and occupation or industry may be replaced by technologies such as artificial intelligence and automation [5]. ...
... Along these lines, a plethora of studies have documented that any new technology can amplify work pace and is associated with increasing worker stress, overload, and burnout [13][14][15]. Finally, research has shown that the introduction of advanced technologies, including those that use forms of artificial intelligence, are often perceived as a threat to employees' jobs and can negatively impact well-being [16]. Consequently, an empirical examination of employee perceptions and implementation practices is necessary to support organizational adoption and employee confidence in new technologies [17] and to preserve the well-being of workers [18]. ...
Article
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Research studying the intersection of occupational safety and health (OSH) and direct reading and sensor technologies (DRST) is sparse, with a specific lack of research available that has empirically considered ways that DRST may impact worker well-being. In this paper, the authors examine how organizations could utilize core elements of their health and safety management system (HSMS) to coordinate and execute DRST in the workplace to support worker well-being. National Institute for Occupational Safety and Health (NIOSH) researchers developed a 39-item questionnaire targeting OSH professionals to understand attitudes toward DRST and the current and intended uses of DRST at their place of employment. Eighty-eight OSH professionals completed the questionnaire between August and December 2021. Descriptive results of the study sample are provided but the focus of the study applies the open-ended responses to two questions, which was deductively analyzed. Descriptive results show that reliability and validity of data was a top concern while the open-ended qualitative feedback revealed three primary themes: (1) acceptability and trust in technology; (2) ease of use; and (3) support and guidelines. Results provide an opening to use core HSMS elements (i.e., management commitment and leadership, communication and coordination, and employee involvement) during DRST integration to demonstrate support for workers during times of ambiguity and change.
... For example, the data utilized for machine learning can either be supervised, in which the data are accompanied by associated information such as labels, or unsupervised, in which the data are presented in their raw form and require the discovery of patterns without prior prompting. This includes the process of reinforcement learning, in which machine-learning algorithms actively select their training material and can even generate their own (Brougham & Haar, 2018). ...
Article
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The consequences of this new technology for international trade have recently garnered much attention, thanks to the growing interest in AI's effects on the economy and society. Given the current reevaluation of the advantages of globalization by the world's leading nations, the focus continues to be on the policies governing international commerce. Understanding and forecasting future trade patterns is a high priority for decision-making within and between countries. This is because trade significantly impacts employment, production, pricing, and wages. Even though conventional economic models are intended to be accurate forecasters, we investigate the prospect that Artificial Intelligence (AI) techniques can produce more accurate predictions and associations. In addition, we describe contextual AI algorithms that can be used to analyze trade patterns disrupted by unusual occurrences such as trade wars and pandemics. The fuel for the algorithms that can forecast, recommend, and categorize policies can only be provided by open-government data; therefore, having access to these data is vital. The information gathered for this study describes the economic elements usually linked with international trade transactions. Association Rules are used for grouping commodity pairs. Finally, models and their results are presented and then appraised in terms of the quality of their predictions and associations, with example policy implications provided. This paper explores the interlinkages between AI technologies and international trade and outlines key trade policy considerations for policymakers looking to harness AI technologies' full potential. Specifically, the paper focuses on China's efforts to develop its artificial intelligence (AI) industry.
... (Jung et al., 2021;Koo et al., 2021). Brougham and Haar (2018) and Shankar et al. (2021) investigated changes in the retail context as a result of advanced technology. Furthermore, because there must be social or psychological factors to clearly establish and explain the relationships, the effect of intervening buffers must be considered in order to comprehend the variability in employee reactions (Aguiar-Quintana et al., 2021;Chen and Eyoun, 2021). ...
Article
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The study intends to investigate the relationship between work stress and job insecurity, as well as technological changes and job insecurity, with job satisfaction acting as a mediator. The study was conducted among Pakistani retail industry employees using survey questionnaires distributed online and in stores. The sample was composed of 262 retail workers from the FMCG and shopping mall industries. The responses were screened using the statistical software tool SPSS, and hypotheses were examined through SMART-PLS. The findings show that work stress has a strong relationship with job insecurity; additionally, the relationship appears to be statistically significant (β = 55.7%, p < 0.05), indicating that there is an increased level of job insecurity if work stress is increased. However, technological advancements showed less influence on job insecurity and had statistically insignificant results (β = 5.9%, p > 0.05). This demonstrates that many technological changes cause high levels of job insecurity because employees fear that they will be unable to cope with the changing environment. Furthermore, the mediating mechanism of job satisfaction was found to be significant, as employees with lower levels of satisfaction reported higher levels of insecurity, aiding in the narrowing of the gap in this section of the study. The study also has practical implications because the results show that the retail industry needs to act quickly to make sure workers do not worry about losing their jobs, especially now that COVID-19 is spreading like wildfire.
