Understanding How Leadership Can Help Reduce Occupational Stress Faced by Gig Economy Workers: Case Study of Ride Sharing Services in the US
DOI:
https://doi.org/10.65080/ajbmss.v2i1.CM2621101021Keywords:
Algorithmic leadership, occupational stress, gig economy, ride-sharing platforms, income stability, work environment support, worker autonomy, leadership styleAbstract
Introduction: The paper analyzed the effects of leadership on occupational stress among employees in the US gig economy. It also examined how income stability, worker autonomy, and work environment impact occupational stress among gig workers.
Methods: The study used a primary quantitative research design. A survey was conducted among a sample of 200 employees in the US gig economy. The survey instrument was the Multifactor Leadership Questionnaire (MLQ), which used Likert scaling. The structured data were analyzed using the PLS-SEM approach in SmartPLS.
Results: The study indicated a statistically significant relationship between occupational stress and Work Environment Support (β = 0.400, p < 0.001). Also, leadership Style is positively and significantly correlated with Occupational Stress (β = 0.202, p = 0.001). Income stability had a negligible effect on occupational stress (β = 0.1, p = 0.06). Worker Autonomy Interaction with Leadership Style on occupational stress is insignificant (β = 0.012, p = 0.820). The study similarly finds insignificant interactions between Worker Autonomy and Income Stability (β = 0.054, p = 0.203) and between Worker Autonomy and Work Environment Support (β = 0.046, p = 0.424).
Conclusion: The findings of the study indicate that to decrease the occupational stress in the employees of the gig-economy, it is necessary to encourage the resource-strengthening leadership, provide better income stability and the platform environment. Since autonomy has proven to have no protective power by itself, leadership and management should combine flexibility with the practical assistance and communication improvement.
Downloads
References
Abkhezr, P., & Tang, M. (2024). Systemic case-study explorations of the career development of middle-aged male immigrants from New Zealand working in the Australian ride-share industry. British Journal of Guidance & Counselling, 52(5), 918-938. https://doi.org/10.1080/03069885.2023.2247543
Adler, L. (2021). Framing disruption: How a regulatory capture frame legitimized the deregulation of Boston’s ride-for-hire industry. Socio-Economic Review, 19(4), pp.1421-1450. https://doi.org/10.1093/ser/mwab020
Ali, K.M., & Sivasubramanian, R.C. (2024). Understanding the Nexus Between Techno-Stress, Psychological Well-Being, and the Moderating Role of Job Resources in the Gig Economy. Employee Responsibilities and Rights Journal, 1-23. https://doi.org/10.1007/s10672-024-09505-5
Asfahani, A., Alsobahi, G., & Dahlan, D. (2023). Navigating the Saudi Gig Economy: The Role of Human Resource Practices in Enhancing Job Satisfaction and Career Sustainability. Sustainability, 15(23), 16406.
https://doi.org/10.3390/su152316406
Batista-Foguet, J. M., Esteve, M., & van Witteloostuijn, A. (2021). Measuring leadership an assessment of the Multifactor Leadership Questionnaire. Plos one, 16(7), e0254329. https://doi.org/10.1371/journal.pone.0254329
Bernhardt, A., Kresge, L., & Suleiman, R. (2023). The data-driven workplace and the case for worker technology rights. ILR Review, 76(1), 3-29.
