本研究探討人工智慧（AI）所引起的工作變革對員工結果的不同影響，特別關注工作不安全感、創造力、參與度以及工作塑造。本研究納入工作需求-資源（JDR）理論，並檢視員工資源和工作塑造在減輕人工智慧（AI）引起的變革所帶來的不良後果方面的重要性。研究顯示資訊通訊技術資源和數位靈活性在幫助員工因應AI引起的工作變革方面的重要性，並強調工作塑造的方式中的主動和迴避策略的重要性。資訊通訊技術資源的可用性以及針對減輕工作不安全感的措施的實施，是使員工能夠在AI驅動的環境中有效運用並積極參與主動的工作塑造的關鍵因素。本研究對當前文獻作出了重要的貢獻，為人工智慧（AI）對員工結果的影響提供了有價值的見解。同時，它還指導組織在有效實施AI技術並在不斷變化的職場中培育創造力方面的做法。

This study investigates the different impacts of job changes caused by artificial intelligence (AI) on employee outcomes, with particular attention being placed on job insecurity, creativity, engagement, and job crafting. This study incorporates the Job Demands-Resources (JDR) theory and examines the significance of employee resources and job crafting in alleviating the adverse consequences of changes induced by artificial intelligence (AI). It demonstrates the importance of ICT resources and digital dexterity for assisting employees cope with AI-induced job changes and emphasizes the importance of approach and avoidance strategies in the form of job crafting. The availability of ICT resources and the implementation of measures aimed at mitigating job insecurity are essential factors in enabling employees to effectively navigate AI-driven environments and actively engage in proactive job crafting. This study makes a significant contribution to the current body of literature by offering valuable insights into the impact of artificial intelligence (AI) on employee outcomes. It also guides organizations in effectively implementing AI technologies and fostering creativity in the ever-changing workplace.

Table of Contents
Thesis Validation Letter ........................................ i
Acknowledgement .......................................................... ii
摘要.................................................................................... iii
Abstract ......................................................................... iv
Table of Contents ........................................................v
Table of Figures............................................................vii
Table of Tables............................................................viii
CHAPTER 1 Introduction ...................................................................... 1
1.1 Research Background ........................................................................ 1
1.2 Research Questions ............................................................. 4
CHAPTER 2 Literature Review ......................................................... 5
2.1. Technology Advancement (Artificial Intelligence) .................. 5
2.2. AI Induced job changes. .................................................... 10
2.3 Job Demand Resource Theory ............................................. 12
2.4 AI induced job changes as a demand ........................................ 13
2.5. Resources ....................................................... 21
2.6. Job Crafting ....................................................................... 23
CHAPTER 3 Research Methods ............................................................ 33
3.1 Research Framework ................................................................... 33
3.2 Research Hypotheses ............................................................... 34
3.3. Participants and Procedure ..................................................... 52
3.4. Demographic Data ................................................ 54
3.5. Survey Constructs and Measurements ......................... 56
CHAPTER 4 Results ................................................................. 60
4.1. Measurement Model ........................................................... 60
4.2. Structural Model ......................................................... 70
Chapter 5 Conclusion .......................................................... 77
Chapter 6 Discussions ......................................................................... 78 References ................................................................................................ 92 Appendix
Research Survey .................................................................................. 101
Table of Tables
Table 1 Definitions of Artificial Intelligence ............................................. 8
Table 2: Role Resource Approach Avoidance Crafting ........................... 28
Table 3: Demographic Data .................................................................... 55
Table 4: Multicollinearity Statistics (VIF) for indicators .......................... 61
Table 5: Construct Reliability Analysis (Cronbach Alpha and Composite Reliability).............. 62
Table 6: Construct Convergent Validity (AVE)........................................ 63
Table 7: Discriminant Validity: Fornell and Larcker's Criteria .............. 65
Table 8: Cross Loadings .................................................................. 66
Table 9 : Discriminant Validity: HTMT ............................................ 69
Table 10: Direct Relationships .............................................................. 73
Table 11: Mediation Analysis ................................................................. 76
Table 12: Factor Loadings.....................................................................107
Table of Figures
Figure 1 History of Artificial Intelligence ..................................................... 7
Figure 2: Research Framework ................................................................ 34
Figure 3: Path Coefficients ...................................................................... 70
Figure 4: Indirect effects and t values .......................................................... 75

A. B. Bakker and E. Demerouti, “Multiple levels in job demands-resources theory: Implications for employee well-being and performance,” in Handbook of Well-Being. Abingdon, U.K.: Routledge, 2018, pp. 1–13.