... expectations, job prospects, satisfaction and commitment) and well-being outcomes (e.g. mental health and stress) (Brougham and Haar, 2018). When a firm is considering the adoption of automation technologies, employees begin to fear that these technologies may displace them and thus become unemployed and face financial difficulties in the future (Schwabe and Castellacci, 2020). ...
Article
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Purpose This study examines the propensity to innovate in automation of family firms (FFs) based on the socio-emotional wealth (SEW) perspective. Design/methodology/approach This study’s analysis is based on three aspects. First, the authors consider three main non-economic goals and priorities of FFs: the family’s relationship with employees (read as to care for their satisfaction and well-being); the inner pride of building and maintaining the family and firm image and reputation; and the inner feeling to be socially responsible. Second, the authors consider how these goals and priorities vary among FFs according to four dimensions: family ownership, the presence of family members on the board of directors, the involvement of young successors, and the presence of founding and later generations. Finally, the consequences of automation are considered: lower firm employment, lower employees’ satisfaction and well-being, and higher firm productivity. The analysis is based on a sample of 4,150 Italian firms. Findings The analysis revealed that FFs are less prone to innovate in automation than non-FFs. Specifically, family ownership, the presence of family members on the board of directors, and the presence of founding generation are negatively associated with innovation in automation. Instead, the involvement of young successors and the presence of later generation are positively associated with innovation in automation. Originality/value To the authors’ knowledge, this study is the first investigation that, based on SEW, examines how FFs act on the decision to innovate in automation, thereby providing empirical evidence.
... With the use of information and communication technologies (ICTs), accessing, gathering, sharing, and analyzing information are easier, and workers can find new ways to collaborate and work, regardless of time and place (e.g., Fischer et al., 2018). Thus, altogether, digital changes, such as smart technology, artificial intelligence, robotics, and algorithms (STARA; Brougham & Haar, 2018), "are reshaping the information workers have access to (e.g., real-time data), where people work (e.g., co-working spaces), collaboration patterns (e.g., increasing interaction with robots), and, most fundamentally, people's work designs" (Parker & Grote, 2020, p. 4). Most recently, the coronavirus pandemic has accelerated many of these trends, with the dramatic increase in remote work perhaps being the most visible one (e.g., Brynjolfsson et al., 2020;Lund et al., 2021). ...
Thesis
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Overall, this article-based dissertation has twofold aims – methodological and empirical. First, the methodological aim is to introduce and further develop a qualitative data collection method called the method of empathy-based stories (MEBS). In the MEBS, the participants write short texts or stories based on frame stories (i.e., introductory scripts) designed by the researcher. The core idea in the MEBS is that at least two versions of a frame story exist, which differ in one element. This variation enables the researcher to examine how the stories change when one element is varied. In this dissertation, a literature review (Publication I) shows how the MEBS has been used in Finland, and discusses its strengths, limitations, and future prospects. The literature review demonstrates that although the MEBS has been used in Finland for decades, it is still a nascent method in international contexts. Thus, a methodological article (Publication II) introduces the method internationally for the first time. This second article illustrates some possible ways to design and conduct MEBS research, discusses its relation to narrative methods as well as explores its methodological possibilities and limitations. The second aim of this dissertation is to empirically illustrate the possible relation between digitalization of work and professional development. Drawing on 101 empathy-based stories from 81 Finnish government workers, this dissertation provides different scenarios and illustrations on how digitalization might either support or hinder workers’ professional development. More specifically, the dissertation provides insights on how digitalization might alter the learning opportunities of the workplace (Publication III) and how digitalization can lead to different experiences of and responses to work–identity (mis)alignments (Publication IV). Overall, this dissertation’s empirical findings lay the foundation for a more comprehensive understanding of the ways in which digitalization may influence workers’ professional development by illustrating possible scenarios and typifications. The findings show how digitalization, by changing work tasks, work practices, and knowledge development and management, potentially alters a variety of aspects related to workplace learning opportunities, such as job demands, the level of job control, task variety and complexity, and social support, and thus can either v support or hinder professional development. In addition to illustrating how digitalization may change workplaces as learning environments, the findings show that whether digitalization supports or hinders professional development also relates to workers’ professional identities and how they practice their professional agency at work. Four types of workers (thriving developer, loyal transformer, stagnant selfdoubter, and career crafter) are identified from the participants’ stories. By introducing these four typifications, the findings describe how digitalization influences professional development by requiring the workers to assess how their work aligns with their professional identities, consequently resulting in experiences of work–identity (mis)alignments, and agentic actions in the form of identity work and job crafting. Altogether, the findings emphasize the need to broaden our view on what accounts for professional development. The results also suggests that a full understanding of how digitalization can either support or hinder workers’ professional development requires a theoretically complex view that acknowledges the interrelations among digitalization, the workplace learning opportunities, professional identity, and professional agency. This dissertation contributes to existing research on professional development and digitalization by applying a novel data collection method, that demonstrates the power of imagination and storytelling in exploring individuals’ perceptions, understandings, and sense-making. Moreover, by introducing the MEBS and showcasing its use empirically, this dissertation aims to generate methodological discussions and inspire researchers to find new ways of using the MEBS in diverse contexts.
