Mathematical and Statistical Analysis of Gig Work in the Platform Economy
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Mathematical and Statistical Analysis of Gig Work in the Platform Economy

Yiming Sun 1*
1 The Barstow School – Ningbo Campus
*Corresponding author: sun1m1ng@outlook.com
Published on 24 September 2025
Journal Cover
AEMPS Vol.218
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-385-7
ISBN (Online): 978-1-80590-386-4
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Abstract

This paper investigates the structure, challenges, and optimization strategies of gig employment in China’s rapidly expanding platform economy. As digital platforms like Meituan, Didi, and Ele.me continue to reshape labor relations, millions of workers engage in task-based, algorithm-mediated work arrangements without formal employment protections. Using a mixed-methods approach—combining statistical modeling, algorithmic system analysis, and empirical case studies—we identify three primary issues: high income volatility, opaque and biased algorithmic dispatch systems, and a widespread absence of social protections such as insurance, paid leave, or representation. To address these concerns, a set of integrated solutions is proposed, including transparent and auditable dispatch algorithms, fairness-aware machine learning frameworks, portable benefits schemes, and government-enforced minimum income standards. Analytical tools such as multivariate regression, Markov chain simulations, and fairness metrics (e.g., demographic parity) are employed to model and evaluate interventions. Ultimately, this study advocates for a multi-level, data-driven approach that combines mathematical optimization with regulatory reform to protect gig workers’ rights, enhance economic resilience, and promote the long-term sustainability of platform ecosystems.

Keywords:

Gig Economy, Algorithmic Management, Platform Labor, Income Volatility, Mathematical Modeling

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Sun,Y. (2025). Mathematical and Statistical Analysis of Gig Work in the Platform Economy. Advances in Economics, Management and Political Sciences,218,61-74.

References

[1]. China Internet Network Information Center. (2023) Statistical Report on Internet Development in China. Retrieved from https: //www.cnnic.com.cn/IDR/ReportDownloads/202311/P020231121355042476714.pdf

[2]. Sixth Tone. (2024) Meituan Report on Delivery Workforce Provokes Pushback. Retrieved from https: //www.sixthtone.com/news/1015908

[3]. China Daily. (2025) Didi sets up $278m special fund. Retrieved from https: //global.chinadaily.com.cn/a/202506/04/WS683fa0a7a310a04af22c30b0.html

[4]. Meituan Research Institute. (2023) 2022 Employment Report on Meituan Delivery Riders [Meituan Rider Employment Report 2022]. Retrieved from https: //about.meituan.com/news/update/nb20230322

[5]. EqualOcean. (2023) A Glimpse Into the Future – From Didi’s 1st Annual Report After Listing. Retrieved from https: //equalocean.com/analysis/2023072619966

[6]. TechNode. (2023) Alibaba’s Ele.me Enhances Welfare Benefits for 3 Million Delivery Workers. Retrieved from https: //technode.com/2023/07/17/alibabas-ele-me-enhances-welfare-benefits-for-3-million-delivery-workers/

[7]. China Labour Bulletin. (2022) Living on the Edge: A Report on the Working Conditions of China’s Delivery Workers. Retrieved from https: //clb.org.hk/content/living-edge-delivery-workers

[8]. Razak, S.S., Razali, N.N., and Tuan, L.Y. (2025) Factors influencing university students’ adoption of digital labour platforms. Environment-Behaviour Proceedings Journal, 10, 195. Retrieved from https: //ebpj.e-iph.co.uk/index.php/EBProceedings/article/view/6514

[9]. Piot-Lepetit, I. (2025) Strategies of digitalization and sustainability in agrifood value chains. Frontiers in Sustainable Food Systems, 9, 1565662. Retrieved from https: //www.frontiersin.org/articles/10.3389/fsufs.2025.1565662/full

[10]. George, A. (2024) Gig economy 2.0: Examining how smart technologies could revolutionize on-demand work. Partners University Innovation Research Publications, 2, 45. Retrieved from https: //www.puirp.com/index.php/research/article/view/66

