A Comparative Analysis of Multi-Criteria Decision Methods for Personnel Selection: A Practical Approach

Abstract

This research focused on decision-making supported by multi-criteria decision methods, specifically TOPSIS, OWA, and their respective variants within personnel selection. The study presented models aimed at facilitating the selection of the best candidate for a job through competency-based assessments and comparing the application of four methods across various scenarios. We employed methods such as TOPSIS, OWA, and two variations (Canós–Liern method and an OWA model based on mathematically replicating expert opinion). Each model provided distinct rankings and demonstrated adaptability to specific situations within a company. Furthermore, it was emphasized that each method could and should be tailored according to the company’s reality to derive maximum benefit from its implementation. A crucial aspect of securing the best candidates involves understanding the context and identifying the appropriate methodology.