In recent business practices, artificial intelligence (AI) based job interviews are often used to conduct online preliminary job interviews with applicants. While AI-based job interviews have become a popular trend, applicants’ perceived interactional justice has been challenged. Applicants feel themselves more like “ a number ” than a worthy candidate. However, there is limited understanding of the influencing factors of perceived interactional justice in AI-based job interviews. To fill this gap, this study establishes a theoretical model to explore the antecedents of the applicants ’ perceived interactional justice based on organizational justice theory. Based on literature review, this study tests the impacts of the gender of AI interviewer, linguistic style of AI interviewer, and whether to provide timely and informative feedback on perceived interactional justice of applicants. The effects of perceived interactional justice on overall favorability and organizational attractiveness are also explored.
Wang, Xiaodi; Min, Qingfei; and Liu, Zhiyong, "Antecedents and Impact of Applicants’ Perceived Interactional Justice in AI-based Job Interviews" (2021). PACIS 2021 Proceedings. 29.
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