[11]. Dubal, V. (2023) On algorithmic wage discrimination. Columbia Law Review, 123, 1497. Retrieved from https: //www.jstor.org/stable/27264954

[12]. Zhao, H., Yuan, B., Gong, Y., and Liao, Y. (2025) Platform algorithmic control and work outcomes of food delivery employees. The Service Industries Journal, 45, 267. Retrieved from https: //doi.org/10.1080/02642069.2025.2477454

[13]. Xiang, Y., Du, J., Zheng, X., Long, L.R., and Xie, H.Y. (2024) Judging in the dark: How delivery riders form fairness perceptions under algorithmic management. Journal of Business Ethics, 187, 455. Retrieved from https: //doi.org/10.1007/s10551-024-05883-w

[14]. Muller, Z. (2020) Algorithmic harms to workers in the platform economy: The case of Uber. Columbia Journal of Law and Social Problems, 53, 265. Retrieved from https: //jlsp.law.columbia.edu/

[15]. Binns, R., Stein, J., Datta, S., and Van Kleek, M. (2025) Not even nice work if you can get it: A longitudinal study of Uber’s algorithmic pay and pricing. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, 2025, 1. Retrieved from https: //dl.acm.org/doi/10.1145/3715275.3732099

[16]. Muldoon, J., and Raekstad, P. (2023) Algorithmic domination in the gig economy. European Journal of Political Theory, 22, 210. Retrieved from https: //doi.org/10.1177/14748851221082078

[17]. Cameron, L. (2020) The rise of algorithmic work: Implications for organizational control and worker autonomy. University of Michigan Working Paper. Retrieved from https: //deepblue.lib.umich.edu/handle/2027.42/155277

[18]. Lian, Z., Tian, F., and Zhang, F. (2025) Transparency, control, and pay in the gig economy: A game-theoretic perspective. SSRN Electronic Journal. Retrieved from https: //papers.ssrn.com/sol3/papers.cfm?abstract_id=5174697

[19]. Xie, Z. (2022) Labour protection of platform workers in China: Legal innovations and emerging trends. Industrial Law Journal, 51, 831. Retrieved from https: //academic.oup.com/ilj/article/51/4/831/6871051

[20]. Sung, H.C. (2023) Platform governance in China: Antitrust issues and algorithmic transparency. Manchester Journal of International Economic Law, 20, 1. Retrieved from https: //heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/mjiel20& section=23

[21]. Liu, M., Zhang, H., and Sui, Y. (2024) Workplace artificial intelligence regulation in China: Between efficiency and social stability. ILR Review, 77, 1. Retrieved from https: //journals.sagepub.com/doi/abs/10.1177/00197939241278956b

[22]. Donoghue, R., Huanxin, L., and Moore, P. (2024) AI, regulation, and the world of work: The competing approaches of the US and China. Handbook of Public Administration and AI. Retrieved from https: //www.elgaronline.com/view/book/9781803922171/9781803922171.00035.xml

[23]. Chau, A. (2022) Regulating the algorithm: Platform economy workers in China. International Union Rights, 29, 24. Retrieved from https: //muse.jhu.edu/pub/438/article/861795/summary

[24]. Zhang, Z., Du, J., and Ding, H. (2025) China’s legal and policy pathways towards regulating algorithmic management. Industrial Law Journal. Retrieved from https: //academic.oup.com/ilj/advance-article-abstract/doi/10.1093/indlaw/dwaf007/8051889

[25]. Lee, D.S. (2025) Governing global gig platforms in the age of AI: When the manager is an algorithm. SSRN Working Paper. Retrieved from https: //papers.ssrn.com/sol3/papers.cfm?abstract_id=5316241

[26]. Kadolkar, I., and Kepes, S. (2024) Algorithmic management in the gig economy: A systematic review. Journal of Organizational Behavior, 45, 1. Retrieved from https: //onlinelibrary.wiley.com/doi/abs/10.1002/job.2831

