IMPLICATION OF RISK-AS-FEELING IN SELECTION AND RECRUITMENT DECISION-MAKING FOR RECRUITERS AND HIRING MANAGERS
DOI:
https://doi.org/10.60101/gbafr.2025.277741Keywords:
Decision making, Human resources management (HRM), Selection, Recruitment, Diversity and inclusion, Risk as Feeling (RaF), Artificial intelligence (AI)Abstract
Purpose – This article investigates the role of the Risk-as-Feeling (RaF) theory in shaping decision-making during recruitment and selection processes. It highlights the emotional and psychological factors influencing recruiters and hiring managers and their implications for fairness and inclusivity in hiring practices.
Body of knowledge – The article draws on the Risk-as-Feeling theory, which suggests that emotional responses significantly shape risk perception and decision-making. It identifies key subjective factors—such as cognitive biases, emotional influences, cultural norms, past experiences, and the role of technology—that impact hiring decisions. By synthesizing findings from behavioral economics, psychology, and HR studies, the article explains how these factors can lead to biased recruitment outcomes, including discrimination based on gender, race, and other attributes. It also explores the dual role of AI in amplifying or mitigating biases in recruitment processes.
Implications – Understanding the influence of emotions and biases in hiring decisions can help recruiters make more informed, equitable, and effective choices. Practical benefits include adopting structured hiring practices, transparency in decision-making, and ethical integration of AI tools to reduce bias. These strategies support diversity and inclusion, improving organizational outcomes and candidates' experiences.
Originality/Value – This article is among the first to apply the Risk-as-Feeling theory to recruitment and selection, bridging insights from behavioral economics and human resource management. It provides a novel perspective on the emotional underpinnings of hiring decisions and offers actionable strategies to address bias, contributing to academic discourse and practical improvements in HR practices.
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