The Impact of Explainable AI–Based Interviews on Organizational Attractiveness: The Mediating Roles of Perceived Organizational Support and Innovativeness

Abstract

This study examines the impact of explainable artificial intelligence (XAI)–based interviews on organizational attractiveness, with perceived organizational support and perceived innovativeness as mediating variables. A quantitative research design was employed, and data were collected from a sample of 302 respondents who had experience with AI-assisted or digital recruitment systems. Structural equation modeling was used to analyze relationships among variables. The findings reveal that explainable AI significantly influences organizational attractiveness (β = 0.44, p < 0.001), perceived organizational support (β = 0.39, p < 0.001), and perceived innovativeness (β = 0.42, p < 0.001). Perceived organizational support (β = 0.31, p < 0.001) and perceived innovativeness (β = 0.28, p < 0.001) both positively affect organizational attractiveness. Mediation analysis confirms that perceived organizational support (indirect effect = 0.12, p < 0.001) and perceived innovativeness (indirect effect = 0.11, p < 0.001) partially mediate the relationship between XAI and organizational attractiveness. The results indicate that transparency in AI-driven recruitment systems enhances applicants’ perceptions of fairness, organizational care, and technological advancement, which collectively improve employer attractiveness. The study contributes to human resource management literature by demonstrating the psychological mechanisms through which explainable AI influences recruitment outcomes. Practical implications suggest that organizations adopting explainable AI can strengthen employer branding and attract high-quality candidates by improving transparency and perceived organizational values in recruitment processes.