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

Yihao Yang, Ming Chi, Xinhua Bi and Yongshun Xu

Journal of Business Research, 2025, vol. 195, issue C

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.

Keywords: Algorithmic control; Proactive customer service performance; Organizational objectification; Self-objectification; Coworker support (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:195:y:2025:i:c:s0148296325002309

DOI: 10.1016/j.jbusres.2025.115407

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