Abstract
BACKGROUND: Online labor platforms rely on algorithmic control to manage gig work, but its impact on work engagement remains contested. Existing research predominantly adopts technological determinism perspectives, neglecting gig workers' agency, and lacking systematic exploration of motivational mechanisms and emotional resources. Based on Self-Determination Theory, this study examines how perceived algorithmic control influences work engagement through psychological empowerment, with deep acting as a moderator. METHODS: Data were collected from Chinese gig workers (delivery riders/ride-hailing drivers, N = 392) through snowball and convenience sampling. Established scales measured core variables. Common method bias was tested using SPSS and AMOS, while PLS-SEM analyzed reliability, validity, and hypothesized pathways. RESULTS: Perceived algorithmic control positively affects work engagement. Three psychological empowerment sub-dimensions-meaning, influence, and competence-partially mediate relationships between perceived algorithmic control sub-dimensions and work engagement respectively. Deep acting strengthens the positive effect of perceptual algorithm tracking evaluation on influence, and shows highest importance for work engagement but suboptimal performance. Among psychological empowerment sub-dimensions, meaning exhibits the most prominent importance and requires priority optimization. CONCLUSIONS: This study transcends technological determinism and validates the positive pathway through which algorithmic control enhances work engagement via psychological empowerment. It reveals meaning construction's central role and deep acting's differentiated moderating effects. Online labor platforms should optimize algorithm design, strengthen meaning perception, reduce ineffective monitoring, implement psychological empowerment incentive mechanisms, provide emotional resource support, and guide deep acting strategies.