... Green creativity has also been found to be negatively associated with environmental dynamism which reduces the effects of a VUCA world. Brougham and Haar (2018), state that the implementation of STARA technologies has popularized selfcheckout rentals, automation in accounting, driverless vehicles, and smartphone applications. They have highly reduced the uncertainty and complex characteristics associated with such systems. ...
Conference Paper
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The topic of consumer engagement has been gaining the attention of both academics and practitioners. This is because of the outcomes associated with consumer engagement such as increased sales, enhanced competitive advantage, consumer loyalty, and the development of mutual beneficial relationships between organisations and consumers. However, in the field of participant sports, there still lacks research on consumer engagement. The paper seeks to fill that gap by developing a conceptual model on consumer engagement in participant sports. The model provides a complete understanding of the process of consumer engagement in participant sports. The model highlights that sport participation motivation is the antecedent of consumer engagement (such as mastery and weight), sport participants engage on three dimensions (cognitive, emotional, and behavioural), and the outcomes of consumer engagement are word-of-mouth and re-participation intention. The model has implications for participant sport managers. The model provides a better understanding of current and prospective consumers, therefore, improving the targeting of customers through segmentation.
... Computer-based decision has less complexity, has less uncertainty on impacting quality and accuracy of context, reduces time required to solve the problem, is efficient and helps managers in taking better decisions and builds satisfaction and enhances user experience along with the quality of choices made while taking a decision as compared to paper pencil task. Brougham and Haar studies show that with the evolution of technology and improvisation in the fourth industrial revolution the jobs could be displaced and robots will impact their future [12]. The future career plans and opportunities will be challenging and this will have implications on mental health of employees, job insecurity, and their well-being. ...
Chapter
There has been explosion of Artificial Intelligence (AI) in recent times and sweeps through various industries and developments tools. These tools are being increasingly being also used in Human Resource Management for hiring, training, employee engagement, promotions, decision-making, speed and accuracy of work and removing the daily hurdles with high end technology. Machine learning algorithms, chatbots, robots help the process to achieve organization goals. This study aims at understanding the intensity of increase in usage of AI by human resource managers across different organizations of different sizes. The five-point Likert scale to develop the questionnaire is used to survey the participating HR managers in the Indian context. The findings of this study are multi-fold. First, the results indicate that although AI will take away lower-level jobs via automation, but it is difficult for top level hiring to be done largely via AI. Second, our results also depict those jobs which require more human touch can’t be easily replaced by automation. Finally, promotion decisions based only on automation can result in errors and hence it is also important to have human interaction before arriving at an outcome.KeywordsArtificial intelligenceMachine learningAlgorithmsHuman resource management
... Algorithms are a part of a "package" of new technologies known as STARA (Brougham and Haar, 2018). We use the term algorithm to denote any automated formula, rule, or set of instructions that are used to process data or perform a specific task (Germann, 2018). ...
Article
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In this essay case studies pointing to problems related to the use of AI in shaping the virtual world are discussed. AI algorithms helps to shape and control the conventional web behaviour and speech of today's media users, mostly teenagers and adults. Considering the development of software, social media may constitute a separate virtual world in the future. AI also shapes the image of this world and human relationships. The essay begins with an analysis of the future of social media against the background of truth; later, case studies show problems caused by AI to media users and the community. The authors attempt to answer questions such as: What kind of attitudes and abilities will be shaped in social media? What network ethics does AI dictate? What kind of attitudes and thinking will be promoted in the social media of the future?
... Bauer et al. (2007) identify role clarity in building an understanding of the expectation of a role. For managers collaborating with AI, a better understanding of responsibilities and tasks within roles helps develop clear expectations that address ambiguity, negative anticipation and uncertainty, impacting performance and commitment (Brougham and Haar, 2018). Makarius et al. (2020) propose that managers and human resource experts should help clarify the role of AI systems to employees for better comprehension and collaboration between them, leading to the development of trust. ...
