ScholarWorks@성균관대학교

초록

The accelerated adoption of artificial intelligence (AI) in hiring is prompting questions about how national institutions and policy initiatives shape societal acceptance of AI-driven selection tools. In South Korea, a state-led push for fair hiring, via blind recruitment, coexists uneasily with employers' drive for efficiency amid high applicant pools. Drawing on institutional complexity and technology governance perspectives, we examine how government-driven fairness logic and firm-level efficiency logic jointly influence AI recruitment adoption. Applying Kaplan-Meier estimation and Cox proportional hazards models to an unbalanced panel dataset (111 firms, 449 firm-year observations, 2018-2022) constructed by integrating publicly available firm-level panel data with survey responses from HR managers, we find that organizations adopting blind recruitment (fairness logic) are significantly more likely to implement AI hiring systems. Likewise, firms experiencing higher applicant-to-hire competition (efficiency logic) also adopt AI more frequently. However, the interaction effect between fairness and efficiency logics is not statistically significant, suggesting incomplete alignment between policy-led fairness objectives and organizational efficiency demands. Our findings highlight how socio-technical contexts guide the path of AI technology diffusion in recruitment: in particular, state-led policy reforms, cultural discourses on fairness, and large-scale applicant competition. We discuss implications for technology governance, institutional actors' roles, and the balancing act between fairness and efficiency in digital hiring practices.

키워드