Algorithmic Control in the Gig Economy: Power Reconfiguration, Labor Plight, and Management Implications

The global expansion of the gig economy, coupled with the deep integration of algorithmic control, has reshaped the labor governance paradigm. This research reveals how algorithms, through mechanisms like dynamic pricing, behavior scoring, and risk transfer, reconstruct the power relations between labor and capital while enhancing platform efficiency. Workers experience an "autonomy paradox," caught by algorithmic black boxes, data surveillance, and systemic exclusion; while superficially enjoying flexibility, they effectively suffer the erosion of their health and rights. The study critically argues that algorithmic control is essentially digital Taylorism masked by "technological empowerment," with its core controversy stemming from the conflict between technological determinism and human-centric values. The article proposes algorithmic transparency, worker participatory governance, and an interdisciplinary research framework to provide a theoretical basis for balancing efficiency logic and labor protection. Future research should examine the disruptive impact of emerging technologies such as Generative AI and the Metaverse on the control models within the gig economy.