Ahmed, W., Hizam, S. M., & Sentosa, I. (2022). Digital dexterity: employee as consumer approach towards organizational success. Human Resource Development International, 25(5), 631-641.
Al-Ali, A. R., Aitken, R. L., & Turner, S. J. (2020). Machine learning in integrated circuit design: A comprehensive survey. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(11), 3945-3966.
Arslanian, H., Azar, A., de Filippi, P., & Mainelli, M. (2019). The future of financial infrastructure: An ambitious look at how blockchain can reshape financial services. World Economic Forum. https://www.weforum.org/reports/the-future-of-financial-infrastructure-an-ambitious-look-at-how-blockchain-can-reshape-financial-services
Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831-858.
Bag, S., Jain, K., & Jain, A. (2021). Impact of technological interventions on employee well-being: A review. Journal of Business Research, 133, 1-14. https://doi.org/10.1016/j.jbusres.2021.02.013
Bag, S., Jain, K., & Jain, A. (2021b). The impact of AI adoption on employee well-being: An empirical investigation. Technological Forecasting and Social Change, 172, 121058. https://doi.org/10.1016/j.techfore.2021.121058
Bag, S., Panchal, P., & Sagar, M. (2021). Impact of artificial intelligence on employee job satisfaction: Moderating role of job control. Journal of Workplace Learning, 33(2), 93-107. https://doi.org/10.1108/JWL-11-2020-0246
Bag, S., Panchal, P., & Sagar, M. (2021b). Examining the role of job demand and job control on artificial intelligence-induced job strain. Journal of Business Research, 136, 222-232. https://doi.org/10.1016/j.jbusres.2021.03.040
Bakker, A. B., & Demerouti, E. (2008). Towards a model of work engagement. Career Development International, 13(3), 209-223.
Bakker, A. B., Tims, M., & Derks, D. (2012). Proactive personality and job performance: The role of job crafting and work engagement. Human Relations, 65(10), 1359-1378. https://doi.org/10.1177/0018726712449458
Balakrishnan, V., Azhar, A., Nayyar, N., & Budhiraja, A. (2020). AI adoption advances, but foundational barriers remain. McKinsey Global Survey. Retrieved from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/ai-adoption-advances-but-foundational-barriers-remain
Bayo‐Moriones, A., Bello‐Pintado, A., & Merino‐Díaz‐de‐Cerio, J. (2010). The effects of integrated manufacturing on job characteristics. New Technology, Work and Employment, 25(1), 63-79.
Begum, S., Ashfaq, M., Xia, E., & Awan, U. (2022). Does green transformational leadership lead to green innovation? The role of green thinking and creative process engagement. Business Strategy and the Environment, 31(1), 580-597.
Bolino, M. C., & Grant, A. M. (2016). The bright side of being prosocial at work, and the dark side, too: A review and agenda for research on other-oriented motives, behavior, and impact in organizations. Academy of Management Annals, 10(1), 599-670.
Borman, W. C., & Motowidlo, S. J. (1993). Expanding the criterion domain to include elements of contextual performance. Personnel Selection in Organizations, 71-98.
Brod, C. (1982). Managing technostress: optimizing the use of computer technology. Personnel Journal, 61(10), 753-57.
Bruning, P. F., & Campion, M. A. (2018). The effects of job crafting on subjective well-being and employability. Journal of Applied Psychology, 103(3), 324-337.
Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke, N., & Trench, M. (2018). Artificial intelligence: The next digital frontier? McKinsey Global Institute.
Califf, C. B., Sarker, S., & Sarker, S. (2020). The bright and dark sides of technostress: A mixed-methods study involving healthcare IT. MIS quarterly, 44(2).
