Job Demands and Stress Resilience of Gig Workforce : Implications for Performance and Burnout
Authors
-
Nisha Sharma
Research Scholar (Corresponding Author), Sharda University, Plot: 32-34, Knowledge Park III, Greater Noida - 201 310, Uttar Pradesh. & Assistant Professor, G. L. Bajaj Institute of Technology & Management, Plot: 2, APJ Abdul Kalam Road, Knowledge Park III, Greater Noida - 201 306, Uttar Pradesh
https://orcid.org/0009-0003-5904-6054
-
Pooja Tiwari
Associate Professor, Sharda University, Plot No. 32-34, Knowledge Park III, Greater Noida - 201 310, Uttar Pradesh
https://orcid.org/0000-0003-2269-7083
- Samarth Sharma Associate Professor, G. L. Bajaj Institute of Technology & Management, Plot No. 2, APJ Abdul Kalam Road, Knowledge Park III, Greater Noida - 201 306, Uttar Pradesh
DOI:
https://doi.org/10.17010/pijom/2026/v19i5/175075Keywords:
gig work, burnout, job demands, work engagement, job performance, stress resilience.JEL Classification Codes : J28, J24, J81
Publication Chronology: Paper Submission Date : September 15, 2025 ; Paper sent back for Revision : March 15, 2026 ; Paper Acceptance Date : April 15, 2026 ; Paper Published Online : May 15, 2026.
Abstract
Purpose : This study explored the factors affecting gig workers in developing economies by focusing on stress resilience, mental health, and work performance of gig workers.
Methodology : The study adopted a quantitative, explanatory research design employing purposive sampling. A total of 401 questionnaires were distributed via social media groups associated with gig work platforms, of which 351 were completed and returned, providing the final dataset for analysis. The instrument included established and validated scales to assess burnout, job demand, boundary management, digital overload, resilience, work engagement, gig-specific factors, and job performance via Smart-PLS.
Findings : The findings revealed that job demands, together with digital overload, contributed to burnout, while job resources had a significant impact on work engagement compared to boundary management enhancement. Additionally, gig-specific factors and resilience significantly enhanced the performance of gig workers.
Practical Implications : The results clearly indicated that organizations need to monitor job demands and manage digital overload to mitigate burnout among gig workers. To strengthen job resources like fair policies, optimizing work engagement, and retraining support for individual well-being, policymakers should address these issues well. Platform and HR Practitioners should introduce training modules to improve workers’ resilience and work–life balance as well as job performance. Organizations could create a healthy work environment and improve productivity by addressing these aspects.
Originality : Unlike prior research on gig work, this study provided not only a theoretical understanding but also a practical perspective on the long-term consequences of gig workers’ burnout, work engagement, and job performance, while drawing attention to platform companies’ approach toward gig work.
Contribution : This study contributed to extending the JD-R model by integrating elements of digital overload and job demands as antecedents influencing burnout. Resilience is an important resource, demonstrating that job resources have a significantly greater impact on performance outcomes than boundary management. The research conceptually advances the existing model.
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1) Adisa, T. A., & Gbadamosi, G. (2021). Work-life border control model: A re-think of border theory. In Work-life interface: Non-Western perspectives (pp. 25–53). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-66648-4_2
2) Adisa, T. A., Antonacopoulou, E., Beauregard, T. A., Dickmann, M., & Adekoya, O. D. (2022). Exploring the impact of COVID-19 on employees' boundary management and work–life balance. British Journal of Management, 33(4), 1694–1709. https://doi.org/10.1111/1467-8551.12643