Article
Purpose With the increase in the adoption of artificial intelligence (AI)-based decision-making, organizations are facilitating human–AI collaboration. This collaboration can occur in a variety of configurations with the division of labor, with differences in the nature of interdependence being parallel or sequential, along with or without the presence of specialization. This study intends to explore the extent to which humans express comfort with different models human–AI collaboration. Design/methodology/approach Situational response surveys were adopted to identify configurations where humans experience the greatest trust, role clarity and preferred feedback style. Regression analysis was used to analyze the results. Findings Some configurations contribute to greater trust and role clarity with AI as a colleague. There is no configuration in which AI as a colleague produces lower trust than humans. At the same time, the human distrust in AI may be less about human vs AI and more about the division of labor in which human–AI work. Practical implications The study explores the extent to which humans express comfort with different models of an algorithm as partners. It focuses on work design and the division of labor between humans and AI. The finding of the study emphasizes the role of work design in human–AI collaboration. There is human–AI work design that should be avoided as they reduce trust. Organizations need to be cautious in considering the impact of design on building trust and gaining acceptance with technology. Originality/value The paper's originality lies in focusing on the design of collaboration rather than on performance of the team.
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Technology enables actor-to-actor experience co-creation leading to value creation for the parties involved in the process. This research presents the initial impact of a mobile application developed to foster technology enabled relationship in rural Lebanon. Results indicate that technology has the potential to positively impact both host and guest fostering relationships building in all the trip stages and leading to socio-economic development and transformative experiences. In fact, the paper shows that relationships created and strengthened with the support of technology are expected to have effects at personal, community and business level.
Article
The extensive implementation of smart technology, artificial intelligence, automation, robotics, and algorithms (STAARA) in hospitality services has accelerated the need to understand their potential influence on hotel employees’ career perceptions. This study conducted two scenario-based experiments based on disruptive innovation theory and the Stimulus-Organism-Response (SOR) model to examine how STAARA awareness shapes hotel employees’ job insecurity and mobility. In addition, this study investigated career progression as a counterstrategy to attenuate the substitution effect of STAARA. Study 1 demonstrated that hotel employees’ negative (vs. positive) awareness of STAARA leads to higher job insecurity and mobility. Furthermore, according to Study 2, for hotel employees with low-level career progression, negative (vs. positive) awareness of STAARA induces higher job insecurity and mobility. However, among employees with high-level career progression, there were no significant differences, which means that high-level career progression attenuates the impact of STAARA. This study also considers theoretical and practical influences.
Chapter
Over the last 70 years, human factors, a term that is used synonymously with ergonomics and denoted as human factors ergonomics (HFE), has been evolving as a unique and independent discipline that originated with a focus on the nature of human–artifact interactions. The HFE discipline advocates systematic use of the knowledge concerning the relevant human characteristics in order to achieve compatibility in the design of interactive systems of people, machines, environments, and devices of all kinds to ensure specific goals. Ergonomics design is concerned with the ability to implement knowledge about human–system interactions and use them to develop systems that satisfy customer needs and relevant human compatibility requirements. Ergonomics literacy prepares individuals to perform their roles in the workplace and outside the working environment. One important subdiscipline of HFE with respect to the central focus of the management discipline is macroergonomics.
Chapter
Industry 4.0 and the Internet of Things have revolutionized every manufacturing process, and the welding industry is far from this huge breakthrough. Big data and real-time monitoring as critical elements of the fourth industrial revolution are the essential parts of all manufacturing sectors, especially laser welding. Therefore, optimizing and controlling manufacturing processes using Industry 4.0 components, such as the Internet of Things, sensor-based monitoring, and big data analytics, are considered critical approaches toward sustainable, efficient, and defect-free manufacturing. In this regard, this chapter has argued intelligent laser welding and analyzed sustainable manufacturing challenges by using optimization approaches. It recommends possible concerted effort and reveals how laser welding and Industry 4.0 strategies can integrate, assist, and synchronize each other.
Chapter
The fundamental norms, structures, processes, and methods have advanced in the soft sciences over the past few decades. However, concerns about Artificial Intelligence (AI) infiltration in these sciences have not changed. There was a time when two flows of research collided: research that resisted technological changes in the humanities and social sciences and research that went in the opposite direction by pushing beyond the biological capabilities of humans through AI. This has been amplified mainly with the advent of Big Data, the Internet of Things (IoT), and Mobile-Ubiquitous Systems (MUS). Faced with this intensification of AI intrusion on the one hand and the intensification of fears from AI, on the other hand, deep academic questioning is required. The objective of this research paper focuses on this gap. We propose an observational-based quantitative–qualitative approach to analyze and understand the evolution of AI in the soft sciences in this meta-study. Focusing on different areas, we discuss the primary factors and cases that shape the trends of the AI revolution. The results of this research are relevant and potentially useful for both AI and soft science disciplines.