Cetindamar, D., Abedin, B., & Shirahada, K. (2021). The role of employees in digital transformation: a preliminary study on how employees’ digital literacy impacts use of digital technologies. IEEE Transactions on Engineering Management.
Chandra, S., Shirish, A., & Srivastava, S. C. (2022). To be or not to be… human? Theorizing the role of human-like competencies in conversational artificial intelligence agents. Journal of Management Information Systems, 39(4), 969-1005.
Chen, M., Zada, M., Khan, J., & Saba, N. U. (2022). How does servant leadership influences creativity? Enhancing employee creativity via creative process engagement and knowledge sharing. Frontiers in Psychology, 13, 947092.
Cook, T. D., Campbell, D. T., & Shadish, W. (2002). Experimental and quasi-experimental designs for generalized causal inference (Vol. 1195). Boston, MA: Houghton Mifflin.
Davenport, T. H., Kalakota, R., & Johnson, J. (2019). Artificial intelligence for the real world. Harvard Business Review, 97(1), 108-116.
De Witte, H. (1999). Job insecurity and psychological well-being: Review of the literature and exploration of some unresolved issues. European Journal of Work and Organizational Psychology, 8(2), 155-177.
Deloitte. (2019). Deloitte’s 2019 global blockchain survey. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/se/Documents/risk/DI_2019-global-blockchainsurvey.pdf.
Deloitte. (2019). Tech trends 2020. Retrieved from https://www2.deloitte.com/us/en/insights/focus/tech-trends.html.
Drummond, C., O'Toole, T., & McGrath, H. (2020). Digital engagement strategies and tactics in social media marketing. European Journal of Marketing.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
E. Demerouti, A. B. Bakker, and D. Xanthopoulou, “Job demandsresources theory and the role of individual cognitive and behavioral strategies,” in The Fun and Frustration of Modern Working Life: Contributions From an Occupational Health Psychology Perspective, T. Taris, M. Peeters, and H. De Witte, Eds., Antwerpen, Belgium: Pelckmans Pro, 2019, pp. 94–104.
Eikebrokk, T. R., & Olsen, D. H. (2020). Robotic process automation and consequences for knowledge workers; A mixed-method study. In Responsible Design, Implementation and Use of Information and Communication Technology: 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020, Skukuza, South Africa, April 6–8, 2020, Proceedings, Part I 19 (pp. 114-125). Springer International Publishing.
Eldor, L., & Harpaz, I. (2016). A process model of employee engagement: The learning climate and its relationship with extra‐role performance behaviors. Journal of Organizational Behavior, 37(2), 213-235.
Elsbach, K. D., & Cable, D. M. (2012). Why showing your face at work matters. MIT Sloan Management Review, 53(3), 53-60.
F. J. Milliken, “Three types of perceived uncertainty about the environment: State, effect, and response uncertainty,” Acad. Manage. Rev., vol. 12, no. 1, pp. 133–143, 1987.
Frost & Sullivan. (2018). Artificial intelligence disrupting healthcare sector, creating growth opportunities.
Gann, D. M. (2005). H. Chesbrough, Open Innovation: The New Imperative for Creating And Profiting From Technology, Harvard Business School Press, 2003 (272 pp., $35.00, ISBN: 1-57851-837-7). Research Policy, 34(1), 122-123.
Gartner. (2017, December 13). Gartner Says By 2020, Artificial Intelligence Will Create More Jobs Than It Eliminates. Retrieved from https://www.gartner.com/en/newsroom/press-releases/2017-12-13-gartner-says-by-2020-artificial-intelligence-will-create-more-jobs-than-it-eliminates
Giovanis, A. (2018). Technostress and the employee: A critical literature review. Telematics and Informatics, 35(1), 1-14.
Grand View Research. (2021). Artificial Intelligence in Healthcare Market Size, Share & Trends Analysis Report By Component (Hardware, Software, Services), By Application (Drug Discovery, Medical Imaging), By Region, And Segment Forecasts, 2021 - 2028. Retrieved from https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-in-healthcare-market
Greenhalgh, L. and Z. Rosenblatt, Job insecurity: Toward conceptual clarity. Academy of Management Review, 1984. 9(1): p. 438-448.
