Unraveling the relationship between algorithmic management, leader’s social distance, and employee engagement: an exchange perspective

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Understanding the relationship between algorithmic management (AM) and employee engagement is crucial as AM increasingly reshapes traditional workplaces beyond the gig economy. Unlike gig settings characterized by transactional, short-term exchanges, traditional employment relationships rely heavily on social reciprocity and trust. Drawing on social exchange theory (SET), this research contributes by explaining why and how AM fundamentally restructure these traditional social dynamics. Two studies were conducted: Study 1 (N = 304) employed a cross-sectional field design, revealing that AM weakens social exchange while reinforcing economic exchange, thereby reducing employee engagement. Study 2 (N = 410) experimentally replicated these findings, established causality, and demonstrated that leader social distance critically moderates these effects. Specifically, in low-AM environments, a proximal leader reinforces social exchange, whereas in high-AM environments, leader proximity attenuates economic exchange. These findings highlight AM’s contingent impacts on engagement, demonstrating that AM actively reduces interpersonal reciprocity and trust. Thus, rather than functioning merely as a neutral technological tool, AM emerges as a central force redefining traditional employer-employee relationships. Theoretical and practical implications for human resource management are discussed.