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Dark sides of algorithmic control in app-based gig work: An objectification perspective

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  • Yang, Yihao
  • Chi, Ming
  • Bi, Xinhua
  • Xu, Yongshun

Abstract

App-based gig work (app-work) relies on algorithmic control (AC) to enhance operational efficiency and minimize costs. While flexible, app-work raises concerns regarding workers’ well-being and performance. Applying the stressor-strain-outcome framework, this study examines the relationship between AC and app-workers’ proactive customer service performance (PCSP) from an objectification perspective. AC can lead to organizational and self-objectification, diminishing workers’ motivation to engage in proactive customer service. This study uses a mixed-methods approach, combining quantitative data from 300 (Study 1) and qualitative insights from 25 app-workers (Study 2). A negative relationship exists between AC and PCSP, mediated by organizational and self-objectification. Coworker support moderates the impact of AC on organizational and self-objectification. Study 2 identifies contextual factors that may influence the verified relationships, providing insights into the research phenomenon. This research contributes to understanding app-workers’ psychological and behavioral responses to AC.

Suggested Citation

  • Yang, Yihao & Chi, Ming & Bi, Xinhua & Xu, Yongshun, 2025. "Dark sides of algorithmic control in app-based gig work: An objectification perspective," Journal of Business Research, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:jbrese:v:195:y:2025:i:c:s0148296325002309
    DOI: 10.1016/j.jbusres.2025.115407
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