A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data

Asynchronous Video Interviewing (AVI) is considered one of the most recent and promising innovations in recruitment process. Using AVI combination with AI-based technologies enables recruiters/employers to automate many tasks that are typically required for screening, assessing, selecting candidates. In fact, automated assessment selection process a complex uncertain problem involving highly subjective, multiple interrelated criteria. order address these issues, an effective practical approach proposed able transform, weight, combine, rank assessments obtained through AI machine learning. The suggested combines Cumulative Belief Structures Weighted Bonferroni-OWA operator, which allows (i) aggregating scores different forms scales; (ii) incorporating interrelationships between criteria into analysis (iii) considering accuracies learning algorithms as weights criteria; (iv) weighting objectively. ensures completely data-driven efficient personnel To justify effectiveness applicability approach, example case presented new compared classical MCDM techniques.