3) Anh, L. E., Whelan, E., & Umair, A. (2023). 'You're still on mute': A study of video conferencing fatigue during the COVID-19 pandemic from a technostress perspective. Behaviour & Information Technology, 42(11), 1758–1772. https://doi.org/10.1080/0144929X.2022.2095304
4) Arble, E., Daugherty, A. M., & Arnetz, B. B. (2018). Models of first responder coping: Police officers as a unique population. Stress and Health, 34(5), 612–621. https://doi.org/10.1002/smi.2821
5) Ashford, S. J., Caza, B. B., & Reid, E. M. (2018). From surviving to thriving in the gig economy: A research agenda for individuals in the new world of work. Research in Organizational Behavior, 38, 23–41. https://doi.org/10.1016/j.riob.2018.11.001
6) Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831–A10. https://doi.org/10.2307/41409963
7) Bakker, A. B. (2011). An evidence-based model of work engagement. Current Directions in Psychological Science, 20(4), 265–269. https://doi.org/10.1177/0963721411414534
8) Bakker, A. B., & Demerouti, E. (2014). Job demands–resources theory. In J. L. Huppert, B. Keverne, & N. Baylis (eds.), Well-being: A complete reference guide (Vol. 3, pp. 1–28). Wiley-Blackwell. https://doi.org/10.1002/9781118539415.wbwell019
9) Baron, R. A., Franklin, R. J., & Hmieleski, K. M. (2016). Why entrepreneurs often experience low, not high, levels of stress: The joint effects of selection and psychological capital. Journal of Management, 42(3), 742–768. https://doi.org/10.1177/0149206313495411
10) Basile, K. A., & Beauregard, T. A. (2020). Boundary management: Getting the work–home balance right. In Agile working and well-being in the digital age (pp. 35–46). Springer. https://doi.org/10.1007/978-3-030-60283-3_3
11) Berg, J. (2015). Income security in the on-demand economy: Findings and policy lessons from a survey of crowdworkers. SSRN. https://ssrn.com/abstract=2740940
12) Bernhardt, A., Campos, C., Prohofsky, A., Ramesh, A., & Rothstein, J. (2023). Independent contracting, self-employment, and gig work: Evidence from California tax data. ILR Review, 76(2), 357–386. https://doi.org/10.1177/00197939221103525
13) BetterPlace. (2023). India's frontline workforce report 2023. BetterPlace.
14) Beuren, I. M., dos Santos, V., & Theiss, V. (2022). Organizational resilience, job satisfaction and business performance. International Journal of Productivity and Performance Management, 71(6), 2262–2279. https://doi.org/10.1108/IJPPM-03-2021-0158
15) Bliese, P. D., Edwards, J. R., & Sonnentag, S. (2017). Stress and well-being at work: A century of empirical trends reflecting theoretical and societal influences. Journal of Applied Psychology, 102(3), 389–402. https://doi.org/10.1037/apl0000109
16) Boston Consulting Group & Michael & Susan Dell Foundation. (2021). Unlocking the potential of the gig economy in India. https://www.bcg.com/unlocking-gig-economy-in-india
17) Bouwhuis, S., Hoekstra, T., Bongers, P. M., Boot, C. R. L., Geuskens, G. A., & van der Beek, A. J. (2019). Distinguishing groups and exploring health differences among multiple job holders aged 45 years and older. International Archives of Occupational and Environmental Health, 92(1), 67–79. https://doi.org/10.1007/s00420-018-1351-2
18) Capitano, J., McAlpine, K. L., & Greenhaus, J. H. (2019). Organizational influences on work–home boundary permeability: A multidimensional perspective. In Research in personnel and human resources management (Vol. 37, pp. 133–172). Emerald Publishing. https://doi.org/10.1108/S0742-730120190000037005
19) 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
20) Chandel, S., Chanda, K., & Chandel, K. (2023). Factors influencing organizational commitment, job involvement, and work–life balance among employees of banks: An analysis. Prabandhan: Indian Journal of Management, 16(7), 43–58. https://doi.org/10.17010/pijom/2023/v16i7/172927
21) Cheah, J.-H., Magno, F., & Cassia, F. (2024). Reviewing the SmartPLS 4 software: The latest features and enhancements. Journal of Marketing Analytics, 12, 97–107. https://doi.org/10.1057/s41270-023-00266-y
22) Cingiene, J. (2024). Exploring meanings of work–nonwork boundaries [Doctoral dissertation, Queen Mary University of London].