https://doi.org/10.1177/00197939221131558
Cameron, L. D., Chan, C. K., & Anteby, M. (2022). Heroes from above but not (always) from within? Gig workers’ reactions to the sudden public moralization of their work. Organizational Behavior and Human Decision Processes, 172, 104179. https://doi.org/10.1016/j.obhdp.2022.104179
Caza, B. B., Reid, E. M., Ashford, S. J., & Granger, S. (2022). Working on my own: Measuring the challenges of gig work. Human relations, 75(11), 2122-2159. https://doi.org/10.1177/00187267211030098
Clausen, T., Pedersen, L. R. M., Andersen, M. F., Theorell, T., & Madsen, I. E. (2022). Job autonomy and psychological well-being: A linear or a non-linear association? European Journal of Work and Organizational Psychology, 31(3), 395-405. https://doi.org/10.1080/1359432X.2021.1972973
Cropanzano, R., Keplinger, K., Lambert, B. K., Caza, B., & Ashford, S. J. (2023). The organizational psychology of gig work: An integrative conceptual review. Journal of Applied Psychology, 108(3), 492. https://doi.org/10.1037/apl0001029
Dolber, B., Rodino-Colocino, M., Kumanyika, C., & Wolfson, T. (Eds.). (2021). The gig economy: Workers and media in the age of convergence. (pp. 3-15), Routledge. https://doi.org/10.4324/9781003140054
El Bourkadi, S. (2023). Uber structure's managerial algorithmic communication and drivers' health issues: sensemaking of work strategic resistance. Frontiers in Communication, 8, 1213679. https://doi.org/10.3389/fcomm.2023.1213679
Fischer, H. E., Boone, W. J., & Neumann, K. (2023). Quantitative research designs and approaches. In Handbook of research on science education (pp. 28-59). Routledge. https://doi.org/10.4324/9780367855758-3
Jaaron, A. A., Pham, D. T., & Cogonon, M. E. (2023). Systems thinking to facilitate “double loop” learning in tourism industry: A COVID-19 response strategy. Journal of Sustainable Tourism, 31(4), 1032-1050.
https://doi.org/10.1080/09669582.2021.1948554
Jain, H., Padmanabhan, B., Pavlou, P. A., & Raghu, T. S. (2021). Editorial for the special section on humans, algorithms, and augmented intelligence: The future of work, organizations, and society. Information Systems Research, 32(3), 675-687. https://doi.org/10.1287/isre.2021.1046
Keith, M. G., Harms, P. D., & Long, A. C. (2020). Worker health and well-being in the gig economy: A proposed framework and research agenda. Entrepreneurial and Small Business Stressors, Experienced Stress, and Well-Being, 1-33.
https://doi.org/10.1108/S1479-355520200000018002
Krzywdzinski, M., & Gerber, C. (2020). Varieties of platform work. Platforms and social inequality in Germany and the United States (No. 7). Weizenbaum Series. http://dx.doi.org/10.34669/wi.ws/7
Kuhn, K. M., Meijerink, J., & Keegan, A. (2021). Human resource management and the gig economy: Challenges and opportunities at the intersection between organizational HR decision-makers and digital labor platforms. Research in Personnel and Human Resources Management, 39, 1-46.
https://doi.org/10.1108/S0742-730120210000039001
Malik, M., & Raziq, M. M. (2022). Digital leadership and the GIG Economy. In Sustainability in the Gig Economy: Perspectives, Challenges and Opportunities in Industry 4.0 (pp. 99-110). Singapore: Springer Nature Singapore.
https://doi.org/10.1007/978-981-16-8406-7_7
Maragheh, O., Rouholamini, M., & Nabavichashme, A. (2024). Evaluating the impact of decision-makers and managers’ characteristics on the export development of SMEs by grounded theory and structural equations approaches. International Journal of Nonlinear Analysis and Applications, 15(8), 135-147. https://doi.org/10.22075/ijnaa.2023.31041.4552
Minderop, I., & Weiß, B. (2023). Now, later, or never? Using response-time patterns to predict panel attrition. International Journal of Social Research Methodology, 26(6), 693-706. https://doi.org/10.1080/13645579.2022.2091259
Möhlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021). Algorithmic management of work on online labor platforms: When matching meets control. MIS Quarterly, 45(4), 1999-2022. https://doi.org/10.25300/MISQ/2021/15333
Moorman, R. H., Lyons, B. D., Mercado, B. K., & Klotz, A. C. (2024). Driving the extra mile in the gig economy: the motivational foundations of gig worker citizenship. Annual Review of Organizational Psychology and Organizational Behavior, 11(1), 363-391.
