Platform algorithmic stress and career commitment of Chinese gig workers: a double-edged sword effect study

The rise of the platform economy has not only created numerous gig employment opportunities but also subjects gig workers to algorithmic stress. While existing research predominantly focuses on the negative consequences of algorithmic stress, many gig workers still exhibit high career commitment. To explain this paradox, this study draws on Self-Determination Theory and surveys 354 full-time Chinese gig workers, proposing a dual-path mediation model. Results reveal two opposing indirect effects of algorithmic stress on gig workers' career commitment. Firstly, algorithmic stress has a positive impact on gig workers' job crafting behaviors, which in turn enhance their career commitment. Secondly, algorithmic stress also has a on gig workers' sense of relative deprivation, which subsequently reduces their career commitment. This study advances algorithmic stress research by uncovering both facilitative and inhibitive pathways, extends Self-Determination Theory to algorithmic management, and offers practical insights for platform algorithm design so as to promote high-quality gig employment.