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A Sociological Analysis of Digital Platform Algorithms' Control over Riders' Labor

Author(s)

Peichen Yan*

Affiliation(s)

Beijing Royal School, Beijing, China *Corresponding Author

Abstract

Platform-based delivery work exemplifies algorithmic governance, where labor is managed through the reorganization of time, space, and recognition into machine-readable signals. This “algorithmic management” creates a control architecture that asserts market neutrality while producing asymmetrical dependence. Synthesizing empirical studies across jurisdictions and quantitative surveys, research shows platforms convert uncertainty into discipline. Algorithmic control operates as a triangular regime—platform metrics, consumer ratings, and urban infrastructure—generating a distinct form of labor power: command without supervisors, sanctions without due process, and incentives that individualize risk. While efficient in matching and coordination, its limitations stem from data extraction, risk externalization, and competitive isolation. Evidence consistently links algorithmic intensification to adverse psychosocial outcomes like burnout and risk-taking among riders, alongside tactical resistance and sporadic solidarity. This shift goes beyond flexibility vs. precarity—labor is reconstituted as continuously audited motion, turning the city into an instrument of management. Governance should therefore prioritize algorithmic due process, data access, and collective voice, treating platform control as infrastructural power rather than private preference.

Keywords

Algorithmic Management; Platform Labor; Gig Economy; Riders; Labor Process; Surveillance; Urban Sociology

References

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