Online platform algorithmic control and gig workers’ turnover intention in China: The mediating role of relative deprivation
Based on the job demands-resources (JD-R) model, this study aims to investigate how algorithmic behavioral constraint and algorithmic tracking evaluation affect gig workers’ turnover intention by increasing relative deprivation and the extent to which this mediating role is moderated by algorithmic standardized guidance. Data from 242 gig workers were collected in two rounds and used to test the hypotheses. The results reveal that algorithmic behavioral constraints and algorithmic tracking evaluation are positively related to turnover intention, while algorithmic standardized guidance is negatively related to turnover intention. Moreover, algorithmic behavioral constraint and algorithmic tracking evaluation are positively related to turnover intention through relative deprivation, with algorithmic standardized guidance weakening this effect.
Authors
- Shanshi Liu (ORCID: https://orcid.org/0000-0001-9719-1234)
- Xiaoxiao Gong (ORCID: https://orcid.org/0000-0001-8279-9140)
- Change Liu
- Shengxian Yu (ORCID: https://orcid.org/0000-0001-5458-8979)
- Wei Cai (ORCID: https://orcid.org/0000-0002-8716-3974)
Institutions
- Guizhou University (CN)
- University of Technology Malaysia (MY)
- Hunan University of Technology (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Journal of Management Science and Engineering
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1016/j.jmse.2024.08.004
- Citations
- 13
- Primary Topic
- Digital Economy and Work Transformation
- Type
- article
- Field-Weighted Citation Impact
- 14.72
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province
- National Social Science Fund of China
- Science Foundation of Ministry of Education of China