Managed by the algorithm: platform discourse, entrepreneurial subjectivity, and precarity among Indonesian gig workers
DOI:
https://doi.org/10.67490/ijle.v1i2.905Keywords:
algorithmic management, entrepreneurial subjectivity, gig workers, precarityAbstract
Background: Algorithmic management has expanded across Indonesia’s gig economy, where platform narratives of flexibility, partnership, and opportunity coexist with informal employment, unstable protection, and digitally mediated control. Objective: This study examines how official platform discourse constructs entrepreneurial subjectivity and organises precarity among Indonesian gig workers. Method: A qualitative critical discourse design was applied to twenty-one public documents comprising platform terms, recruitment pages, driver communications, corporate releases, verified reporting, scholarly materials, and policy documents, analysed through discourse framing, subject-positioning, and precarity-and-control matrices. Results: Findings show that welfare, flexibility, and recognition legitimise platform participation by presenting conditional benefits and operational choice as evidence of partnership. Workers are simultaneously positioned as autonomous, calculative, self-investing, resilient, and responsible for converting platform opportunities into sustainable livelihoods. Implication: However, tariff setting, performance metrics, benefit eligibility, account governance, risk transfer, information asymmetry, and protection gaps delimit this autonomy and distribute uncertainty disproportionately towards workers. Novelty: This study contributes a relational account of platform labour by conceptualising conditional entrepreneurial autonomy as a discursive and institutional arrangement through which limited operational discretion coexists with concentrated infrastructural authority, thereby integrating language, subject formation, and algorithmic governance within one analytical framework in a Global South setting often examined mainly through employment relations, technical systems, or workers’ experiences.
References
[1] M. H. Jarrahi, G. Newlands, M. K. Lee, C. T. Wolf, E. Kinder, and W. Sutherland, “Algorithmic management in a work context,” Big Data & Society, vol. 8, no. 2, 2021, doi: 10.1177/20539517211020332.
[2] A. Benlian, M. Wiener, W. Cram, H. Krasnova, A. Maedche, M. Möhlmann, J. Recker, and U. Remus, “Algorithmic management,” Business & Information Systems Engineering, vol. 64, pp. 825–839, 2022, doi: 10.1007/s12599-022-00764-w.
[3] J. Duggan, R. Carbery, A. McDonnell, and U. Sherman, “Algorithmic HRM control in the gig economy: The app-worker perspective,” Human Resource Management, 2023, doi: 10.1002/hrm.22168.
[4] N. K. Chan, “Algorithmic precarity and metric power: Managing the affective measures and customers in the gig economy,” Big Data & Society, vol. 9, no. 2, 2022, doi: 10.1177/20539517221133779.
[5] J. Muldoon and P. Raekstad, “Algorithmic domination in the gig economy,” European Journal of Political Theory, vol. 22, no. 4, pp. 587–607, 2022, doi: 10.1177/14748851221082078.
[6] L. D. Cameron, “The making of the “good bad” job: How algorithmic management manufactures consent through constant and confined choices,” Administrative Science Quarterly, vol. 69, no. 2, pp. 458–514, 2024, doi: 10.1177/00018392241236163.
[7] A. Novianto, “Gamification from below as a form of resistance: Algorithmic control, precarity, and resistance dynamics among Indonesian gig workers,” New Technology, Work and Employment, vol. 40, 2024, doi: 10.1111/ntwe.12324.
[8] R. Dorschel, “A new middle-class fraction with a distinct subjectivity: Tech workers and the transformation of the entrepreneurial self,” The Sociological Review, vol. 70, no. 6, pp. 1302–1320, 2022, doi: 10.1177/00258172221103015.
[9] O. Maury, “The fragmented labor power composition of gig workers: Entrepreneurial tendency and the heterogeneous production of difference,” Critical Sociology, vol. 50, no. 7–8, pp. 1167–1182, 2023, doi: 10.1177/08969205231216418.
[10] D. W. P. Yasih, “Normalizing and resisting the new precarity: A case study of the Indonesian gig economy,” Critical Sociology, vol. 49, no. 6, pp. 847–863, 2022, doi: 10.1177/08969205221087130.
[11] J. Meijerink and T. V. Bondarouk, “The duality of algorithmic management: Toward a research agenda on HRM algorithms, autonomy and value creation,” Human Resource Management Review, 2021, doi: 10.1016/j.hrmr.2021.100876.
[12] R. Qadri and C. D’Ignazio, “Seeing like a driver: How workers repair, resist, and reinforce the platform’s algorithmic visions,” Big Data & Society, vol. 9, no. 2, 2022, doi: 10.1177/20539517221133780.
