Exploring DEA Personality Index Utility for Reskilling Candidate Selection

Abstract

Research Question: This study examines whether personality traits can be a valid criterion for candidate selection in reskilling programs and whether they can be objectively aggregated and ranked using quantitative methods. Motivation: Governments increasingly fund reskilling programmes to address shortages of IT competencies. Selecting the right candidates becomes critical when traditional criteria such as prior knowledge or formal qualifications are excluded. In such contexts, decision-makers need transparent and data-driven tools to differentiate among candidates with similar profiles. This study addresses that gap by combining psychological assessment with quantitative evaluation. The novelty lies in applying the Data Envelopment Analysis (DEA) method for personality-based candidate ranking. This approach enables more objective and transparent decision-making in the selection process. Idea: This study proposes a personality-based competence index for candidate selection in reskilling programs, integrating Cattell's 16 Personality Factor model with the DEA method. Data: Data were collected from 240 candidates who applied for a government-funded IT reskilling program in Serbia. Candidates had no prior IT knowledge, experience, or formal qualifications in the field. Tools: The study applies Cattell's 16PF questionnaire for personality assessment and DEA, a non-parametric method based on linear programming, to construct a composite personality index. DEA enables objective weight assignment for each candidate without predetermined criteria importance, allowing relative competence ranking across all candidates. Findings: Reasoning emerged as the strongest predictor of reskilling success, followed by self-control, independence, and extraversion. Anxiety and tough-mindedness were identified as undesirable dimensions in this context. The DEA method successfully ranked candidates, identified competence gaps, and provided measurable improvement targets, demonstrating its practical utility as a selection support tool in reskilling contexts. Contribution: This study introduces a novel DEA-based personality competence index as an objective, transparent decision-support tool for candidate selection in reskilling programs.