Article
Background: Artificial intelligence (AI) is being increasingly adopted in the health care industry for administrative tasks, patient care operations, and medical research. Objective: To examine the opinions of health care workers about the adoption and implementation of AI-powered technology in the health care industry. Methods: Data were comments about AI posted on an online forum by 905 health care professionals from at least 77 countries, from May 2013 through October 2021. Structural topic modeling was used to identify the topics of discussion, and hierarchical clustering was performed to determine how these topics cluster into different groups. Results: Twelve topics were identified from the collected comments. These comments clustered into two groups: 1) impact of AI on health care system and practice and 2) AI as a tool for disease screening, diagnosis, and treatment. Topics associated with negative sentiments included concerns about AI replacing human workers, the impact of AI on traditional medical diagnostic procedure (i.e., patient history and physical examination), the accuracy of the algorithm, and the entry of information technology companies into the health care industry. Concerns about the legal liability for using AI in treating patients were discussed as well. Positive topics about AI included the opportunity offered by the technology for improving the accuracy of image-based diagnosis and for enhancing personalized medicine. Conclusions: The adoption and implementation of AI applications in the health care industry are eliciting both enthusiasm and concerns about patient care quality and the future of health care professions. The successful implementation of AI-powered technologies requires the involvement of all stakeholders, including patients, health care organizations workers, health insurance companies, and government regulatory agencies.
Article
Unionized organizations are implementing more than ever technological changes to cope with an increasingly changing and highly digital environment. Despite the extensive literature on union responses to changes, there is not much evidence on how unions and employers draft provisions pertaining to technological changes in collective agreements. Therefore, this paper aims to conduct an in-depth analysis of these provisions in over 500 collective agreements signed between 2000 and 2020. Specifically, this study focuses on office workers in two of the most important Canadian industries, namely, the healthcare and manufacturing sectors. The findings indicate that within the examined provisions, the regulation of technological change varies along a continuum that extends from no obligations to stringent obligations on the part of the employer. Moreover, the results show that these provisions have remained stable over the past two decades.
Article
Organizations are increasingly augmenting employee jobs with intelligent machines. Although this augmentation has a bright side, in terms of its ability to enhance employee performance, we think there is likely a dark side as well. Draw from self‐regulation theory, we theorize that dependence on intelligent machines is discrepancy‐reducing—enhancing work goal progress, which in turn boosts employees’ task performance. On the other hand, such dependence may be discrepancy‐enlarging—threatening employee self‐esteem, which in turn detracts from employees’ task performance. Drawing further from self‐regulation theory, we submit that employees’ core self‐evaluation (CSE) may influence these effects of dependence on intelligent machines. Across an experience‐sampling field study conducted in India (Study 1) and a simulation‐based experiment conducted in the United States (Study 2), our results generally support a “mixed blessing” perspective of intelligent machines at work. We conclude by discussing the theoretical and practical implications of our work.
Article
Purpose This study aims to examine the relationship between digital transformation (DigiTr), innovation and human resources planning (HRP) in hotels to investigate the impact of DigiTr on innovations and HRP and to test the mediating impact of innovation on the DigiTr-HRP relationship. Design/methodology/approach The authors used a quantitative research method in this study, specifically by conducting a hybrid face-to-face and online survey to collect data from 462 human resources (HR) managers, department managers and HR professionals at four- and five-star hotels in Turkey. The structured questionnaire assessed DigiTr, innovations in business models, services and processes and quantitative and qualitative changes in HR. The authors used covariance-based structural equation modeling to test the hypotheses. Findings DigiTr affected both innovations and HR planning in hotels, and also the effect of innovations on HR planning. In addition, DigiTr and innovations increased qualitative changes in HR planning but reduced quantitative changes. Finally, innovations mediated the relationship between DigiTr and HR planning. Practical implications These findings indicate that employers and employees need to be aware of developments in employment in the tourism industry, as these can significantly impact HR planning via DigiTr and innovations. Originality/value This study differs from the existing literature by providing empirical evidence to fill the knowledge gap regarding how DigiTr and innovation affect HR planning.