Grote, G., & Raub, S. (2019). Artificial intelligence and the future of work: Human-AI collaboration, job automation, and skills development. Journal of Business and Psychology, 34(6), 657-663.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications.
Harris, L. C., Rae, A., & Henneberg, S. C. (2018). The future of employee privacy rights in the era of big data. Journal of Business Research, 82, 256-264.
Häusser, J. A., Mojzisch, A., Niesel, M., & Schulz-Hardt, S. (2010). Ten years on: A review of recent research on the Job Demand–Control (-Support) model and psychological well-being. Work & Stress, 24(1), 1-35.
Helsper, E. J., & Van Deursen, A. J. (2017). Do the rich get digitally richer? Quantity and quality of support for digital engagement. Information, Communication & Society, 20(5), 700-714.
Helsper, E. J., & Van Deursen, A. J. (2017). Do the rich get digitally richer? Quantity and quality of support for digital engagement. Information, Communication & Society, 20(5), 700-714.
Hsieh, H. H., & Kao, K. Y. (2022). Beyond individual job insecurity: A multilevel examination of job insecurity climate on work engagement and job satisfaction. Stress and Health, 38(1), 119-129.
Hughes, C., Robert, L., Frady, K., & Arroyos, A. (2019). Artificial intelligence, employee engagement, fairness, and job outcomes. In Managing Technology and Middle-and Low-skilled Employees: Advances for Economic Regeneration (pp. 61-68). Emerald Publishing Limited.
Hughes, C., Robert, L., Frady, K., & Arroyos, A. (2019). Artificial intelligence, employee engagement, fairness, and job outcomes. In Managing Technology and Middle-and Low-skilled Employees: Advances for Economic Regeneration (pp. 61-68). Emerald Publishing Limited.
Inoue, A., Kawakami, N., Tsuno, K., Shimazu, A., Tomioka, K., Nakanishi, M., ... & Kishi, R. (2018). Job insecurity, health risks, and occupational stress among Japanese employees: A cohort study. International Journal of Environmental Research and Public Health, 15(11), 2524.
Jacob, F., Grosse, E. H., Morana, S., & König, C. J. (2023). Picking with a robot colleague: a systematic literature review and evaluation of technology acceptance in human–robot collaborative warehouses. Computers & Industrial Engineering, 109262.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business horizons, 61(4), 577-586.
Jiang, H., & Shen, H. (2023). Toward a relational theory of employee engagement: Understanding authenticity, transparency, and employee behaviors. International Journal of Business Communication, 60(3), 948-975.
Karatepe, O. M., Yavas, U., & Babakus, E. (2020). Does job insecurity lead to employee disengagement? The role of job autonomy. Journal of Business Research, 108, 349-359.
Karwowski, M., Skarżyńska, K., Ziemiańska, A., & Turek, K. (2021). The Use of Artificial Intelligence and Its Effect on Job Strain and Satisfaction among Employees. International Journal of Environmental Research and Public Health, 18(4), 1728. doi: 10.3390/ijerph18041728
Kivimäki, M., Singh-Manoux, A., Virtanen, M., & Ferrie, J. E. (2018). Effort-reward imbalance at work and the risk of sleep disturbances: Cross-sectional and longitudinal findings from the Whitehall II study. Sleep, 41(5), zsy029.
Kropp, B., Smith, A., & Cain, M. (2021, October 4). How to build digital dexterity into your workforce. Harvard Business Review. https://hbr.org/2021/10/how-to-build-digital-dexterity-into-your-workforce
Krutova, O., Turja, T., Koistinen, P., Melin, H., & Särkikoski, T. (2022). Job insecurity and technology acceptance: an asymmetric dependence. Journal of Information, Communication and Ethics in Society, 20(1), 110-133.
Kshetri, N. (2018). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 39, 1-3. doi: 10.1016/j.ijinfomgt.2018.01.002
Langerak, J. B., Koen, J., & van Hooft, E. A. (2022). How to minimize job insecurity: The role of proactive and reactive coping over time. Journal of Vocational Behavior, 136, 103729.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer.
