Algorithmic Control, Economic Dependence, and Institutional Mismatch: A Mixed-Methods Study of Food-Delivery Riders in Beijing

Abstract

The growth of digital platforms has rapidly expanded the food-delivery sector while intensifying concerns about riders’ employment status, social protection, algorithmic management, and access to dispute resolution. This study adopts a multi-source mixed-methods design, drawing on 976 judicial decisions involving food-delivery riders across China, including 52 from Beijing, a survey of 482 riders in Beijing, and semi-structured interviews with 20 riders, five platform managers, and five legal practitioners. Only 7.7% of surveyed riders had formal employment contracts. Only 23% had coverage for work-related injuries or occupational injury protection. Moreover, 63.9% regarded platform algorithmic rules as unreasonable. Across the three data sources, riders mainly face difficulties in identifying employment status classification, insufficient social security, algorithmic management disputes, and poor access to legal remedies. Algorithmic control, economic dependence and institutional mismatch constitute important mechanisms to understand the above labor protection gaps. The paper argues for improving employment-status determination standards based on actual control, expanding the coverage of occupational injury protection, and strengthening algorithmic transparency, appeal review, and coordination among multiple responsible actors.