References
Agbeyinka, I. Y. (2025). Examining the psychological and ethical impacts of algorithmic management across cultural contexts in platform labour. Journal of Technology and Labour Studies, 6(1). Ajunwa, I., Crawford, K., & Schultz, J. (2017). Limitless worker surveillance. California Law Review, 105(3), 735–776. Bakker, A. B., & de Vries, J. D. (2021). Job demands–resources theory and self-regulation: New explanations and remedies for job burnout. Anxiety, Stress, & Coping, 34(1), 1– 21. Bakker, A. B., & Demerouti, E. (2017). Job Demands–Resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273–285. Bakker, A. B., & Oerlemans, W. G. M. (2011). Subjective well-being in organisations. In K. S. Cameron & G. M. Spreitzer (Eds.), The Oxford handbook of positive organizational scholarship (pp. 178–189). Oxford University Press. Ball, K. (2021). Electronic monitoring and surveillance in the workplace. In S. J. Zaccaro & R. J. Klimoski (Eds.), The Oxford handbook of organisational psychology (2nd ed.). Oxford University Press. Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with Computers, 23(1), 4–17. Bednar, P. M., & Welch, C. (2020). Socio-technical perspectives on smart working: Creating meaningful and sustainable systems. Information Systems Frontiers, 22(2), 281–298. CIPD. (2023). Health and wellbeing at work 2023. Chartered Institute of Personnel and Development. Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The Job Demands– Resources model of burnout. Journal of Applied Psychology, 86(3), 499–512. Dodge, R., Daly, A. P., Huyton, J., & Sanders, L. D. (2012). The challenge of defining wellbeing. International Journal of Wellbeing, 2(3), 222–235. Fisher, C. D. (2014). Conceptualising and measuring wellbeing at work. In P. Y. Chen & C. L. Cooper (Eds.), Wellbeing: A complete reference guide (Vol. 3, pp. 9–33). Wiley- Blackwell. Glavin, P., Bierman, A., & Schieman, S. (2024). Private eyes, they see your every move: Workplace surveillance and worker well-being. Socius: Sociological Research for a Dynamic World, 10. Grant, A. M., Christianson, M. K., & Price, R. H. (2007). Happiness, health, or relationships? Managerial practices and employee well-being trade-offs. Academy of Management Perspectives, 21(3), 51–63. Guest, D. E. (2017). Human resource management and employee well-being: Towards a new analytic framework. Human Resource Management Journal, 27(1), 22–38. Hennum Nilsson, K., Bodin, T., Strauss, P., Matilla-Santander, N., Badarin, K., Brulin, E., & Håkansta, C. (2025). Algorithmic management is associated with psychological distress, musculoskeletal pain, and occupational accidents: A cross-sectional study in logistics. International Archives of Occupational and Environmental Health, 98, 929–942. International Labour Organization. (2022). World employment and social outlook: Trends 2022. International Labour Organization. Jukic, T., Ihan, A., Strojnik, V., Stubljar, D., & Starc, A. (2020). The effect of active occupational stress management on psychosocial and physiological wellbeing: A pilot study. BMC Medical Informatics and Decision Making, 20, 321. Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. Meijerink, J., & Bondarouk, T. (2023). Algorithmic management and human resource management: A systematic literature review. Human Resource Management Review, 33(2), 100940. Miebaka Chidiebere Tamunomiebi, Goodluck Prince Uhuru (2018) 'Group, Teams and Tasks in the Organization: A Historical Escortion,' European Journal of Business and Management Research, European Open Science, vol. 3(4), October. Moore, P. V. (2020). The quantified self in precarity: Work, technology and what counts. Routledge. Nielsen, K., Yarker, J., Munir, F., & Bültmann, U. (2023). Workplace resources, job demands and employee wellbeing: Contemporary perspectives on the Job Demands–Resources model. Work & Stress, 37(2), 101–118. Pasmore, W., Winby, S., Mohrman, S. A., & Vanasse, R. (2019). Reflections: Sociotechnical systems design and organisation change. Journal of Change Management, 19(2), 67– 85. Ravid, D. M., Tomczak, D. L., White, J. B., & Behrend, T. S. (2020). EPM 20/20: A review, framework and research agenda for electronic performance monitoring. Journal of Management, 46(1), 100–126. Schaufeli, W. B., & Taris, T. W. (2014). A critical review of the Job Demands–Resources model: Implications for improving work and health. In G. F. Bauer & O. Hämmig (Eds.), Bridging occupational, organisational and public health (pp. 43–68). Springer. Sun, T., Zhang, Y., Liu, H., & Wang, X. (2023). Algorithmic management and employee well- being: A systematic review. Human Resource Management Review, 33(4), 101002. Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal getting. Human Relations, 4(1), 3–38. Vuković, M., Jaklič, J., & Popovič, A. (2022). Influence of algorithmic management practices on workplace well-being: Evidence from European organisations. Information Technology & People, 36(8), 21–42. Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2019). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy. Work, Employment and Society, 33(1), 56–75. World Health Organization. (2022). WHO guidelines on mental health at work. World Health Organization. Zayid, H., Alzubi, A., Berberoğlu, A., & Khadem, A. (2024). How do algorithmic management practices affect workforce well-being? A parallel moderated mediation model. Behavioral Sciences, 14(12), 1123.