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All issues Volume 155 (2023) SHS Web Conf., 155 (2023) 03022 References
Open Access
Issue
SHS Web Conf.
Volume 155, 2023
2022 2nd International Conference on Social Development and Media Communication (SDMC 2022)
Article Number 03022
Number of page(s) 6
Section Intelligent Social Change and Women's Artistic Expression
DOI https://doi.org/10.1051/shsconf/202315503022
Published online 12 January 2023
  1. M.-H. Huang, R. Rust, and V. Maksimovic, “The Feeling Economy: Managing in the Next Generation of Artificial Intelligence (AI),” California Management Review, vol. 61, no. 4 pp. 43–65, Aug. 2019, doi: 10.1177/0008125619863436. [CrossRef] [Google Scholar]
  2. J. Amankwah-Amoah and Y. Lu, “Harnessing AI for business development: a review of drivers and challenges in Africa,” Production Planning & Control, vol. 0, no. 0 pp. 1–10, Apr. 2022, doi: 10.1080/09537287.2022.2069049. [Google Scholar]
  3. C. Campbell, S. Sands, C. Ferraro, H.-Y. Tsao, and A. Mavrommatis, “From data to action: How marketers can leverage AI,” Business Horizons, vol. 63, no. 2 pp. 227–243, Mar. 2020, doi: 10.1016/j.bushor.2019.12.002. [CrossRef] [Google Scholar]
  4. K. Sowa, A. Przegalinska, and L. Ciechanowski, “Cobots in knowledge work: Human - AI collaboration in managerial professions,” Journal of Business Research, vol. 125, pp. 135–142, Mar. 2021, doi: 10.1016/j.jbusres.2020.11.038. [Google Scholar]
  5. M.-H. Huang and R. T. Rust, “Artificial Intelligence in Service,” Journal of Service Research, vol. 21, no. 2 pp. 155–172, May 2018, doi: 10.1177/1094670517752459. [Google Scholar]
  6. A. Jaiswal, C. J. Arun, and A. Varma, “Rebooting employees: upskilling for artificial intelligence in multinational corporations,” The International Journal of Human Resource Management, vol. 33, no. 6 pp. 1179–1208, Mar. 2022, doi: 10.1080/09585192.2021.1891114. [Google Scholar]
  7. M. H. Jarrahi, “Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making,” Business Horizons, vol. 61, no. 4 pp. 577–586, Jul. 2018, doi: 10.1016/j.bushor.2018.03.007. [CrossRef] [Google Scholar]
  8. P. Puranam, “Human-AI collaborative decisionmaking as an organization design problem,” J Org Design, vol. 10, no. 2 pp. 75–80, Jun. 2021, doi: 10.1007/s41469-021-00095-2. [Google Scholar]
  9. N. Malik, S. Tripathi, A. Kar, and S. Gupta, “Impact of Artificial Intelligence on Employees working in Industry 4.0 Led Organizations,” International Journal of Manpower, May 2021, doi: 10.1108/IJM-03-2021-0173. [Google Scholar]
  10. C. B. Califf, S. Sarker, and S. Sarker, “The Bright and Dark Sides of Technostress: A Mixed-Methods Study Involving Healthcare IT,” p. 49. [Google Scholar]
  11. Y. R. Shrestha, S. M. Ben-Menahem, and G. von Krogh, “Organizational Decision-Making Structures in the Age of Artificial Intelligence,” California Management Review, vol. 61, no. 4 pp. 66–83, Aug. 2019, doi: 10.1177/0008125619862257. [CrossRef] [Google Scholar]
  12. C. Brod, Technostress: the human cost of the computer revolution. Reading, Mass.: Addison- Wesley, 1984. Accessed: Jun. 22, 2022. [Online]. Available: http://archive.org/details/technostresshuma0000brod [Google Scholar]
  13. R. Ayyagari, V. Grover, and R. Purvis, “Technostress: Technological Antecedents and Implications,” MIS Quarterly, vol. 35, pp. 831–858, Dec. 2011, doi: 10.2307/41409963. [Google Scholar]
  14. A. Suh and J. Lee, “Understanding teleworkers’ technostress and its influence on job satisfaction,” INTR, vol. 27, no. 1 pp. 140–159, Feb. 2017, doi: 10.1108/IntR-06-2015-0181. [CrossRef] [Google Scholar]
  15. D. M. Marchiori, E. W. Mainardes, and R. G. Rodrigues, “Do Individual Characteristics Influence the Types of Technostress Reported by Workers?,” International Journal of Human-Computer Interaction, vol. 35, no. 3 pp. 218–230, Feb. 2019, doi: 10.1080/10447318.2018.1449713.16. [CrossRef] [Google Scholar]
  16. M. Tarafdar, Q. Tu, B.S. Ragu-Nathan, and T.S. Ragu-Nathan, “The Impact of Technostress on Role Stress and Productivity,” Journal of Management Information Systems, vol. 24, no. 1 pp. 301–328, Jul. 2007, doi: 10.2753/MIS0742-1222240109. [Google Scholar]
  17. M. M. Rahman, T. Ming, T. Baigh, and M. Sarker, “Adoption of artificial intelligence in banking services: an empirical analysis,” International Journal of Emerging Markets, vol. ahead-of-print, Dec. 2021, doi: 10.1108/IJOEM-06-2020-0724. [Google Scholar]
  18. P. Meyer, J. Jonas, and A. Roth, “Frontline Employees’ Acceptance of and Resistance to Service Robots in Stationary Retail - An Exploratory Interview Study,” Journal of Service Management Research, vol. 4, pp. 21–34, Jan. 2020, doi: 10.15358/2511-8676-2020-121. [Google Scholar]