Leka, S., & Jain, A. (2021). Organisational support for employee well-being in the context of technological change. Employee Relations, 43(1), 216-229.
Lichtenthaler, U. (2019). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 62(1), 107-114.
Lyu, Y., & Zhang, Y. (2021). The impact of artificial intelligence on job satisfaction and emotional labor: The moderating role of responsibility attribution. Frontiers in Psychology, 12, 630566. doi: 10.3389/fpsyg.2021.630566
M. Bhattacharya, D. E. Gibson, and D. H. Doty, “The effects of flexibility in employee skills, employee behaviors, and human resource practices on firm performance,” J. Manage., vol. 31, no. 4, pp. 622–640, 2005.
M. Tarafdar, Q. Tu, T. S. Ragu-Nathan, and B. S. Ragu-Nathan, “Crossing to the dark side: Examining creators, outcomes, and inhibitors of technostress,” Commun. Assoc. Comput. Machinery, vol. 54, no. 9, pp. 113–120, 2011.
Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., & Dewhurst, M. (2017). Artificial intelligence: The next digital frontier? McKinsey Global Institute. https://www.mckinsey.com/featured-insights/artificial-intelligence/ai-and-the-future-of-work-how-society-can-respond-to-growing-automation
MarketsandMarkets. (2021). Artificial Intelligence in Healthcare Market by Offering, Technology, End-Use Application, End User - Global Forecast to 2026. Retrieved from https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-57681505.html
Molino, M., Cortese, C. G., & Ghislieri, C. (2020). The promotion of technology acceptance and work engagement in industry 4.0: From personal resources to information and training. International journal of environmental research and public health, 17(7), 2438.
Mondolo, J. (2022). The composite link between technological change and employment: A survey of the literature. Journal of Economic Surveys, 36(4), 1027-1068.
Moore, G. C. (2000). Understanding the use of technology-based self-service: A comparative analysis of" Web-Only" and" Web-With-Assistance" self-service. Journal of the Academy of Marketing Science, 28(2), 218-233.
Nastjuk, I., Trang, S., Grummeck-Braamt, J. V., Adam, M. T., & Tarafdar, M. (2023). Integrating and synthesising technostress research: a meta-analysis on technostress creators, outcomes, and IS usage contexts. European Journal of Information Systems, 1-22.
Nella, A., Christensen, K. B., & Kristensen, T. S. (2015). Job insecurity and the association with health among Danish employees: A systematic review. Safety and Health at Work, 6(1), 1-8.
Organ, D. W., & Ryan, K. (1995). A meta-analytic review of attitudinal and dispositional predictors of organizational citizenship behavior. Personnel Psychology, 48(4), 775-802.
P. Crosman, “How artificial intelligence is reshaping jobs in banking,” May 7, 2018. [Online]. Available: https://www.americanbanker.com/ news/how-artificial-intelligence is reshaping-jobs-in-banking
Paramita, A. P., & Sudhartio, L. (2022). Analyzing The Impact Of Job Stress, Job Insecurity, and Work Engagement On Job Performance During The COVID-19 Pandemic In The Aviation Industry. The Asian Journal of Technology Management, 15(1), 1-20.
Pett, M. A., Lackey, N. R., & Sullivan, J. J. (2003). Making sense of factor analysis: The use of factor analysis for instrument development in health care research. sage.
Razzaq, M. A., Qaisar, S. B., Arif, M. F., Imran, M., & Hassan, S. A. (2021). Exploring the Impact of Artificial Intelligence on Employee Performance and Job Complexity: A Qualitative Study. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 8. doi: 10.3390/joitmc7010008
Research and Markets. (2020). Autonomous vehicles market by level of automation, application, and region - global forecast to 2030. Retrieved from https://www.researchandmarkets.com/reports/5206354/autonomous-vehicle-market-by-automation-level
Rhee, T., & Jin, X. (2021). The Effect of Job Anxiety of Replacement by Artificial Intelligence on Organizational Members' Job Satisfaction in the 4th Industrial Revolution Era: The Moderating Effect of Job Uncertainty. Journal of Digital Convergence, 19(7).
