ALGORITHMIC MANAGEMENT IN HRM: AN ANALYSIS OF ITS IMPACT ON EMPLOYEE AUTONOMY, ORGANIZATIONAL JUSTICE, AND PRODUCTIVITY

Abstract

The transformation of human resource management (HRM) has undergone a fundamental shift toward algorithmic management (AM) driven by artificial intelligence (AI) and big data analytics. This study aims to analyze the impact of AM implementation on employee autonomy, perceptions of organizational justice, and productivity, particularly within the context of digital transformation in developing countries such as Indonesia. Using a narrative review approach, this study systematically synthesizes literature published over the last decade from the Scopus, Web of Science, and PsycINFO databases concerning algorithmic control in both platform-based and conventional organizations. The findings reveal the emergence of a “productivity–well-being paradox,” in which increased operational efficiency is frequently accompanied by a decline in employee autonomy, reflected in the shift from discretionary decision-making toward algorithmic conformity. Furthermore, the opacity of black-box algorithms was found to reduce perceptions of procedural justice and weaken employee trust in organizational decision-making processes. The study concludes that effective implementation of AM requires the integration of principles from Self-Determination Theory and Organizational Justice Theory through transparent, accountable, and human-centered governance mechanisms. Such an approach is essential to mitigate negative psychosocial consequences, including technostress and burnout, while maintaining organizational productivity and employee well-being.