  19. A. Arslan, C. Cooper, Z. Khan, I. Golgeci, and I. Ali, “Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies,” International Journal of Manpower, vol. 43, no. 1 pp. 75–88, Jan. 2021, doi: 10.1108/IJM-01-2021-0052. [Google Scholar]
  20. T.-J. Wu, J.-M. Li, and Y. J. Wu, “Employees’ job insecurity perception and unsafe behaviours in human-machine collaboration,” Management Decision, vol. ahead-of-print, no. ahead-of-print, Jan. 2022, doi: 10.1108/MD-09-2021-1257. [Google Scholar]
  21. H. Kong, Y. Yuan, Y. Baruch, N. Bu, X. Jiang, and K. Wang, “Influences of artificial intelligence (AI) awareness on career competency and job burnout,” IJCHM, vol. 33, no. 2 pp. 717–734, Mar. 2021, doi: 10.1108/IJCHM-07-2020-0789. [CrossRef] [Google Scholar]
  22. S. Ransbotham, P. Gerbert, M. Reeves, D. Kiron, and M. Spira, “Artificial Intelligence in Business Gets Real,” MIT SMR, Sep. 2018, Accessed: Jun. 23, 2022. [Online]. Available: https://sloanreview.mit.edu/projects/artificial-intelligence-in-business-gets-real/ [Google Scholar]
  23. P. Bedué and A. Fritzsche, “Can we trust AI? An empirical investigation of trust requirements and guide to successful AI adoption,” JEIM, vol. 35, no. 2 pp. 530–549, Mar. 2022, doi: 10.1108/JEIM-06-2020-0233. [CrossRef] [Google Scholar]
  24. G. Cao, Y. Duan, J. S. Edwards, and Y. K. Dwivedi, “Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making,” Technovation, vol. 106, p. 102312, Aug. 2021, doi: 10.1016/j.technovation.2021.102312. [Google Scholar]
  25. E. Kambur and C. Akar, “Human resource developments with the touch of artificial intelligence: a scale development study,” IJM, vol. 43, no. 1 pp. 168–205, Apr. 2022, doi: 10.1108/IJM-04-2021-0216. [CrossRef] [Google Scholar]
  26. Y. Suseno, C. Chang, M. Hudik, and E. S. Fang, “Beliefs, anxiety and change readiness for artificial intelligence adoption among human resource managers: the moderating role of high-performance work systems,” The International Journal of Human Resource Management, vol. 33, no. 6 pp. 1209–1236, Mar. 2022, doi: 10.1080/09585192.2021.1931408. [Google Scholar]
  27. A.P. Henkel, S. Bromuri, D. Iren, and V. Urovi, “Half human, half machine - augmenting service employees with AI for interpersonal emotion regulation,” Journal of Service Management, vol. 31, no. 2 pp. 247–265, Jan. 2020, doi: 10.1108/JOSM-05-2019-0160. [Google Scholar]
  28. D. Vorobeva, Y. El Fassi, D. Costa Pinto, D. Hildebrand, M. M. Herter, and A. S. Mattila, “Thinking Skills Don’t Protect Service Workers from Replacement by Artificial Intelligence,” Journal of Service Research, pp. 1–13, May 2022, doi: 10.1177/10946705221104312. [Google Scholar]
  29. Y. Choi, “A study of employee acceptance of artificial intelligence technology,” European Journal of Management and Business Economics, vol. 30, no. 3 pp. 318–330, Jan. 2021, doi: 10.1108/EJMBE-06-2020-0158. [CrossRef] [Google Scholar]
  30. E. Glikson and A. W. Woolley, “Human Trust in Artificial Intelligence: Review of Empirical Research,” ANNALS, vol. 14, no. 2 pp. 627–660, Jul. 2020, doi: 10.5465/annals.2018.0057. [CrossRef] [Google Scholar]
  31. M. Charalampous, C. A. Grant, C. Tramontano, and E. Michailidis, “Systematically reviewing remote eworkers’ well-being at work: a multidimensional approach,” European Journal of Work and Organizational Psychology, vol. 28, no. 1 pp. 51–73, Jan. 2019, doi: 10.1080/1359432X.2018.1541886. [CrossRef] [Google Scholar]
  32. A. Braganza, W. Chen, A. Canhoto, and S. Sap, “Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust,” Journal of Business Research, vol. 131, pp. 485–494, Jul. 2021, doi: 10.1016/jjbusres.2020.08.018. [Google Scholar]
  33. J. Smids, S. Nyholm, and H. Berkers, “Robots in the Workplace: a Threat to—or Opportunity for— Meaningful Work?,” Philosophy & Technology, vol. 3, no. 33, pp. 503–522, 2020, doi: https://doi.org/10.1007/s13347-019-00377-4. [Google Scholar]
  34. S. Chandra, A. Shirish, and S. Srivastava, “Does Technostress Inhibit Employee Innovation? Examining the Linear and Curvilinear Influence of Technostress Creators,” Communications of the Association for Information Systems, vol. 44, no. 1, Mar. 2019, doi: 10.17705/1CAIS.04419. [Google Scholar]
  35. M.-H. Huang and R. T. Rust, “A strategic framework for artificial intelligence in marketing,” J. of the Acad. Mark. Sci., vol. 49, no. 1 pp. 30–50, Jan. 2021, doi: 10.1007/s11747-020-00749-9. [Google Scholar]
  36. E. Solberg, M. Kaarstad, M. H. R. Eitrheim, R. Bisio, K. Reegård, and M. Bloch, “A Conceptual Model of Trust, Perceived Risk, and Reliance on AI Decision Aids,” Group & Organization Management, vol. 47, no. 2 pp. 187–222, Apr. 2022, doi: 10.1177/10596011221081238. [CrossRef] [Google Scholar]

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