How Dare You Refuse Me? How and When AI Negative Hiring Decision Influences Applicants’ Reactions

Despite the growing attention given to applicants' reactions to the utilization of artificial intelligence (AI) within organizational recruitment contexts, scholars have paid little attention to the emotional mechanism between AI decision-making (especially negative) and applicants' procedural justice perception, as well as how the perception affects their subsequent behavior. Drawing on the cognitive–functional model of discrete negative emotions, we propose and empirically test the effect of anger triggered by AI-driven negative hiring decisions on applicants' procedural justice perception and complaint behavior. General support for the model testing is obtained from two studies, namely, a laboratory experiment (N = 97) that uses technology for facial expression analysis (i.e., Face Reader 8.0) and an online scenario-based experiment (N = 270). The rigor of our findings is enhanced by collecting data from multiple participant sources, using FaceReader and self-reports in a complementary manner to measure anger, and by introducing control variables for robustness checks. We find that AI-driven negative decisions, rather than human-driven ones, elicit greater anger from applicants. Notably, this effect is weakened for applicants with extensive prior AI experience. Moreover, anger suppresses applicants' perceptions of procedural justice, thus yielding a distinct effect on their complaint behavior. Our study contributes to the understanding of the effect of AI-driven negative hiring decisions on applicants' emotional, cognitive, and behavioral reactions. It also sheds light on the influence of applicants' prior AI experience in reducing the negative effect of AI-driven negative hiring decisions on applicants' subsequent responses.