[13] Kadolkar, S. Kepes, and M. Subramony, “Algorithmic management in the gig economy: A systematic review and research integration,” Journal of Organizational Behavior, 2024, doi: 10.1002/job.2831.
[14] M. Dedema and H. S. Rosenbaum, “Socio-technical issues in the platform-mediated gig economy: A systematic literature review,” Journal of the Association for Information Science and Technology, vol. 75, no. 4, pp. 344–374, 2024, doi: 10.1002/asi.24868.
[15] D. R. Öborn, R. MacKenzie, H. Örnebring, and E. Van Couvering, “Bypassing the limitations of algorithmic management via out-of-app activities and the emergence of opportunistic agency in the Swedish gig economy,” New Technology, Work and Employment, vol. 40, 2024, doi: 10.1111/ntwe.12323.
[16] M. P. Crayne and A. B. Newlin, “Driven to succeed, or to leave? The variable impact of self-leadership in rideshare gig work,” The International Journal of Human Resource Management, vol. 35, no. 1, pp. 98–120, 2023, doi: 10.1080/09585192.2023.2211712.
[17] A. Alacovska, E. Bucher, and C. Fieseler, “A relational work perspective on the gig economy: Doing creative work on digital labour platforms,” Work, Employment and Society, vol. 38, no. 1, pp. 161–179, 2022, doi: 10.1177/09500170221103146.
[18] Alacovska, E. Bucher, and C. Fieseler, “Algorithmic paranoia: Gig workers’ affective experience of abusive algorithmic management,” New Technology, Work and Employment, vol. 40, 2024, doi: 10.1111/ntwe.12317.
[19] A. Anwar, P. Garcia, and J. Hui, “Entangled independence: From labor rights to gig “empowerment” under the algorithmic gaze,” Proceedings of the ACM on Human-Computer Interaction, vol. 8, pp. 1–26, 2024, doi: 10.1145/3686916.
[20] Huang and H.-C., “Riders on the storm: Amplified platform precarity and the impact of COVID-19 on online food-delivery drivers in China,” Journal of Contemporary China, vol. 31, no. 135, pp. 351–365, 2021, doi: 10.1080/10670564.2021.1966895.
[21] Gerber, “Gender and precarity in platform work: Old inequalities in the new world of work,” New Technology, Work and Employment, 2022, doi: 10.1111/ntwe.12233.
[22] Popan, “Embodied precariat and digital control in the “gig economy”: The mobile labor of food-delivery workers,” Journal of Urban Technology, vol. 31, no. 1, pp. 109–128, 2021, doi: 10.1080/10630732.2021.2001714.
[23] P. Sun, J. Y. Chen, and U. Rani, “From flexible labour to “sticky labour”: A tracking study of workers in the food-delivery platform economy of China,” Work, Employment and Society, vol. 37, no. 2, pp. 412–431, 2021, doi: 10.1177/09500170211021570.
[24] R. Grohmann, G. Pereira, A. Guerra, L. Abílio, B. Moreschi, and A. Jurno, “Platform scams: Brazilian workers’ experiences of dishonest and uncertain algorithmic management,” New Media & Society, vol. 24, no. 7, pp. 1611–1631, 2021, doi: 10.1177/14614448221099225.
[25] T. Vieira, “Platform couriers’ self-exploitation: The case study of Glovo,” New Technology, Work and Employment, 2023, doi: 10.1111/ntwe.12272.
[26] Ķešāne and M. Spuriņa, “Sociological types of precarity among gig workers: Lived experiences of food-delivery workers in Riga,” Social Inclusion, 2024, doi: 10.17645/si.7696.
[27] L. Cini, “Resisting algorithmic control: Understanding the rise and variety of platform worker mobilisations,” New Technology, Work and Employment, 2022, doi: 10.1111/ntwe.12257.
[28] R. Duggan, U. Sherman, R. Carbery, and A. McDonnell, “Boundaryless careers and algorithmic constraints in the gig economy,” The International Journal of Human Resource Management, vol. 33, no. 22, pp. 4468–4498, 2021, doi: 10.1080/09585192.2021.1953565.
[29] M. Walker, P. Fleming, and M. Berti, ““You can’t pick up a phone and talk to someone”: How algorithms function as biopower in the gig economy,” Organization, vol. 28, no. 1, pp. 26–43, 2021, doi: 10.1177/1350508420978831.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Abdul Wahid (Author)

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








Creative Commons Attribution 4.0 International License