23) Connor, K. M., & Davidson, J. R. T. (2003). Development of a new resilience scale: The Connor–Davidson Resilience Scale (CD-RISC). Depression and Anxiety, 18(2), 76–82. https://doi.org/10.1002/da.10113
24) Cram, W. A., Wiener, M., Tarafdar, M., & Benlian, A. (2022). Examining the impact of algorithmic control on Uber drivers' technostress. Journal of Management Information Systems, 39(2), 426–453. https://doi.org/10.1080/07421222.2022.2063556
25) Cruz, D., & Meisenbach, R. (2018). Expanding role boundary management theory: How volunteering highlights contextually shifting strategies and collapsing work–life role boundaries. Human Relations, 71(2), 182–205. https://doi.org/10.1177/0018726717718917
26) Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316. https://doi.org/10.25300/MISQ/2015/39.2.02
27) Dimri, A., Kumar, P., & Jain, V. K. (2024). Unraveling job embeddedness in the Indian hotel sector: Investigating turnover and retention. Prabandhan: Indian Journal of Management, 17(6), 27–45. https://doi.org/10.17010/pijom/2024/v17i6/173559
28) Eapen, S., Shamshuddin, S., & Mayur, S. J. (2025). Empowering educators: Self-efficacy and psychological safety in driving employee engagement. Prabandhan: Indian Journal of Management, 18(7), 47–57. https://doi.org/10.17010/pijom/2025/v18i7/174564
29) Fischer, T., & Riedl, R. (2022). On the stress potential of an organisational climate of innovation: A survey study in Germany. Behaviour & Information Technology, 41(4), 805–826. https://doi.org/10.1080/0144929X.2020.1836258
30) Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
31) Gedam, R. K., Mehta, N., & Date, H. (2022). Antecedents of career decision-making self-efficacy and its impact on job satisfaction: A study in the Indian IT industry. Prabandhan: Indian Journal of Management, 15(11), 43–62. https://doi.org/10.17010/pijom/2022/v15i11/172522
32) Hafeez, S., Gupta, C., & Sprajcer, M. (2022). Stress and the gig economy: It's not all shifts and giggles. Industrial Health, 61(2), 140–150. https://doi.org/10.2486/indhealth.2022-0005
33) Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
34) Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151. https://doi.org/10.2753/MTP1069-6679190202
35) Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
36) Hemavathi, G., & Justus, F. S. (2023). Flexibility culture, person–job fit, and job benefits as predictors of eudaimonic workplace well-being and turnover intention of employees. Prabandhan: Indian Journal of Management, 16(10), 46–60. https://doi.org/10.17010/pijom/2023/v16i10/171900
37) Henly, J. R., & Lambert, S. J. (2014). Unpredictable work timing in retail jobs: Implications for employee work–life conflict. ILR Review, 67(3), 986–1016. https://doi.org/10.1177/0019793914537458
38) Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8
39) Hoyt, M. A., Wang, A. W.-A., Boggero, I. A., Eisenlohr-Moul, T. A., Stanton, A. L., & Segerstrom, S. C. (2020). Emotional approach coping in older adults as predictor of physical and mental health. Psychology and Aging, 35(4), 591–603. https://doi.org/10.1037/pag0000463
40) Huang, S., van der Veen, R., & Song, Z. (2018). The impact of coping strategies on occupational stress and turnover intentions among hotel employees. Journal of Hospitality Marketing & Management, 27(8), 926–945. https://doi.org/10.1080/19368623.2018.1471434
41) Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20, 195–204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7
42) Kadolkar, I., Kepes, S., & Subramony, M. (2025). Algorithmic management in the gig economy: A systematic review and research integration. Journal of Organizational Behavior, 46(7), 1057–1080. https://doi.org/10.1002/job.2831
43) Kamis, A., Saibon, R. A., Yunus, F. A., Yunus, N., Rahim, M. B., Herrera, L. M., & Montenegro, Y., Luis, P., Tun, U., Onn, H., & Johor, B. P. (2020). The SmartPLS analysis approach in validity and reliability of graduate marketability instrument. Social Psychology of Education, 57(8), 987–1001.
44) Kossek, E. E., Ruderman, M. N., Braddy, P. W., & Hannum, K. M. (2012). Work–nonwork boundary management profiles: A person-centered approach. Journal of Vocational Behavior, 81(1), 112–128. https://doi.org/10.1016/j.jvb.2012.04.003
45) Kumar, S., Karani, K. P., & Aithal, S. (2024). Tech-business analytics in gig economy - A futuristic technology-supported online business model. Poornaprajna International Journal of Teaching, Research and Case Studies, 1(1), 28–59.
