The impact of technology acceptance and personality traits on the willingness to use AI-assisted hiring practices

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Abstract

Purpose: This study aims to investigate some individual factors that may positively/negatively impact upon the willingness to use AI-assisted hiring procedures (AI-WtU). Specifically, the authors contribute to the ongoing discussion by testing the specific role of individuals’ personality traits and their attitude toward technology acceptance. Design/methodology/approach: Data have been collected from a cohort of workers (n = 157) to explore their individual level of AI-WtU, their personality traits and level of technology acceptance, along with a series of control variables including age, gender, education, employment status, knowledge and previous experience of AI-assisted hiring. Findings: The results obtained show the significant role played by a specific personality trait –conscientiousness – and technology acceptance in shaping the level of AI-WtU. Importantly, technology acceptance also mediates the relationship between AI-WtU and conscientiousness, thus suggesting that conscientious people may be more willing to engage in AI-assisted practices, as they see technologies as means of improving reliability and efficiency. Further, the study also shows that previous experience with AI-assisted hiring in the role of job applicants has a negative effect on AI-WtU, suggesting a prevailing negative experience with such tools, and the consequent urge for their improvement. Originality/value: This study, to the best of the authors’ knowledge, is the first to test the potential role of personality traits in shaping employees AI-WtU and to provide a comprehensive understanding of the issue by additionally testing the joint effect of technology acceptance, age, gender, education, employment status and knowledge and previous experience of AI-assisted hiring in shaping individual AI-WtU.

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APA

Calluso, C., & Devetag, M. G. (2025). The impact of technology acceptance and personality traits on the willingness to use AI-assisted hiring practices. International Journal of Organizational Analysis, 33(5), 1368–1385. https://doi.org/10.1108/IJOA-06-2024-4562

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