When and why algorithmic control leads to app-based gig workers’ deviant work behaviour in China: A mixed-methods study in the food delivery sector

Algorithmic control (AC) aligns worker behaviour with organisational goals and has consequently become a central feature of the gig economy. Despite its success, the impact of AC on deviant work behaviours (DWB) among app-based gig workers (app-workers) remains unclear, as it can yield both positive and negative effects. To address these contradictory outcomes, this study draws on the transactional model of stress and coping, proposing that AC may be perceived as a hindrance, leading to DWB through organisational dehumanisation, or as a challenge, reducing DWB through job crafting. We also examine how technology readiness moderates workers’ appraisals of AC. Employing a mixed-methods approach, the study combines quantitative data from 317 app-workers in China (Study 1) and qualitative insights from 28 app-workers in China (Study 2). The results of Study 1 reveal that AC has a direct negative impact on app-workers’ DWB, and an indirect negative impact through job crafting. This indirect effect is stronger when technology readiness is higher. Conversely, AC also has a positive indirect impact on DWB via organisational dehumanisation, with this effect being stronger when technology readiness is lower. The qualitative findings from Study 2 provide deeper insights into these relationships. Overall, the results offer important theoretical and practical implications for understanding app-workers’ psychological and behavioural responses to AC, suggesting ways to mitigate the negative effects of AC and improve its effectiveness in the gig economy.