Preliminary Study on the Dynamics of Food Delivery Driver
DOI:
https://doi.org/10.34149/jebmes.v5i1.186Keywords:
Choices, decision making, food delivery application, gig economy, gig workerAbstract
While previous studies have explored the intersection of flexibility and algorithmic control in gig work, there is a notable gap in understanding how drivers strategically manage their idle time, balancing personal autonomy and platform constraints. Additionally, while research has primarily focused on ride-hailing drivers, the experiences of food delivery drivers remain underexplored though it has a unique work environment. This study explores how food delivery drivers in Jakarta manage their daily routines and idle time within the gig economy using a qualitative approach combining non-participatory observations and interviews. The research reveals how drivers navigate idle periods and develop scheduling strategies while working through food delivery apps, shedding light on their time use and work dynamics in this unique context. The findings show that there is a complex interconnection between time, space, and activity, of drivers’ idle time behavior. Furthermore, the research challenges the idea of complete freedom and flexibility in gig work as the scheduling system, designed to reduce idle time, limits drivers’ freedom and flexibility. The result of this study could help platform operators refining their algorithms and support systems to better align driver autonomy with platform objectives, which could improve driver productivity, wellbeing, and satisfaction.
References
Arora, S., Choudhary, V., Hasija, S., Gorban, I., Turki, S., & Shekhani, A. (2024). Unravelling the implications of effort allocation in gig economy: A study of driver relocation in food delivery. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4679321
Ashkrof, P., Homem de Almeida Correia, G., Cats, O., & van Arem, B. (2022). Ride acceptance behaviour of ride-sourcing drivers. Transportation Research Part C: Emerging Technologies, 142, 103783. https://doi.org/10.1016/j.trc.2022.103783
Berger, T., Frey, C. B., Levin, G., & Danda, S. R. (2019). Uber happy? Work and well-being in the ‘Gig Economy.’ Economic Policy, 34(99), 429–477. https://doi.org/10.1093/epolic/eiz007
Bon, A. T., & Shire, A. M. (2022). Review of conservation of resources theory in job demands and resources model. International Journal of Global Optimization and Its Application, 1(4), 236–248. https://doi.org/10.56225/ijgoia.v1i4.102
Chen, A. H. L., Lee, J. Z.-H., & Ho, Y.-L. (2025). Influential factors for online food delivery platform drivers’ order acceptance. Information Discovery and Delivery. https://doi.org/10.1108/IDD-03-2024-0038
Creswell, J. W. (2007). Qualitative inquiry & research design: Choosing among five approaches (2nd ed). Sage Publications.
Du Toit, D., & Phumzile, N. (2024). Beyond digital flexibility: Standing’s labor securities framework and the precarious lives of migrant food delivery couriers in johannesburg. Clinical Sociology Review, 19(2), 106–133. https://doi.org/10.36615/hyf6ea64
Jain, G., & Sethi, A. (2024). Breadwinners on wheels: Delving into the world of food delivery partners in raipur city. Journal of Ravishankar University (PART-A), 31(1), 15–25. https://doi.org/10.52228/JRUA.2025-31-1-3
Keith, M. G., Harms, P., & Tay, L. (2019). Mechanical Turk and the gig economy: Exploring differences between gig workers. Journal of Managerial Psychology, 34(4), 286–306. https://doi.org/10.1108/JMP-06-2018-0228
Lee, S. W. (2024). Fostering engagement in the gig economy: The impact of jd-r model. Pakistan Journal of Life and Social Sciences (PJLSS), 22(2). https://doi.org/10.57239/PJLSS-2024-22.2.001073
Li, S. (2023). The gig economy and labour market dynamics. Advances in Economics, Management and Political Sciences, 61(1), 275–281. https://doi.org/10.54254/2754-1169/61/20231285
Ma, Y., Chen, K., Xiao, Y., & Fan, R. (2022). Does online ride-hailing service improve the efficiency of taxi market? Evidence from shanghai. Sustainability, 14(14), 8872. https://doi.org/10.3390/su14148872
Ma, S., Bala, P., Nisi, V., Zimmerman, J., & Nunes, N. J. (2023). Uncovering gig worker-centered design opportunities in food delivery work. Proceedings of the 2023 ACM Designing Interactive Systems Conference, 688–701. https://doi.org/10.1145/3563657.3596123
Marquis, E. B., Kim, S., Alahmad, R., Pierce, C. S., & Robert Jr., L. P. (2018). Impacts of perceived behavior control and emotional labor on gig workers. Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing, 241–244. https://doi.org/10.1145/3272973.3274065
Mezmir, E. A. (2020). Qualitative data analysis: An overview of data reduction, data display and interpretation. Research on Humanities and Social Sciences, 10(21), 15–27. https://doi.org/10.7176/RHSS/10-21-02
Mohamed, S. and Mat, N. (2023). Gig work in post pandemic times: does it an agile work structure?. Journal of Entrepreneurship and Business, 11(2), 56-68. https://doi.org/10.17687/jeb.v11i2.1014
Penner, S., Griffith, J., Hughes, E., Karoli, K., & Stockdale, C. (2024). Precarious but possible: a qualitative study of the landscape of gig work for people living with disabilities and future recommendations for best practices. Journal of Occupational Rehabilitation, https://doi.org/10.21203/rs.3.rs-3998060/v1
Salleh, N. M., Shukry, S. N. M., & Jokinol, V. M. C. (2023). Analyzing the challenges, effects, and motivations of gig economy workers. International Journal of Academic Research in Business and Social Sciences, 13(6), Pages 2125-2142. https://doi.org/10.6007/IJARBSS/v13-i6/17514
Sigroha, A., & Kapoor, P. (2024). Algorithmic management in the food delivery gig economy: Mechanisms of control and worker autonomy. ShodhKosh: Journal of Visual and Performing Arts, 5(1). https://doi.org/10.29121/shodhkosh.v5.i1.2024.2878
Tara, N., & Iqbal, S. M. J. (2023). Examining the impact of job demands, resources and technostress on psychological wellbeing of gig workers: A theoretical model. Qlantic Journal of Social Sciences, 4(4), 369–378. https://doi.org/10.55737/qjss.750203843
Webster, N. and Zhang, Q. (2020). Careers delivered from the kitchen? immigrant women small-scale entrepreneurs working in the growing nordic platform economy. Nora - Nordic Journal of Feminist and Gender Research, 28(2), 113-125. https://doi.org/10.1080/08038740.2020.1714725
Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2018). 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 (Original work published 2019)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Journal of Emerging Business Management and Entrepreneurship Studies
This work is licensed under a Creative Commons Attribution 4.0 International License.
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities tacitly or explicitly of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