46) Kumari, K. T. (2025). Examining techno-stress and work–personal conflict of gig workers in the Indian IT sector: The moderating role of gender. Prabandhan: Indian Journal of Management, 18(11), 8–26. https://doi.org/10.17010/pijom/2025/v18i11/173903
47) Labrague, L. J. (2021). Psychological resilience, coping behaviours and social support among health care workers during the COVID-19 pandemic: A systematic review of quantitative studies. Journal of Nursing Management, 29(7), 1893–1905. https://doi.org/10.1111/jonm.13336
48) Labrague, L. J., McEnroe-Petitte, D., Leocadio, M. C., Bogaert, P. V., & Cummings, G. G. (2018). Stress and ways of coping among nurse managers: An integrative review. Journal of Clinical Nursing, 27(7–8), 1346–1359. https://doi.org/10.1111/jocn.14165
49) Li, Y., Xu, S., Yu, Y., & Meadows, R. (2023). The well-being of gig workers in the sharing economy during COVID-19. International Journal of Contemporary Hospitality Management, 35(4), 1470–1489. https://doi.org/10.1108/IJCHM-01-2022-0064
50) Lu, Z., Wang, S., Ling, W., & Guo, Y. (2023). Gig work and mental health during the COVID-19 pandemic: A gendered examination of comparisons with regular employment and unemployment. Social Science & Medicine, 337, Article No. 116281. https://doi.org/10.1016/j.socscimed.2023.116281
51) Maffie, M. D. (2024). Adversaries or cross-organization co-workers? Exploring the relationship between gig workers and conventional employees. ILR Review, 77(1), 3–31. https://doi.org/10.1177/00197939231194254
52) Mai, Q. D., Hill, T. D., Vila-Henninger, L., & Grandner, M. A. (2019). Employment insecurity and sleep disturbance: Evidence from 31 European countries. Journal of Sleep Research, 28, e12763. https://doi.org/10.1111/jsr.12763
53) Marchlewska, M., Green, R., Cichocka, A., Molenda, Z., & Douglas, K. M. (2022). From bad to worse: Avoidance coping with stress increases conspiracy beliefs. British Journal of Social Psychology, 61(2), 532–549. https://doi.org/10.1111/bjso.12494
54) Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Occupational Behavior, 2(2), 99–113. https://doi.org/10.1002/job.4030020205
55) Mendola, M. (2021). Working conditions in the gig economy: How new organisational models affect gig workers' well-being. International Labour Organization. https://www.ilo.org
56) Mondal, S., Sharma, A., & Panackal, N. (2025). A study of the impact of social capital on job satisfaction: The mediating and moderating role of social trust and academic leadership. Prabandhan: Indian Journal of Management, 18(4), 8–30. https://doi.org/10.17010/pijom/2025/v18i4/174314
57) Morgan, G. A., & Harmon, R. J. (2001). Data collection techniques. Journal of the American Academy of Child & Adolescent Psychiatry, 40(8), 973–976. https://doi.org/10.1097/00004583-200108000-00020
58) Murthy, R. N., & Antony, J. M. (2025). Career resilience and advancement: A research note on women in Indian IT. Prabandhan: Indian Journal of Management, 18(11), 70–84. https://doi.org/10.17010/pijom/2025/v18i11/173880
59) Nel, P., & Kotze, M. (2017). The influence of psychological resources on mineworkers' levels of burnout in a remote and isolated mining town in South Africa. The Extractive Industries and Society, 4(4), 885–892. https://doi.org/10.1016/j.exis.2017.10.002
60) NITI Aayog. (2022). India's booming gig and platform economy: Perspectives and recommendations on the future of work. Government of India.
61) Norman, S. M., Avey, J. B., Nimnicht, J. L., & Pigeon, N. G. (2010). The interactive effects of psychological capital and organizational identity on employee organizational citizenship and deviance behaviors. Journal of Leadership & Organizational Studies, 17(4), 380–391. https://doi.org/10.1177/1548051809353764
62) Panackal, N., Rautela, S., & Sharma, A. (2024). Hypothesizing the enablers of the gig economy: A TISM and MICMAC approach. Prabandhan: Indian Journal of Management, 17(7), 23–41. https://doi.org/10.17010/pijom/2024/v17i7/173635
63) Piszczek, M. M. (2017). Boundary control and controlled boundaries: Organizational expectations for technology use at the work–family interface. Journal of Organizational Behavior, 38(4), 592–611. https://doi.org/10.1002/job.2153
64) Popov, B., Miljanović, M., Stojaković, M., & Matanović, J. (2013). Work stressors, distress, and burnout: The role of coping strategies. Primenjena Psihologija, 6(4), 355–370.
