This study demonstrates how interactional justice influences affective commitment in flexible gig work, highlighting the role of algorithmic monitoring.
Broadly using algorithmic monitoring systems, digital gig platforms offer flexible work arrangements but simultaneously expose workers to various insecurities in non-standard employment, leading to high turnover rates and lower job performance. We address this underexplored question by exploring how and when to cultivate affective commitment among highly flexible but insecure platform workforces. Drawing on fairness heuristic theory and the mutual verification of 269 two-wave time-lagged surveys and 303 cross-sectional surveys from gig workers working on different digital platforms in China, we demonstrate that interactional justice fully mediates the positive effect of platform work flexibility and the negative effect of platform work insecurity on affective commitment to the platform. Interactional algorithmic monitoring mitigates the indirect negative effect of platform work insecurity on affective commitment. We offer key ergonomic implications for designing supportive interactional algorithmic monitoring systems enabling gig workers to improve performance-related outcomes by fostering their affective commitment to the platform.
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Wang et al. (2025) studied this question.
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