Dark sides of algorithmic control in app-based gig work: An objectification perspective
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.
Authors
- Yongshun Xu (ORCID: https://orcid.org/0000-0003-1885-4306)
- Ming Chi (ORCID: https://orcid.org/0000-0002-6532-9371)
- Xinhua Bi
- Yihao Yang (ORCID: https://orcid.org/0009-0008-2440-3660)
Institutions
- Jilin University (CN)
- Hainan University (CN)
Publication Details
- Journal
- Journal of Business Research
- Published
- 2025-04-20
- DOI
- https://doi.org/10.1016/j.jbusres.2025.115407
- Citations
- 12
- Primary Topic
- Digital Economy and Work Transformation
- Type
- article
- Field-Weighted Citation Impact
- 50.42