[27]. Li, P., and Wang, M. (2024) Navigating the legal labyrinth: The future of data-driven platform labor in China. Journal of the Knowledge Economy. Retrieved from https: //link.springer.com/article/10.1007/s13132-024-02099-1

[28]. Wang, T., and Cooke, F.L. (2021) Internet platform employment in China: Legal challenges and implications for gig workers. Relations Industrielles, 76, 489. Retrieved from https: //www.erudit.org/en/journals/ri/2021-v76-n3-ri06535/1083612ar/

References

[1]. China Internet Network Information Center. (2023) Statistical Report on Internet Development in China. Retrieved from https: //www.cnnic.com.cn/IDR/ReportDownloads/202311/P020231121355042476714.pdf

[2]. Sixth Tone. (2024) Meituan Report on Delivery Workforce Provokes Pushback. Retrieved from https: //www.sixthtone.com/news/1015908

[3]. China Daily. (2025) Didi sets up $278m special fund. Retrieved from https: //global.chinadaily.com.cn/a/202506/04/WS683fa0a7a310a04af22c30b0.html

[4]. Meituan Research Institute. (2023) 2022 Employment Report on Meituan Delivery Riders [Meituan Rider Employment Report 2022]. Retrieved from https: //about.meituan.com/news/update/nb20230322

[5]. EqualOcean. (2023) A Glimpse Into the Future – From Didi’s 1st Annual Report After Listing. Retrieved from https: //equalocean.com/analysis/2023072619966

[6]. TechNode. (2023) Alibaba’s Ele.me Enhances Welfare Benefits for 3 Million Delivery Workers. Retrieved from https: //technode.com/2023/07/17/alibabas-ele-me-enhances-welfare-benefits-for-3-million-delivery-workers/

[7]. China Labour Bulletin. (2022) Living on the Edge: A Report on the Working Conditions of China’s Delivery Workers. Retrieved from https: //clb.org.hk/content/living-edge-delivery-workers

[8]. Razak, S.S., Razali, N.N., and Tuan, L.Y. (2025) Factors influencing university students’ adoption of digital labour platforms. Environment-Behaviour Proceedings Journal, 10, 195. Retrieved from https: //ebpj.e-iph.co.uk/index.php/EBProceedings/article/view/6514

[9]. Piot-Lepetit, I. (2025) Strategies of digitalization and sustainability in agrifood value chains. Frontiers in Sustainable Food Systems, 9, 1565662. Retrieved from https: //www.frontiersin.org/articles/10.3389/fsufs.2025.1565662/full

[10]. George, A. (2024) Gig economy 2.0: Examining how smart technologies could revolutionize on-demand work. Partners University Innovation Research Publications, 2, 45. Retrieved from https: //www.puirp.com/index.php/research/article/view/66

[11]. Dubal, V. (2023) On algorithmic wage discrimination. Columbia Law Review, 123, 1497. Retrieved from https: //www.jstor.org/stable/27264954

[12]. Zhao, H., Yuan, B., Gong, Y., and Liao, Y. (2025) Platform algorithmic control and work outcomes of food delivery employees. The Service Industries Journal, 45, 267. Retrieved from https: //doi.org/10.1080/02642069.2025.2477454

[13]. Xiang, Y., Du, J., Zheng, X., Long, L.R., and Xie, H.Y. (2024) Judging in the dark: How delivery riders form fairness perceptions under algorithmic management. Journal of Business Ethics, 187, 455. Retrieved from https: //doi.org/10.1007/s10551-024-05883-w

[14]. Muller, Z. (2020) Algorithmic harms to workers in the platform economy: The case of Uber. Columbia Journal of Law and Social Problems, 53, 265. Retrieved from https: //jlsp.law.columbia.edu/

