Algorithmic control and delivery worker service behavior in instant delivery industry

Abstract

Leveraging affective events theory and the challenge-hindrance framework, this research develops a model to investigate the diametrical impacts of algorithmic control—as a dual-edged sword—on the service behaviors of delivery workers. We collected the questionnaire data and adopt the OLS regression and structural model to test our hypotheses. In particular, we suggested that challenge appraisal toward algorithmic control will promote delivery workers’ service behavior via their positive affect at work; hindrance appraisal toward algorithmic control will inhibit their service behavior via emotional exhaustion. Meanwhile, compared with full-time employees, the positive effect of algorithm control on part-time employees is weaker, and the negative effect is stronger. A large-scale online survey of delivery workers on Chinese online labor platforms underpinned the theoretical model.