Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
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An Empirical Study on Job Embracing by Mobile Platform Workers

  • Received : 2023.08.28
  • Accepted : 2024.01.24
  • Published : 2024.06.30
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Abstract

Despite the maturity of platforms, only some studies have explored the relationships between the working conditions of platform workers and their organization-like responses to these platforms. Thus, this research utilized the Job Demands-Resources Model (JD-R Model) to analyze the effects of job demands and resources on platform workers' job embracing. The data were collected from 182 food delivery riders in South Korea. This study utilized the PLS technique (partial least squares) to examine the research model. Regarding job demands, this study has found that work overload and physical effort significantly affect burnout. Regarding job resources, the results revealed that service technology support and training significantly affect work engagement. In alignment with the Job Demands-Resources literature, the findings offer tangible proof that burnout has a detrimental impact on job embracing, whereas work engagement has a beneficial effect on job embracing. Our findings indicate that work engagement exerts a more substantial beneficial effect on job embracing, and burnout reduces job embracing. Results also provide novel insights to scholars seeking a comprehensive research model on the impact of on-demand workplace conditions to help platforms attract and retain platform workers.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2021S1A5A2A03064273).

References

  1. Ahuja, M. K., Chudoba, K. M., Kacmar, C. J., Mcknight, D. H., and George, J. F. (2007). IT road warriors: Balancing work-family conflict, job autonomy, and work overload to mitigate turnover intentions. MIS Quarterly, 31(1), 1-17. https://doi.org/10.2307/25148778 
  2. Allen, D. G., Shore, L. M., and Griffeth, R. W. (2003). The role of perceived organizational support and supportive human resource practices in the turnover process. Journal of Management, 29(1), 99-118. https://doi.org/10.1016/S0149-2063(02)00222-2 
  3. Alstyne, M. W. V., Parker, G. G., and Choudary, S. P. (2016). Pipelines, platforms, and the new rules of strategy. Harvard Business Review, 94(4), 54-62. 
  4. Armstrong, D. J., Brooks, N. G., and Riemenschneider, C. K. (2015). Exhaustion from information system career experience: Implications for turn-away intention. MIS Quarterly, 39(3), 713-727.  https://doi.org/10.25300/MISQ/2015/39.3.10
  5. Babakus, E., Yavas, U., and Ashill, N. J. (2009). The role of customer orientation as a moderator of the job demand-burnout-performance relationship: A surface-level trait perspective. Journal of Retailing, 85(4), 480-492. https://doi.org/10.1016/j.jretai.2009.07.001 
  6. Bakker, A. B., and Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22(3), 309-328. https://doi.org/10.1108/02683940710733115 
  7. Bakker, A. B., Demerouti, E., and Verbeke, W. (2004). Using the job demands-resources model to predict burnout and performance. Human Resource Management, 43(1), 83-104. https://doi.org/10.1002/hrm.20004 
  8. Bakker, A. B., Demerouti, E., De Boer, E., and Schaufeli, W. B. (2003). Job demands and job resources as predictors of absence duration and frequency. Journal of Vocational Behavior, 62(2), 341-356. https://doi.org/10.1016/S0001-8791(02)00030-1 
  9. Bakker, A. B., Emmerik, H. V., and Euwema, M. C. (2006). Crossover of burnout and engagement in work teams. Work and Occupations, 33(4), 464-489. https://doi.org/10.1177/0730888406291310 
  10. Boyd, C. M., Bakker, A. B., Pignata, S., Winefield, A. H., Gillespie, N., and Stough, C. (2011). A longitudinal test of the job demands-resources model among Australian university academics. Applied Psychology: An International Review, 60(1), 112-140. https://doi.org/10.1111/j.1464-0597.2010.00429.x 
  11. Chan, J. (2021). Hunger for profit: How food delivery platforms manage couriers in China. Sociologias, 23, 58-82. https://doi.org/10.1590/15174522-112308 
  12. Chen, C. F. (2023). Investigating the effects of job stress on the distraction and risky driving behaviors of food delivery motorcycle riders. Safety and Health at Work, 14(2), 207-214. https://doi.org/10.1016/j.shaw.2023.03.004 
  13. Chin, W. W., Marcolin, B. L., and Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217. https://doi.org/10.1287/isre.14.2.189.16018 
  14. Chu, F., Guo, M., Liu, S., and Chen, S. (2020). Work-family conflict, personality, and safety behaviors among high-speed railway drivers. Journal of Transportation Safety & Security, 12(9), 1147-1163. https://doi.org/10.1080/19439962.2019.1579289 
  15. Cini, L. (2022). Resisting algorithmic control: Understanding the rise and variety of platform worker mobilisations. New Technology, Work and Employment, 38(1), 125-144. https://doi.org/10.1111/ntwe.12257. 
