Algorithm transparency and turnover intention of gig workers: the role of perceived dehumanization and self-perceived employability

Purpose Drawing on conservation of resources theory (COR), this study explores the effect of algorithm transparency on gig workers' turnover intention, along with the mediating role of perceived dehumanization and the moderating role of self-perceived employability. Design/methodology/approach We conducted two studies to test the hypotheses. Study 1 was a scenario-based experiment that collected data from 149 participants. Study 2 was a multi-wave survey that collected data from 194 gig workers. Findings We found that algorithm transparency is negatively related to turnover intention, and perceived dehumanization mediates this relationship. Self-perceived employability moderates the effect of perceived dehumanization on turnover intention and the indirect effect of algorithm transparency on turnover intention through perceived dehumanization, with both effects being stronger when self-perceived employability is high. Originality/value This study deepens the academic understanding of the relationship between algorithm transparency and gig workers' turnover intention, and offers implications for gig platforms to reduce the turnover intention of gig workers.