How does AI recruitment influence satisfaction among student job-seekers? The role of self-efficacy as a moderator and mediator

Abstract

Introduction. Companies have recently begun to use Artificial Intelligence (AI) technology for recruitment. Job seekers are then analysed and recruited by AI interview systems. However, there is a lack of studies on the relationship between AI recruitment and job seekers.Aims. This study aims to analyse job seekers’ perception of AI recruitment expected value, to investigate how to improve job seeker satisfaction under the AI recruitment technology, and to explore the expectations of job seekers in the AI recruitment process. Besides, self-efficacy serves as a moderator and mediator in the relationship between perception of AI recruitment expected value and job seeker satisfaction.Aims. This study aims to analyse job seekers’ perception of AI recruitment expected value, to investigate how to improve job seeker satisfaction under the AI recruitment technology, and to explore the expectations of job seekers in the AI recruitment process.Methodology and research method. A sample of 254 student job seekers was collected for data analysis. Self-efficacy serves as a moderator and mediator in the relationship between perception of AI recruitment expected value and job seeker satisfaction. Through factor analysis, the study classified and named each dimension of perception of AI recruitment expected value and self-efficacy. Perception of AI recruitment expected value is divided into full participation, process flexibility and file diversity. Self-efficacy is divided into positivity and confidence. Next, statistical analysis was then performed to test the hypotheses.Results. The findings show that (1) the process flexibility is positively correlated with job seeker satisfaction; (2) positivity has a moderating effect on full participation and job seeker satisfaction; (3) confidence has a moderating effect on process flexibility and job seeker satisfaction; (4) positivity and confidence serve as mediators the relationship between perception of AI recruitment expected value and job seeker satisfaction.Scientific novelty. The current study helped to develop new scales to measure the constructs related to AI recruitment.Practical significance. The findings provide us with information to improve job seeker satisfaction in AI recruitment. Companies provide AI recruitment maps before recruiting, give job seekers greater flexibility in the process, and finally produce recruitment results quickly after the job search and provide feedback from AI analysis.