https://doi.org/10.1146/annurev-orgpsych-111821-033012
Oruh, E. S., Mordi, C., Dibia, C. H., & Ajonbadi, H. A. (2021). Exploring compassionate managerial leadership style in reducing employee stress level during COVID-19 crisis: the case of Nigeria. Employee Relations: The International Journal, 43(6), 1362-1381. https://doi.org/10.1108/ER-06-2020-0302
Ray, B., Sengupta, A., & Varma, A. (2024). The gig verse: building a sustainable future. International Journal of Organizational Analysis, 32(10), 2275-2298.
https://doi.org/10.1108/IJOA-08-2023-3946
Roemer, E., Schuberth, F., & Henseler, J. (2021). HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling. Industrial Management & Data Systems, 121(12), 2637-2650.
https://doi.org/10.1108/IMDS-02-2021-0082
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of Market Research (pp. 587-632). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-2
Shannon, B., Friedman, L. S., Hellinger, A., Almberg, K., & Ehsani, J. (2024). Work-related crashes in rideshare drivers in the United States. Journal of Safety Research, 89, 13-18. http://dx.doi.org/10.1016/j.jsr.2024.01.005
Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4-11. https://doi.org/10.12691/ajams-9-1-2
Shafie, S. G. (2024). Work Stress in The Public Sector: An Analysis of Occupational Stress Indicator Factors Among Healthcare Employees in Malaysia. Journal Contemporary of Islamic Counselling Perspective. Available from: https://jcicp.unishams.edu.my/images/vol%203%20no%201%202024/8-WORK%20STRESS%20IN%20THE%20PUBLIC%20SECTOR%20AN%20ANALYSIS%20OF%20OCCUPATIONAL%20STRESS%20INDICATOR%20FACTORS%20AMONG%20HEALTHCARE%20EMPLOYEES%20IN%20MALAYSIA-%20SHARIZAL.pdf
Silva, M., & Nyobe, S. (2023). Social sustainability in the gig economy era: insights from the on-demand delivery sector. Revue Française de Gestion Industrielle, 37(1), 55-69. https://doi.org/10.53102/2023.37.01.1140
South, L., Saffo, D., Vitek, O., Dunne, C., & Borkin, M. A. (2022, June). Effective use of Likert scales in visualization evaluations: A systematic review. In Computer Graphics Forum, 41(3), 43-55. https://doi.org/10.1111/cgf.14521
Tassinari, A., & Maccarrone, V. (2020). Riders on the storm: Workplace solidarity among gig economy couriers in Italy and the UK. Work, Employment and Society, 34(1), 35-54. https://doi.org/10.1177/0950017019862954
Watson, G., Kistler, L., Graham, B., & Sinc. (2021). Looking at the gig picture: Defining gig work and explaining profile differences in gig workers’ job demands and resources. Group & Organization Management, 46(2), 327-361. https://doi.org/10.1177/1059601121996548
Woodcock, J. (2021). The fight against platform capitalism: An inquiry into the global struggles of the gig economy (Vol. 20). University of Westminster Press, 127. Available from: https://library.oapen.org/bitstream/id/ec7fb7dd-01be-4bfc-bbab-b12132393bc5/the-fight-against-platform-capitalism.pdf
Zeuge, A., Lemmer, K., Klesel, M., Kordyaka, B., Jahn, K., & Niehaves, B. (2023). To be or not to be stressed: Designing autonomy to reduce stress at work. Work, 75(4), 1199-1213. https://doi.org/10.3233/WOR-220177
Zhang, A. H. (2022). Agility over stability: China's great reversal in regulating the platform economy. Harv. Int'l LJ, 63, 457. https://dx.doi.org/10.2139/ssrn.3892642
Zhu, G., Huang, J., Lu, J., Luo, Y., & Zhu, T. (2024). Gig to the left, algorithms to the right: A case study of the dark sides in the gig economy. Technological Forecasting and Social Change, 199, 123018.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ishaq Kalanther (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.