  16. Crawford, E. R., Lepine, J. A., and Rich, B. L. (2010). Linking job demands and resources to employee engagement and burnout: A theoretical extension and meta-analytic test. Journal of Applied Psychology, 95(5), 834-848. https://doi.org/10.1037/a0019364 
  17. De Croon, E. M., Sluiter, J. K., Blonk, R. W. B., Broersen, J. P. J., and Frings-Dresen, M. H. W. (2004). Stressful work, psychological job strain, and turnover: A 2-year prospective cohort study of truck drivers. Journal of Applied Psychology, 89(3), 442-454. https://doi.org/10.1037/0021-9010.89.3.442 
  18. Demerouti, E., Bakker, A. B., Nachreiner, F., and Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499-512.  https://doi.org/10.1037/0021-9010.86.3.499
  19. Diamantopoulos, A., and Siguaw, J. A., (2006). Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. British Journal of Management, 17(4), 2006, 263-282. https://doi.org/10.1111/j.1467-8551.2006.00500.x 
  20. Dunn, M. (2020). Making gigs work: Digital platforms, job quality and worker motivations. New Technology, Work & Employment, 35(2), 232-249. https://doi.org/10.1111/ntwe.12167 
  21. Ecker, Y., and Struver, A. (2022). Towards alternative platform futures in post-pandemic cities? A case study on platformization and changing socio-spatial relations in on-demand food delivery. Digital Geography and Society, 3, 100032. https://doi.org/10.1016/j.diggeo.2022.100032 
  22. Fornell, C., and Larcker, D. (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 
  23. Gawer, A. (2014). Bridging differing perspectives on technological platforms: Toward an integrative framework. Research Policy, 43(7), 1239-1249. https://doi.org/10.1016/j.respol.2014.03.006 
  24. Gefen, D., and Straub, D. W. (2005). A practical guide to factorial validity using pls-graph: Tutorial and annotated example. Communications of the AIS, 16(5), 19-109. https://doi.org/10.17705/1CAIS.01605 
  25. Hagiu, A., and Wright, J. (2015). Multi-sided platforms. International Journal of Industrial Organization, 43, 162-174. http://dx.doi.org/10.2139/ssrn.2794582 
  26. Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998). Multivariate data Analysis, NJ, Prentice Hall. 
  27. Hair, J. F., Ringle, C. M., and Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory & Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202 
  28. Henseler, J., Ringle, C. M., and 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 
  29. Jin, L., Kominers, S. D., and Shroff, L. (2021). A labor movement for the platform economy, Harvard Business Review Digital Articles, Retrieved from https://www.hbs.edu/faculty/Pages/item.aspx?num=61274 
  30. Kang, Y., and Kim, J. (2023). Five trends that will define South Korean grocery in 2023, McKinsey & Company Article, Retrieved from https://www.mckinsey.com/industries/retail/our-insights/five-trends-that-will-define-south-korean-grocery-in-2023#/ 
  31. Karanovic, J., Berends, H., and Engel, Y. (2021). Regulated dependence: Platform workers' responses to new forms of organizing. Journal of Management Studies, 58(4), 1070-1106. https://doi.org/10.1111/joms.12577 
  32. Kim, J. (2023). Platform Workers in South Korea. Korea Employment Information Service Employment Trend Brief, 1, 1-35. 
