Designing Optimal Policies for Indonesia’s Gig Economy through Agent-Based Modeling to Enhance Worker Welfare and Sustainable Growth
Keywords:
gig economy BPJS costs agent-based model price elasticity worker welfareAbstract
The growth of the gig economy in Indonesia has fostered a new form of employment relationship that is flexible yet highly vulnerable to social and economic uncertainties. A critical issue emerging within this context is the BPJS contribution policy, which potentially suppresses workers’ income and distorts the equilibrium of the digital labor market. This condition calls for an analytical framework capable of capturing the dynamic interactions among policy interventions, worker behavior, and market mechanisms. This study aims to analyze the impact of BPJS contribution costs on gig workers’ welfare, assess the role of price elasticity as a stabilizing factor, and design an optimal socio-economic policy that balances social protection with digital economic efficiency. The research employs an Agent-Based Modeling (ABM) approach involving three primary agent types: gig workers, digital platforms, and regulators. Simulations are conducted across 27 scenarios that vary BPJS contribution rates, income preferences, and price elasticity. Sensitivity analysis using Ordinary Least Squares (OLS) identifies the influence of each parameter on workers’ average income. The simulation results reveal that an increase in BPJS contributions reduces worker income by approximately 0.9 units for every one-unit rise in fees, while price elasticity acts as a stabilizing mechanism maintaining market balance. A proportional contribution policy with flexible rates proves more effective than a fixed-rate scheme. The study concludes that the optimal policy for Indonesia’s gig sector is a hybrid policy mix integrating proportional subsidies, flexible tariffs, and fiscal incentives for platforms, ensuring both worker welfare and systemic digital economic sustainability.
References
Alauddin, F. D. A., Aman, A., Ghazali, M. F., & Daud, S. (2024). The influence of digital platforms on workers: A systematic literature review. Heliyon, 11. https://doi.org/10.1016/j.heliyon. 2024.e41491
Anwar, M. A., Schäfer, S., & Golušin, S. (2023). Work futures: globalization, planetary markets, and uneven developments in the gig economy. Globalizations, 21, 571–589. https://doi.org/10.1080/14747731.2023.2236876
Arif, Novianto, Anindya, Dessi, & Wulansari. (2024). Kemitraan Semu dalam Ekonomi Gig di Indonesia : Analisis Terhadap Kondisi Pekerja Berstatus Mitra. January.
Asfahani, A., Alsobahi, G., & Dahlan, D. A. (2023). Navigating the Saudi Gig Economy: The Role of Human Resource Practices in Enhancing Job Satisfaction and Career Sustainability. Sustainability. https://doi.org/10.3390/su152316406
Axtell, R., & Farmer, J. (2025). Agent-Based Modeling in Economics and Finance: Past, Present, and Future. Journal of Economic Literature. https://doi.org/10.1257/jel.20221319
Ayu, R. (2024). Role of Gig Economy Participation in Shaping Worker Economic Security in Indonesia. International Journal of Sociology. https://doi.org/10.47604/ijs.2830
Bertani, F., Ponta, L., Raberto, M., Teglio, A., & Cincotti, S. (2020). The complexity of the intangible digital economy: an agent-based model. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2020.03.041
Bucos, T. (2023). The GIG Economy – Result of the Labour Market Platformization. Economica. https://doi.org/10.53486/econ.2023.124.025
Chen, B., Liu, T., & Wang, Y. (2020). Volatile Fragility: New Employment Forms and Disrupted Employment Protection in the New Economy. International Journal of Environmental Research and Public Health, 17. https://doi.org/10.3390/ijerph17051531
Choudary, S. P. (2022). Labor Market in the Digital Economy – Prospects for Regulation. World Economy and International Relations. https://doi.org/10.20542/0131-2227-2022-66-10-102-111
Douven, I. (2024). Social Learning in Neural Agent-Based Models. Philosophy of Science, 92, 141–161. https://doi.org/10.1017/psa.2024.33
Gill, A., Lalith, M., Poledna, S., Hori, M., Fujita, K., & Ichimura, T. (2021). High-Performance Computing Implementations of Agent-Based Economic Models for Realizing 1:1 Scale Simulations of Large Economies. IEEE Transactions on Parallel and Distributed Systems, 32, 2101–2114. https://doi.org/10.1109/tpds.2021.3060462
Guo, J.-C., Tang, Q., & Jin, G. (2021). Labor protection and the efficiency of human capital investment. Economic Analysis and Policy, 69, 195–207. https://doi.org/10.1016/j.eap.2020.12.006
Hickson, J. (2023). Freedom, domination and the gig economy. New Political Economy, 29, 321–336. https://doi.org/10.1080/13563467.2023.2254712
Indonesiana.id. (2025). Superposisi Pekerja Gig: Terjebak antara Status “Mitra” dan Realitas “Buruh.” Indonesiana.Id. https://www.indonesiana.id/read/187293/superposisi-pekerja-gig-terjebak-antara-status-mitra-dan-realitas-buruh
Jin, D., & Liu-Lastres, B. (2024). Critical reflection on the impact of the gig economy on the hospitality workforce. International Journal of Contemporary Hospitality Management.
