<![CDATA[This study examines the effects of workload and customer rating pressure on burnout, with job stress as a mediating variable, in the ride-hailing context. Using a quantitative approach, data were collected from 160 ride-hailing drivers in Makassar, Indonesia, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that customer rating pressure has a stronger impact on job stress compared to workload, highlighting the critical role of algorithmic management in shaping drivers’ psychological conditions. Job stress is found to significantly influence burnout and serves as a key mediating mechanism. While workload directly and indirectly affects burnout (partial mediation), customer rating pressure influences burnout only indirectly through job stress (full mediation). These results suggest that burnout among gig workers is not merely driven by physical job demands but is primarily shaped by psychological pressures embedded in platform-based evaluation systems. This study contributes to the literature by demonstrating that not all job demands operate through the same pathways, emphasizing the dominance of algorithmic pressure in the gig economy. The findings offer practical implications for platform providers and policymakers to design more sustainable and worker-friendly systems.]]>
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