Assessing and ranking the skills required for IT personnel: a hybrid decision-making model using fuzzy AHP-TOPSIS

Purpose The hiring process for information technology (IT) personnel, given its high stakes and intricacies, demands an objective, methodical and nuanced approach. The multifaceted nature of IT roles necessitates a comprehensive evaluation methodology to identify and prioritize pertinent skills and competencies. Therefore, this study aims to devise and implement a robust multi-criteria decision-making model integrating the fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) for assessing and ranking the skills required for IT personnel. Design/methodology/approach This study integrates expert opinions and insights from the literature to identify five key criteria and 21 sub-criteria essential for IT personnel selection. The fuzzy Analytic Hierarchy Process (AHP) was applied to determine the relative importance of each criterion and sub-criterion. These weighted criteria were then utilized in the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to systematically rank five candidate alternatives based on their suitability for IT roles. Findings Results identified “Objective of factors” to be the most significant criteria, whereas “Assessment Centre Score” as the most viable sub-criterion. Using the integrated model results of fuzzy AHP-TOPSIS candidate, A3 was the most fitted IT personnel, whereas Candidate A4 has emerged as the poor/ unsuitable fit. Practical implications This research helps firms and policymakers use their limited resources efficiently. Furthermore, this study acts as a guideline for future researchers to empirically investigate the impact of listed skills on employee performance. Originality/value This study is a pioneering effort in integrating fuzzy AHP and TOPSIS to address the challenges in IT personnel selection, catering to the intricate layers of human evaluative judgments. Its extended applicability and innovative approach makes it a valuable contribution to the existing body of knowledge, serving as a benchmark for future endeavors in related domains.