  33. Kock, N. (2015). Common method bias in pls-sem: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101 
  34. Kougiannou, N. K., and Mendonca, P. (2021). Breaking the managerial silencing of worker voice in platform capitalism: The rise of a food courier network. British Journal of Management, 32(3), 744-759. https://doi.org/10.1111/1467-8551.12505 
  35. Kuhn, K. M., and Maleki, A. (2017). Micro-entrepreneurs, dependent contractors, and instaserfs: Understanding online labor platform workforces. Academy of Management Perspectives, 31(3), 183-200. https://doi.org/10.5465/amp.2015.0111 
  36. Leighton, P., and Wynn, M. (2011). Classifying employment relationships-more sliding doors or a better regulatory framework?. Industrial Law Journal, 40(1), 5-44. https://doi.org/10.1093/indlaw/dwq029 
  37. Li, X., Tan, A. J. H., Wang, X., and Yuen, K. F. (2023). Investigating gig workers' commitment to crowdsourced logistics platforms: Fair employment and social exchange perspectives. Technology in Society, 74, 102311. https://doi.org/10.1016/j.techsoc.2023.102311 
  38. Mohlmannn, M., Alves De Lima Salge, C., and Marabelli, M. (2023). Algorithm sensemaking: How platform workers make sense of algorithmic management. Journal of the Association for Information Systems, 24(1), 35-64. https://doi.org/10.17705/1jais.00774 
  39. Mohlmannn, M., Zalmanson, L., Henfridsson, O., and 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
  40. Nahrgang, J. D., Morgeson, F. P., and Hofmann, D. A. (2011). Safety at work: A meta-analytic investigation of the link between job demands, job resources, burnout, engagement, and safety outcomes. Journal of Applied Psychology, 96(1), 71-94. https://doi.org/10.1037/a0021484 
  41. Nielsen, M. L., Laursen, C. S., and Dyreborg, J. (2022). Who takes care of safety and health among young workers? Responsibilization of OSH in the platform economy. Safety Science, 149, 105674. https://doi.org/10.1016/j.ssci.2022.105674 
  42. Nwafor, O., Ma, X., Hou, J., and Johnson, N. (2022). Online communities and discontinuance of information technology-enabled on-demand workers: Impacts of informal social interactions through dual commitments. International Journal of Information Management, 66, 102540. https://doi.org/10.1016/j.ijinfomgt.2022.102540 
  43. Park, S., and Ryoo, S. (2023). How Does Algorithm Control Affect Platform Workers' Responses? Algorithm as a Digital Taylorism. Journal of Theoretical and Applied Electronic Commerce Research, 18(1), 273-288. https://doi.org/10.3390/jtaer18010015 
  44. Parwez, S. (2022). Covid-19 pandemic and work precarity at digital food platforms: A delivery worker's perspective. Social Sciences & Humanities Open, 5(1), 100259. https://doi.org/10.1016/j.ssaho.2022.100259 
  45. Quy Nguyen-Phuoc, D., An Ngoc Nguyen, N., Nguyen, M. H., Ngoc Thi Nguyen, L., and Oviedo-Trespalacios, O. (2022). Factors influencing road safety compliance among food delivery riders: An extension of the Job Demands-Resources (JD-R) model. Transportation Research Part A: Policy and Practice, 166, 541-556. https://doi.org/10.1016/j.tra.2022.11.002 
  46. Quy Nguyen-Phuoc, D., Ngoc Thi Nguyen, L., Ngoc Su, D., Nguyen, M. H., and OviedoTrespalacios, O. (2023). Deadly meals: The influence of personal and job factors on burnout and risky riding behaviours of food delivery motorcyclists. Safety Science, 159, 106007. https://doi.org/10.1016/j.ssci.2022.106007 
  47. Rha, J.-Y., Nam, Y., Yoon, J., and Lee, B. (2023). Korean consumers' use and concerns about food delivery service. Nutrition Research and Practice, 17(3), 583-596. https://doi.org/10.4162/nrp.2023.17.3.583 
  48. Ringle, C. M., Sarstedt, M., and Straub, D. W. (2012). A critical look at the use of pls-sem in mis quarterly. MIS Quarterly, 36(1), iii-xiv. 