65) Rathi, S., & Kumar, P. (2023). Work-life balance and work-life conflict: A bibliometric analysis. Prabandhan: Indian Journal of Management, 16(8), 45–64. https://doi.org/10.17010/pijom/2023/v16i8/173064
66) Reinke, K., & Gerlach, G. I. (2022). Linking availability expectations, bidirectional boundary management behavior and preferences, and employee well-being: An integrative study approach. Journal of Business and Psychology, 37, 695–715. https://doi.org/10.1007/s10869-021-09768-x
67) Rushton, C. H., Batcheller, J., Schroeder, K., & Donohue, P. (2015). Burnout and resilience among nurses practicing in high-intensity settings. American Journal of Critical Care, 24(5), 412–420. https://doi.org/10.4037/ajcc2015291
68) 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. https://doi.org/10.1023/A:1015630930326
69) Schneider, D., & Harknett, K. (2019). Consequences of routine work-schedule instability for worker health and well-being. American Sociological Review, 84(1), 82–114. https://doi.org/10.1177/0003122418823184
70) Schwarzer, R., & Reuter, T. (2023). Manage stress at work through preventive and proactive coping. In Principles of organizational behaviour: The handbook of evidence‐based management (3rd ed., pp. 463–482). Wiley. https://doi.org/10.1002/9781394320769
71) Sen, S., & Banerjee, S. (2024). Exploring the relationship between psychological maturity and leadership personality traits: A discourse analysis. Prabandhan: Indian Journal of Management, 17(5), 60–70. https://doi.org/10.17010/pijom/2024/v17i5/173482
72) Singh, A. P. (2017). Coping with work stress in police employees. Journal of Police and Criminal Psychology, 32(3), 225–235. https://doi.org/10.1007/s11896-016-9228-5
73) Singh, R., Sharma, A., & Mishra, M. (2024). Beyond flexibility: Exploring motivation factors influencing work satisfaction in the gig workforce. Journal of Economics and Business Aseanomics, 9(1), 1–18.
74) Stephan, U. (2018). Entrepreneurs' mental health and well-being: A review and research agenda. Academy of Management Perspectives, 32(3), 290–322. https://doi.org/10.5465/amp.2017.0001
75) Suh, A., & Lee, J. (2017). Understanding teleworkers' technostress and its influence on job satisfaction. Internet Research, 27(1), 140–159. https://doi.org/10.1108/IntR-07-2016-0207
76) Suldo, S. M., Hoffman, J. A., & Mercer, S. H. (2020). Striving for work–life balance, engaging in self-care, and preventing burnout. In Handbook of university and professional careers in school psychology (1st ed., pp. 241–258). Routledge.
77) Suvarnapathaki, P., Shah, V., Negi, S., & Rangaswamy, N. (2025). The boring and the tedious: Invisible labor in India's gig-economy [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2504.17697
78) Tara, N., & Iqbal, S. M. (2023). Examining the impact of job demands, resources and technostress on psychological well-being of gig workers: A theoretical model. Qlantic Journal of Social Sciences, 4(4), 369–378.
79) Tarafdar, M., Cooper, C. L., & Stich, J. F. (2019). The technostress trifecta—Techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6–42. https://doi.org/10.1111/isj.12169
80) Taylor, K., Van Dijk, P., Newnam, S., & Sheppard, D. (2023). Physical and psychological hazards in the gig economy system: A systematic review. Safety Science, 166, Article 106234. https://doi.org/10.1016/j.ssci.2023.106234
81) Udayakumar, H. M., Nazeer, I., & Santhosha, H. M. (2023). Digital workplace: A conceptual model for better performance in the IT industry. Human Systems Management, 42(5), 515–525. https://doi.org/10.3233/HSM-211593
82) Van Haute, E. (2021). Sampling techniques. In Research methods in the social sciences: An A–Z of key concepts. Oxford University Press.
83) Van Wingerden, J., Derks, D., & Bakker, A. B. (2017). The impact of personal resources and job crafting interventions on work engagement and performance. Human Resource Management, 56, 51–67. https://doi.org/10.1002/hrm.21758
84) Varshney, D., & Varshney, N. K. (2024). Self-concept and job performance: The mediating role of resilience. International Journal of Productivity and Performance Management, 73(5), 1563–1586. https://doi.org/10.1108/IJPPM-10-2022-0548
85) Vera, M., Martínez, I. M., Lorente, L., & Chambel, M. J. (2016). The role of self-efficacy and work engagement in protecting nursing professionals' health. The Spanish Journal of Psychology, 19, E42. https://doi.org/10.1017/sjp.2016.43
86) Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of Management, 17(3), 601–617. https://doi.org/10.1177/014920639101700305
87) 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. https://doi.org/10.1177/0950017018785616
88) Xu, X., Huang, D., & Chen, Q. (2021). Stress and coping among micro-entrepreneurs of peer-to-peer accommodation. International Journal of Hospitality Management, 97, Article ID 103009. https://doi.org/10.1016/j.ijhm.2021.103009
89) Yuan, B., Zhang, T., & Li, J. (2022). The dilemma of dual adaptation to delayed retirement initiative and work model change of gig economy: The influence of late retirement and multiple-job holding on mental health among older workers. International Archives of Occupational and Environmental Health, 95(5), 1067–1078. https://doi.org/10.1007/s00420-021-01792-8