Article
Despite having one of the most advanced healthcare systems in the world, Japan is expected to experience a shortage of nearly half a million healthcare workers by 2025 due to its rapidly aging population. In response, government authorities plan to implement a wide range of AI-driven healthcare solutions. This includes care robots that assist the physically handicapped or elderly, to chatbots that provide anonymous online mental health consultation, to diagnostic software utilizing machine learning. Yet one of the most popular smart technologies to augment the nation's already overstrained and undermanned healthcare system is a little known but emerging emotional AI technologies, i.e., deep learning systems trained to read, classify, and respond to human emotions. These technologies are being sold on a commercial level to the public but also to rehabilitation centers, local hospitals and senior citizen residences. Although the augmentation of healthcare services to intelligent machines may seem like a logical step in a country well-known for its long-standing affection toward robots, Japanese society is also known for its adherence to established social relations, and traditional institutional practices, especially, in the realm of medical care. In order to gauge Japanese acceptance of emotion-sensing technology, we analyze a dataset of 245 visitors to clinics and hospitals in a typical suburban area in Japan using multiple linear regression. The results show that in general, senior and male patients perceive the EAI technology more negatively. For behavioral variables, patients' level of familiarity has positive correlations with attitudes toward EAI-based applications in private setting (βFamiliarity_AttitudePri = 0.346, p < 0.001) and public setting (βFamiliarity_PublicAttitude = 0.297, p < 0.001); while concerns for losing control to AI has negative correlations with the attitudes' variables: private setting (βLosingControl_AttitudePri = −0.262, p = 0.002) and public setting (β LosingControl_AttitudePub = -0.188, p = 0.044). Interestingly, concerns over violation of privacy and discrimination are non-significant correlates, which contradict the emerging literature on this subject. We further contextualize the findings with insights afforded by an understanding of Japanese culture as well as the relevant literature on care robots in Japan. Finally, policy and education implications to promote EAI acceptance to the general and senior members of the society are provided.
Article
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Robots are transforming the nature of human work. Although human-robot collaborations can create new jobs and increase productivity, pundits often warn about how robots might replace humans at work and create mass unemployment. Despite these warnings, relatively little research has directly assessed how laypeople react to robots in the workplace. Drawing from cognitive appraisal theory of stress, we suggest that employees exposed to robots (either physically or psychologically) would report greater job insecurity. Six studies-including two pilot studies, an archival study across 185 U.S. metropolitan areas (Study 1), a preregistered experiment conducted in Singapore (Study 2), an experience-sampling study among engineers conducted in India (Study 3), and an online experiment (Study 4)-find that increased exposure to robots leads to increased job insecurity. Study 3 also reveals that this robot-related job insecurity is in turn positively associated with burnout and workplace incivility. Study 4 reveals that self-affirmation is a psychological intervention that might buffer the negative effects of robot-related job insecurity. Our findings hold across different cultures and industries, including industries not threatened by robots. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Article
This research aimed to identify the HR strategies and functions most likely to be affected by emerging digital technologies and explores the competencies and capabilities required by present and future HR professionals to transform these changing functions. Further, it analyses the developmental roles of educational institutions and professional associations in equipping HR professionals for this transition process. The study employed an exploratory sequential mixed methods research design incorporating two phases. Phase I involved a survey of HR professionals (n = 203) and Phase II involved a focus group of senior HR professionals and HR academics involved in accrediting HR courses nationally in Australia. The findings point to a patchy uptake of smart technologies, artificial intelligences, robotics and algorithm (STARA) technologies in workplaces, with the expected usage of most of these technologies more likely in the future than currently. Most HR functions and HR roles are likely to be affected by these new digital technologies and associated competencies and skills.
Article
The purpose of this paper is to investigate cognitive biases among financial planners and, if and how, digital transformation through Artificial Intelligence (AI) can help overcome biases. The literature establishes that investors and financial services clients can exhibit cognitive biases. However, it is not evident whether the financial planners understand and detect cognitive biases among the clients and if they at all 'attempt' to address the biases whilst providing financial planning services. Utilizing the attribution theory, our paper contributes by exploring the gap in research related on cognitive biases among financial planners and provides a future research agenda for addressing the gap, through a qualitative investigation. Our study was designed over two stages, wherein we conducted in-depth interviews in both stages. The first stage included in depth interviews with 21 financial planners and a repeat 10 interviewers with select financial planners, with scenarios in the second stage. In total, we conducted 31 interviews to investigate cognitive biases among financial planners and how Artificial Intelligence can assist. Our findings suggest that cognitive biases exist among financial planners while providing services for the people in need, which is a major challenge for them. Our findings further suggest that digital transformation by using the Artificial Intelligence technologies might help overcome this existing biases, albeit, AI technologies ought to be combined with human intelligence. To the best of our knowledge, there exists no existing research on the association between cognitive biases and artificial intelligence among financial planners.
