Research on the Impact of Algorithmic Management on Employee Work Behavior in Platform Enterprises
Abstract
This paper, set against the backdrop of platform enterprises, examines the impact of algorithmic management on employee work behavior. Through a literature review and theoretical construction, the study first defines the core concepts of platform enterprises, algorithmic management, and employee work behavior, while outlining related theoretical foundations such as institutional theory, the technology acceptance model, and social exchange theory. Based on this, a conceptual model is developed that describes how algorithmic management influences employee behavior through mediating variables such as trust, sense of control, and performance incentives. The research suggests that while algorithmic management enhances work efficiency and enables personalized incentives, it may also trigger issues such as excessive monitoring, privacy infringements, and a decline in employee autonomy. Finally, the paper discusses how platform enterprises should balance technological applications with humanistic care in practice, offering theoretical insights and references for future empirical research.
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