Algorithmic Management, Voice Efficacy, and Organizational Silence: A Conceptual Framework

Artificial intelligence is increasingly embedded in managerial activities, including task allocation, performance monitoring, employee evaluation, and decision support. As a result, algorithmic management has emerged as a distinctive form of organizing and exercising managerial authority, in which algorithmic and AI-based systems perform or support functions traditionally associated with human managers. Although these systems may improve efficiency, consistency, and scalability, their implications for employee voice and organizational silence remain insufficiently integrated within the existing literature. This study therefore examines how algorithmic management may influence employees' willingness to express suggestions, raise concerns, and challenge organizational decisions. Using a conceptual and integrative literature review, the study synthesizes recent research on algorithmic management, employee voice, organizational silence, contextual voice efficacy, and AI governance, with particular attention to literature published between ۲۰۲۰ and ۲۰۲۶. The review suggests that the behavioral consequences of algorithmic management depend not only on its technical functions but also on how employees interpret algorithmic authority. When algorithmic systems are perceived as highly controlling, opaque, difficult to challenge, or disconnected from identifiable human accountability, employees may experience a reduced sense of influence over organizational decisions. Building on these insights, the study proposes a sequential conceptual framework in which algorithmic management may strengthen perceived algorithmic control, which may subsequently weaken contextual voice efficacy and increase the likelihood of organizational silence. The study further identifies human oversight, employee participation, transparency, accountability, and organizational responsiveness as governance conditions that may protect meaningful employee voice. The framework contributes to the emerging literature on algorithmic management by connecting it with established research on voice and silence and by extending the discussion to public organizations, where employee knowledge, accountability, and institutional legitimacy are particularly important. The study provides a behavioral governance perspective for designing more human-centered and participatory approaches to AI-enabled management.

کلیدواژه ها:

Algorithmic Management ، Organizational Silence ، Artificial intelligence ، Contextual Voice Efficacy