‘Gain or drain’? The nonlinear effects of algorithmic management on job performance from a proactive behaviour perspective in China

Based on the Proactive Motivation Model and integrating Self-Determination Theory and Social Information Processing Theory, this study incorporated individual traits to develop a moderated nonlinear mediation model. Using Stata 16 and Mplus 8.0, we analysed 401 three-wave datasets from questionnaire surveys of Chinese employees. The findings revealed a positive U-shaped relationship between algorithmic management and employees’ work engagement. Algorithmic management exerts an inverted U-shaped indirect effect on job performance, mediated by work engagement. Employees’ proactive behaviour is found to moderate nonlinear indirect effects. The study offers theoretical and practical implications for achieving ‘technology empowerment’ rather than ‘technology constraints’.