The Impact of Online Platform Algorithmic Control on Gig Worker Task Performance
Based on the job demands-resources model,this study constructs a dual-chain mediation model of online platform algo-rithmic control affecting gig worker task performance.Through a multi-time-point questionnaire survey of 286 full-time gig workers from two leading platforms,the research results show that the independent mediating effects of information quality perception,self-efficacy,time pressure,and emotional exhaustion are significant between algorithmic control and task performance.Algorithmic control has a positive impact on task performance through the chain-mediating role of information quality perception and self-efficacy,and has a neg-ative impact on task performance through the other chain-mediating role of time pressure and emotional exhaustion.The conclusions of this study not only enrich the theoretical research on the impact effect of algorithmic control,but also provide practical implications for platforms to optimize algorithmic control and gig worker management.