Promotion or suppression? Effect of perceived algorithmic control on service performance of gig workers

Gig workers have been managed using algorithmic control for years, but gaps remain in research on and knowledge about how algorithmic control affects their service quality. Combining the job demands–resources model with conservation of resources theory, we examined the relationship between perceived algorithmic control and service performance through an empirical study with 475 gig workers. The results showed that work engagement played a mediating role between gig workers' perceived algorithmic control and their service performance, with burnout playing a mediating role in this relationship. The indirect effects of (a) perceived algorithmic control on service performance via work engagement and (b) perceived algorithmic control on service performance via burnout were weaker when there was high (vs. low) algorithmic transparency. Overall, our research results provide theoretical and practical implications for managing gig workers.