Article
Purpose Service robots have increasingly been utilized in retail settings, yet empirical research on how frontline employees (FLEs) might deal with this new reality remains scarce. This mixed-methods study aims to examine how FLEs expect physical service robots to impact job characteristics and affect their job engagement and well-being. Design/methodology/approach First, explorative interviews (Study 1; N = 32) were conducted to investigate how FLEs currently experience job characteristics and how they believe robots might impact these job characteristics and job outcomes. Next, a survey (Study 2; N = 165) examined the relationship between job characteristics that retail FLEs expect to be impacted by robots and their own well-being and job engagement. Findings While the overall expectations for working with robots are mixed, retail FLEs expect that working with robots can alleviate certain job demands, but robots cannot help to replenish their job resources. On the contrary, most retail FLEs expect the pains and gains associated with robots in the workspace to cancel each other out, leaving their job engagement and well-being unaffected. However, of the FLEs that do anticipate that robots might have some impact on their well-being and job engagement, the majority expect negative effects. Originality/value This study is unique in addressing the trade-off between expected benefits and costs inherent to job demands-resources (JD-R) theory while incorporating a transformative service research (TSR) lens. By integrating different streams of research to study retail FLEs' expectations about working with robots and focusing on robots' impact on job engagement and well-being, this study offers new insights for theory and practice.
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The purpose of this study is to investigate which type of leadership characteristics advocated in Langford’s Leadership Big 5 Model can enhance Gen Z work performance. In addition, this study seeks to develop current knowledge on effective leadership characteristics to manage Generation Z. This study also endeavours to examine the mediating effect of structural empowerment in managing Generation Z and identify the appropriate leadership characteristics to enhance the contextual performance of generation Z workforce.
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We assess the extent to which manufacturing decline and housing booms contributed to changes in U.S. non-employment during the 2000s. Using a local labor market design, we estimate that manufacturing decline significantly increased non-employment during 2000-2007, while local housing booms decreased non-employment by roughly the same magnitude. The effects of manufacturing decline persist through 2011, but we find no persistent non-employment effects of local housing booms, most plausibly because housing booms were associated with subsequent busts of similar magnitude. We also find that housing booms significantly reduce the likelihood that displaced manufacturing workers remain non-employed, suggesting that housing booms "mask" non-employment growth that would have otherwise occurred earlier in the absence of the booms. Applying our estimates to the national labor market, we find that housing booms reduced non-employment growth by roughly 30 percent during 2000-2007 and that roughly 40 percent of the aggregate increase in non-employment during 2000-2011 can be attributed to manufacturing decline. Collectively, our results suggest that much of the non-employment growth during the 2000s can be attributed to manufacturing decline and these effects would have appeared in aggregate statistics earlier had it not been for the large, temporary increases in housing demand.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
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This study used the Comprehensive Career Needs Survey to assess the career planning needs of 2360 senior high school students in Southern Alberta, Canada. This article examines how senior high school students perceive the relevance of career planning, who they feel comfortable approaching for help with career planning, and what help they would like during their career planning. Results indicated that career planning is important to high school students and they are likely to approach their parents first for help with career planning. Students in grades 10 through 12 indicated that specific information regarding courses, post-secondary information and careers would be helpful. Grade 12 students also expressed a desire for improved career counselling and increased work experience. Implications for teachers, school counsellors, parents and community services are discussed.
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This paper reports on a repeated measures study of job insecurity conducted during drastic organisational change in one of Australia's large public transport organisations. In a redundant group (n = 32) and a control group (n = 63), effects of job insecurity and the availability of coping resources on psychological health and withdrawal were examined longitudinally by means of self-report questionnaires. Results indicate that job insecurity is associated with a deterioration of psychological health (i.e. leading to psychological distress and burnout), as well as job and organisational withdrawal. Contrary to expectations, however, neither support from colleagues nor management nor unions seemed to protect job incumbents from the negative effects of job insecurity. Apparently, these three sources of potential support do not have a stress-buffering effect. It was concluded that in order to combat the adverse effects of job insecurity on psychological health and morale, the job stressor itself has to be dealt with, instead of trying to render it less harmful by providing more social support.
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This paper presents a new picture of the labor market effects of technological change in pre-WWII United States. I show that, similar to the recent computerization episode, the electrification of the manufacturing sector led to a "hollowing out" of the skill distribution whereby workers in the middle of the distribution lost out to those at the extremes. To conduct this analysis, a new dataset detailing the task composition of occupations in the United States for the period 1880-1940 was constructed using information about the task content of over 4,000 occupations from the Dictionary of Occupational Titles (1949). This unique data was used to measure the skill content of electrification in U.S. manufacturing. OLS estimates show that electrification increased the demand for clerical, numerical, planning and people skills relative to manual skills while simultaneously reducing relative demand for the dexterity-intensive jobs which comprised the middle of the skill distribution. Thus, early twentieth century technological change was unskill-biased for blue collar tasks but skill-biased on aggregate. These results are in line with the downward trend in wage differentials within U.S. manufacturing up to 1950. To overcome any threat to the exogeneity of the electricity measure, due for example to endogenous technological change, 2 instrumental variable strategies were developed. The first uses cross-state differences in the timing of adoption of state-level utility regulation while the second exploits differences in state-level geography that encouraged the development of hydro-power generation and thus made electricity cheaper. The results from these regressions support the main conclusions of the paper.