https://doi.org/10.1108/ijchm-08-2023-1297
Jung, J., Miller, J., & Page, S. (2025). Agent-based modeling for psychological research on social phenomena. The American Psychologist. https://doi.org/10.1037/amp0001530
Koutsimpogiorgos, N., Slageren, J., Herrmann, A., & Frenken, K. (2020). Conceptualizing the Gig Economy and Its Regulatory Problems. Policy & Internet. https://doi.org/10.31235/osf.io/jmqyt
Kvart, S., Cuervo, I., Gunn, V., Lewchuk, W., Bosmans, K., Davis, L., Escrig-Piñol, A., Östergren, P., Padrosa, E., Vives, A., Zaupa, A., Ahonen, E., Álvarez-López, V., Bolíbar, M., Díaz, I., Gutiérrez-Zamora, M., Ivarsson, L., Juliá, M., Muntaner, C., … Baron, S. (2025). Labour and social protection gaps impacting the health and well-being of workers in non-standard employment: An international comparative study. PLOS One, 20. https://doi.org/10.1371/journal.pone.0320248
Lata, L., Burdon, J., & Reddel, T. (2022). New tech, old exploitation: Gig economy, algorithmic control and migrant labour. Sociology Compass. https://doi.org/10.1111/soc4.13028
Malik, R., Visvizi, A., & Skrzek-Lubasinska, M. (2021). The Gig Economy: Current Issues, the Debate, and the New Avenues of Research. Sustainability, 13, 5023. https://doi.org/10.3390/su13095023
Mehta, B. (2020). Changing Nature of Work and the Gig Economy: Theory and Debate. FIIB Business Review, 12, 227–237. https://doi.org/10.1177/2319714520968294
Meijerink, J., & Keegan, A. (2019). Conceptualizing human resource management in the gig economy. Journal of Managerial Psychology. https://doi.org/10.1108/JMP-07-2018-0277
Montgomery, T., & Baglioni, S. (2020). Defining the gig economy: platform capitalism and the reinvention of precarious work. International Journal of Sociology and Social Policy.
https://doi.org/10.1108/ijssp-08-2020-0400
Muldoon, J., & Sun, P. (2024). The Global Gig Economy: How Transport Platform Companies Adapt to Regulatory Challenges—A Comparative Analysis of Six Countries. Industrial Law Journal.
https://doi.org/10.1093/indlaw/dwae010
Ostoj, I. (2021). The Logic of Gig Economy (Origins and Growth Prospects). Studies in Logic, Grammar and Rhetoric, 66, 451–462. https://doi.org/10.2478/slgr-2021-0025
Raimi, L. (2025). Contributions of the shadow economy and gig economy to entrepreneurship and business development in emerging economies: a systematic review. International Journal of
Sociology and Social Policy. https://doi.org/10.1108/ijssp-12-2024-0638
Reissl, S. (2022). Fiscal multipliers, expectations and learning in a macroeconomic agent-based model. Economic Inquiry. https://doi.org/10.1111/ecin.13084
Silva, B., & Moreira, A. (2022). Entrepreneurship and the gig economy: A bibliometric analysis. Cuadernos de Gestión. https://doi.org/10.5295/cdg.211580am
Srihita, R. H., Goli, G., M, R., & Gobinath, R. (2025). “Transformative dynamics of the gig economy: Technological impacts, worker well-being and global research trends.” International Journal of Engineering Business Management. https://doi.org/10.1177/18479790241310362
Tan, Z. M., Aggarwal, N., Cowls, J., Morley, J., Taddeo, M., & Floridi, L. (2020). The Ethical Debate about the Gig Economy: A Review and Critical Analysis. Information Policy & Ethics EJournal. https://doi.org/10.2139/ssrn.3669216
Tieleman, S. (2021). Towards a Validation Methodology for Macroeconomic Agent-Based Models. Computational Economics, 60, 1507–1527. https://doi.org/10.1007/s10614-021-10191-w
Van Doorn, N., Ferrari, F., & Graham, M. (2020). Migration and Migrant Labour in the Gig Economy: An Intervention. Work, Employment & Society, 37, 1099–1111. https://doi.org/10.1177/09500170221096581
Vu, A. N., & Nguyen, D. L. (2024). The gig economy: The precariat in a climate precarious world. World Development Perspectives, 34, 100596. https://doi.org/https://doi.org/10.1016/j.wdp.2024.100596
Webster, N. A., & Zhang, Q. (2025). Strategic silences for normative work: Inclusions and exclusions of migrant labour in policy foregrounding of the Swedish gig economy. Geoforum, 158, 104157. https://doi.org/https://doi.org/10.1016/j.geoforum.2024.104157
White, D. (2023). Adaptive functions in an agent-based model of an economic system. Adaptive Behavior, 31, 21–34. https://doi.org/10.1177/10597123221095644
Yasih, D. W. P. (2022). Normalizing and Resisting the New Precarity: A Case Study of the Indonesian Gig Economy. Critical Sociology, 49, 847–863. https://doi.org/10.1177/08969205221087130
Zehra, A., & Urooj, A. (2022). A Bibliometric Analysis of the Developments and Research Frontiers of Agent-Based Modelling in Economics. Economies. https://doi.org/10.3390/economies10070171
License
Copyright (c) 2025 Indonesia Forum on Labour and Productivity
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.