[15]. Binns, R., Stein, J., Datta, S., and Van Kleek, M. (2025) Not even nice work if you can get it: A longitudinal study of Uber’s algorithmic pay and pricing. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, 2025, 1. Retrieved from https: //dl.acm.org/doi/10.1145/3715275.3732099

[16]. Muldoon, J., and Raekstad, P. (2023) Algorithmic domination in the gig economy. European Journal of Political Theory, 22, 210. Retrieved from https: //doi.org/10.1177/14748851221082078

[17]. Cameron, L. (2020) The rise of algorithmic work: Implications for organizational control and worker autonomy. University of Michigan Working Paper. Retrieved from https: //deepblue.lib.umich.edu/handle/2027.42/155277

[18]. Lian, Z., Tian, F., and Zhang, F. (2025) Transparency, control, and pay in the gig economy: A game-theoretic perspective. SSRN Electronic Journal. Retrieved from https: //papers.ssrn.com/sol3/papers.cfm?abstract_id=5174697

[19]. Xie, Z. (2022) Labour protection of platform workers in China: Legal innovations and emerging trends. Industrial Law Journal, 51, 831. Retrieved from https: //academic.oup.com/ilj/article/51/4/831/6871051

[20]. Sung, H.C. (2023) Platform governance in China: Antitrust issues and algorithmic transparency. Manchester Journal of International Economic Law, 20, 1. Retrieved from https: //heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/mjiel20& section=23

[21]. Liu, M., Zhang, H., and Sui, Y. (2024) Workplace artificial intelligence regulation in China: Between efficiency and social stability. ILR Review, 77, 1. Retrieved from https: //journals.sagepub.com/doi/abs/10.1177/00197939241278956b

[22]. Donoghue, R., Huanxin, L., and Moore, P. (2024) AI, regulation, and the world of work: The competing approaches of the US and China. Handbook of Public Administration and AI. Retrieved from https: //www.elgaronline.com/view/book/9781803922171/9781803922171.00035.xml

[23]. Chau, A. (2022) Regulating the algorithm: Platform economy workers in China. International Union Rights, 29, 24. Retrieved from https: //muse.jhu.edu/pub/438/article/861795/summary

[24]. Zhang, Z., Du, J., and Ding, H. (2025) China’s legal and policy pathways towards regulating algorithmic management. Industrial Law Journal. Retrieved from https: //academic.oup.com/ilj/advance-article-abstract/doi/10.1093/indlaw/dwaf007/8051889

[25]. Lee, D.S. (2025) Governing global gig platforms in the age of AI: When the manager is an algorithm. SSRN Working Paper. Retrieved from https: //papers.ssrn.com/sol3/papers.cfm?abstract_id=5316241

[26]. Kadolkar, I., and Kepes, S. (2024) Algorithmic management in the gig economy: A systematic review. Journal of Organizational Behavior, 45, 1. Retrieved from https: //onlinelibrary.wiley.com/doi/abs/10.1002/job.2831

[27]. Li, P., and Wang, M. (2024) Navigating the legal labyrinth: The future of data-driven platform labor in China. Journal of the Knowledge Economy. Retrieved from https: //link.springer.com/article/10.1007/s13132-024-02099-1

[28]. Wang, T., and Cooke, F.L. (2021) Internet platform employment in China: Legal challenges and implications for gig workers. Relations Industrielles, 76, 489. Retrieved from https: //www.erudit.org/en/journals/ri/2021-v76-n3-ri06535/1083612ar/

Cite this article

Sun,Y. (2025). Mathematical and Statistical Analysis of Gig Work in the Platform Economy. Advances in Economics, Management and Political Sciences,218,61-74.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICEMGD 2025 Symposium: Resilient Business Strategies in Global Markets

ISBN: 978-1-80590-385-7(Print) / 978-1-80590-386-4(Online)
Editor: Florian Marcel Nuţă Nuţă, Li Chai
Conference website: https://2025.icemgd.org/CAU.htm
Conference date: 20 September 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.218
ISSN: 2754-1169(Print) / 2754-1177(Online)

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