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What-you-should-be-when-you-grow-up need not and should not be planned in advance. Instead career counselors should teach their clients the importance of engaging in a variety of interesting and beneficial activities, ascertaining their reactions, remaining alert to alternative opportunities, and learning skills for succeeding in each new activity. Four propositions: (1) The goal of career counseling is to help clients learn to take actions to achieve more satisfying career and personal lives—not to make a single career decision. (2) Assessments are used to stimulate learning, not to match personal characteristics with occupational characteristics. (3) Clients learn to engage in exploratory actions as a way of generating beneficial unplanned events. (4) The success of counseling is assessed by what the client accomplishes in the real world outside the counseling session.
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This study set to explore the career needs and proposes the concept of the gap between career development programs and career needs, and its subsequent effect on job satisfaction, turnover intention, in an effort to contribute to the field of career management, through the effective integration of career needs and career development programs. Questionnaires were completed by 367 R&D personnel from Hsinchu Science-based Industrial Park (HSIP) in the north of Taiwan. The results reveal that R&D personnel have very diverse career needs at various stages of their career, and that depending on which stage of their career they have reached. The result show that the larger the gap, the higher the levels of both turnover intentions and job dissatisfaction. Managerial implications of these findings are also discussed.
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Purpose The purpose of this paper is to show how mobile robots are addressing a variety of hospital logistic needs. Design/methodology/approach The paper includes in‐depth interviews with developers of the Aethon hospital mobile robot logistics system. Findings Robotics can greatly improve hospital logistic services such as moving food, lab samples, prescriptions and even add a bit of entertainment in the process. Practical implications Hospital administrators have new answers to the old challenges of moving items in a timely and cost‐effective manner around their facility. Originality/value Hospitals are first implementers of mobile robotics to look for answers to their logistic problems. They do not have to break new ground for themselves.
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Through the application of cognitive appraisal theory, this study unifies the emergent themes of studying justice in relation to organizational context, as well as justice in relation to employee feelings of psychological distress. A sample of 677 employees from 72 organizations was used to test hypotheses related to justice, job control, mechanistic structure, and employee feelings of anxiety and depression. We found procedural justice, within a primary appraisal role, to be a highly effective tool for minimizing psychological distress. In combination with both distributive justice as well as a mechanistic structure, procedural justice can help to minimize feelings of anxiety and depression, but in different manners for each variable. Further, a strong influence of job control upon both procedural justice and, ultimately, depression and anxiety highlighted its role as a perceived means for avoiding or minimizing the harm of a potential stressor. Copyright © 2007 John Wiley & Sons, Ltd.
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Data obtained from a sample of technical, professional and administrative/managerial employees (N = 214) in Singapore were used to examine the cross-cultural generalizability of a version of Gould's career planning model. The recursive model depicts the mechanisms through which career planning affects career behavior (career strategy) and attitudes (career satisfaction, self-esteem at work and career commitment) and thereby reinforce the career planning function. Path analysis results of the four structural equations provided modest support for the hypothesized relations. In addition to the hypothesized relations, the results revealed some significant direct paths that were not hypothesized. Limitations of the study, implications of the findings and a direction for future studies are discussed.
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The current growth of the service sector in global economies is unparalleled in human history—by scale and speed of labor migration. Even large manufacturing firms are seeing dramatic shifts in percent revenue derived from services. The need for service innovations to fuel further economic growth and to raise the quality and productivity levels of services has never been greater. Services are moving to center stage in the global arena, especially knowledge-intensive business services aimed at business performance transformation. One challenge to systematic service innovation is the interdisciplinary nature of service, integrating technology, business, social, and client (demand) innovations. This paper describes the emergence of service science, a new interdisciplinary area of study that aims to address the challenge of becoming more systematic about innovating in service.
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This article describes a longitudinal study of how openness to change, job satisfaction, anxiety and depression are affected by exposure to a change situation - in this case, the implementation of new technology and work practices. Measures were taken before the change was fully implemented and again several months later. Employees fell into two groups: those with high exposure to the change and those with low exposure. Longitudinal analysis revealed that greater exposure was directly related to subsequent improvements in openness to change for operational employees, but not for managers and engineers. Exposure was associated with improvements in job satisfaction and depression, irrespective of job type. The effect on job satisfaction, however, could be accounted for by the increased job complexity experienced on the new technology rather than exposure to change per se. Although the impact of exposure on depression became non-significant after controlling for job complexity, the result was marginal. Implications of the role of exposure in the management of change are discussed.