S. O. Atiku, K. I. Genty, and B. H. Akinlabi, “Effect of electronic banking on employees’ job security in Nigeria,” Eur. J. Humanities Social Sci., vol. 4, no. 2, pp. 68–84, 2011.
Schaufeli, W. B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3(1), 71-92.
Sharma, A., & Nambudiri, R. (2020). Work engagement, job crafting and innovativeness in the Indian IT industry. Personnel Review, 49(7), 1381-1397.
Shin, Y., & Hur, W. M. (2020). Exploring the impact of job insecurity on employees' energy, health, and organizational outcomes: The role of self-concordance and thriving at work. Frontiers in Psychology, 11, 1207.
Smithson, J. and S. Lewis, Is job insecurity changing the pscyhological contract? Personnel Review, 2000. 29(6): p. 680-702.
T. Nam, “Technology usage, expected job sustainability, and perceived job insecurity,” Technological Forecasting Social Change, vol. 138, pp. 155–165, 2019.
T. S. Ragu-Nathan, M. Tarafdar, B. S. Ragu-Nathan, and Q. Tu, “The consequences of technostress for end users in organizations: Conceptual development and empirical validation,” Inf. Syst. Res., vol. 19, no. 4, pp. 417–433, 2008.
Tang, C., Mao, S., Naumann, S. E., & Xing, Z. (2022). Improving student creativity through digital technology products: A literature review. Thinking Skills and Creativity, 44, 101032.
Tarafdar, M., Tu, Q., & Ragu-Nathan, T. S. (2007). Impact of technostress on end-user satisfaction and performance. Journal of Management Information Systems, 24(1), 301-328.
Tidd, J., & Bessant, J. R. (2020). Managing innovation: integrating technological, market and organizational change. John Wiley & Sons.
Tims, M., Bakker, A. B., & Derks, D. (2013). The impact of job crafting on job demands, job resources, and well-being. Journal of Occupational Health Psychology, 18(2), 230-240.
Tims, M., Bakker, A. B., & Derks, D. (2016). Job crafting and employee well-being. In S. K. Parker & U. K. Bindl (Eds.), Proactivity at Work: Making Things Happen in Organizations (pp. 47-62).
Tims, M., Twemlow, M., & Fong, C. Y. M. (2022). A state-of-the-art overview of job-crafting research: current trends and future research directions. Career Development International, 27(1), 54-78.
Uen, J. F., Vandavasi, R. K. K., Lee, K., Yepuru, P., & Saini, V. (2021). Job crafting and psychological capital: a multi-level study of their effects on innovative work behaviour. Team Performance Management: An International Journal, 27(1/2), 145-158.
Vrontis, D. (2022). The impact of industry 4.0 on human resources and the future of work. European Journal of Business and Management, 14(10), 13-18.
Wang, Q., Khan, S. N., Sajjad, M., Sarki, I. H., & Yaseen, M. N. (2023). Mediating Role of Entrepreneurial Work-Related Strains and Work Engagement among Job Demand–Resource Model and Success. Sustainability, 15(5), 4454.
Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. Journal of Database Management (JDM), 30(1), 61-79.
Wang, Z., Cui, T., Cai, S., & Ren, S. (2022). How and when high-involvement work practices influence employee innovative behavior. International Journal of Manpower, 43(5), 1221-1238.
Wu, T. J., Li, J. M., & Wu, Y. J. (2022). Employees' job insecurity perception and unsafe behaviours in human–machine collaboration. Management Decision, 60(9), 2409-2432.
Yu, X., Xu, S., & Ashton, M. (2023). Antecedents and outcomes of artificial intelligence adoption and application in the workplace: the socio-technical system theory perspective. Information Technology & People, 36(1), 454-474.
Zhang, X., & Bartol, K. M. (2010). Linking empowering leadership and employee creativity: The influence of psychological empowerment, intrinsic motivation, and creative process engagement. Academy of management journal, 53(1), 107-128.
Zirar, A., Ali, S. I., & Islam, N. (2023). Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research