The Adoption and Utilization of Algorithmic HRM: The Impact of Organizational Management Orientation

The increasing use of advanced technologies in human resource management, such as big data driven decision making, HR analytics, and AI-enhanced selection processes, is a notable trend. Algorithmic HRM refers to the application of advanced algorithms to automate tasks within human resource management or to facilitate data-driven decision making. This study seeks to investigate the differences in the adoption and utilization of algorithmic HRM among organizations based on organizational management orientations. In particular, this study posits that companies may vary in their perception of usefulness and ease of use for algorithm HRM depending on two distinct management orientations: control structure and external orientation. Based on the empirical analysis of 329 companies, our findings indicate that organizations with a control structure orientation, compared to those valuing flexibility structure, were more likely to adopt and utilize algorithmic HRM. Similarly, our results show that companies prioritizing the integration of internal resources, rather than relying on external environments, tend to be more engaged with algorithmic HRM. Based on these findings, the study discusses theoretical and practical implications and suggests future directions for algorithm HRM research.