  49. Schaufeli, W. B. (2017). Applying the job demands-resources model: A 'how to' guide to measuring and tackling work engagement and burnout. Organizational Dynamics, 46(2), 120-132. https://doi.org/10.1016/j.orgdyn.2017.04.008
  50. Schaufeli, W. B., and Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25(3), 293-315. https://doi.org/10.1002/job.248 
  51. Schaufeli, W. B., Bakker, A. B., and Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66(4), 701-716. https://doi.org/10.1177/0013164405282471 
  52. Sendawula, K., Nakyejwe Kimuli, S., Bananuka, J., and Najjemba Muganga, G. (2018). Training, employee engagement, and employee performance: Evidence from Uganda's health sector. Cogent Business & Management, 5(1), 1470891. https://doi.org/10.1080/23311975.2018.1470891 
  53. Ting, L., and Ahn, J. (2022). Role of mobile application attributes in building job meaningfulness among food delivery employees. Journal of Hospitality and Tourism Management, 52, 161-167. https://doi.org/10.1016/j.jhtm.2022.06.010 
  54. Tran, N. a. T., Nguyen, H. L. A., Nguyen, T. B. H., Nguyen, Q. H., Huynh, T. N. L., Pojani, D., Nguyen Thi, B., and Nguyen, M. H. (2022). Health and safety risks faced by delivery riders during the COVID-19 pandemic. Journal of Transport & Health, 25, 101343. https://doi.org/10.1016/j.jth.2022.101343 
  55. Wang, C., Chen, J., and Xie, P. (2022). Observation or interaction? Impact mechanisms of gig platform monitoring on gig workers' cognitive work engagement. International Journal of Information Management, 67, 102548. https://doi.org/10.1016/j.ijinfomgt.2022.102548 
  56. Wang, X.C., Kim, W., Holguin-Veras, J., and Schmid, J. (2021). Adoption of delivery services in light of the COVID pandemic: who and how long?. Transportation Research Part A-Policy Practice, 154, 270-286. https://doi.org/10.1016/j.tra.2021.10.012 
  57. Won, J., Lee, D., and Lee, J. (2023). Understanding experiences of food-delivery-platform workers under algorithmic management using topic modeling. Technological Forecasting and Social Change, 190, 122369. https://doi.org/10.1016/j.techfore.2023.122369 
  58. Woon, L.S., Sze, C.C., Ying, C.Y., and Yusof, A. (2022). Impact of JD-R Model on Psychological Well-Being of Gig Workers, In Proceedings of the 3rd Annual Conference of Education and Social Sciences (ACCESS 2021), (pp. 12-20). https://doi.org/10.2991/978-2-494069-21-3_3. 
  59. Xanthopoulou, D., Bakker, A. B., Demerouti, E., and Schaufeli, W. B. (2007). The role of personal resources in the job demands-resources model. International Journal of Stress Management, 14(2), 121-141. https://doi.org/10.1037/1072-5245.14.2.121 
  60. Zhang, C., Chen, J., and Raghunathan, S. (2022a). Two-sided platform competition in a sharing economy. Management Science, 68(12), 8909-8932.  https://doi.org/10.1287/mnsc.2022.4302
  61. Zhang, C., Cheung, S.P., and Huang, C. (2022b). Job Demands and Resources, Mindfulness, and Burnout Among Delivery Drivers in China. Frontiers in Psychology, 13, 792254. https://doi.org/10.3389/fpsyg.2022.792254 
  62. Zhang, C., Sitar, S., and Huang, C. C. (2022c). Effects of job demands and resources on positive and negative affect of delivery drivers in China. International Journal of Environmental Research and Public Health, 19(13), 8140. https://doi.org/10.3390/ijerph19138140 
  63. Zheng, Y., Ma, Y., Guo, L., Cheng, J., and Zhang, Y. (2019). Crash involvement and risky riding behaviors among delivery riders in China: The role of working conditions. Transportation Research Record, 2673(4), 1011-1022. https://doi.org/10.1177/0361198119841028 
  64. Zhu, F., and Iansiti, M. (2019). Why some platforms thrive and others don't, Harvard Business Review, 97(1), 118-125.