Comparison of key weighting methods in multi-criteria decision analysis

Purpose:The paper aims to conduct a structured comparison of key weighting methods used in Multi-Criteria Decision Analysis (MCDA) Design/methodology/approach: The study provides a qualitative assessment of eight selected weighting methods, categorized as subjective (AHP, SMART/SWING, Direct Rating, BWM), objective (Entropy, CRITIC, PCA), and hybrid (Fuzzy AHP + Entropy).A set of seven evaluation criteria is proposed: ease of use, data requirements, transparency, resistance to subjectivity, group applicability, compliance with decision theory, and stability of results.A comparative matrix was developed using a structured Likert-scale-based scoring system.Findings: No single method proved to be universally superior across all evaluation dimensions.Subjective methods offer greater intuitiveness and simplicity, while objective methods provide better stability and theoretical soundness.Hybrid methods present a balanced compromise but may suffer from computational complexity.The Best-Worst Method (BWM) and hybrid approaches achieved the highest overall scores. Research limitations/implications:The evaluation is based on the author's subjective judgment and literature review.The scoring reflects synthesized knowledge rather than empirical testing.Future research could include sensitivity analyses or the application of fuzzy/probabilistic evaluation to account for uncertainty. Practical implications:The study provides decision-makers with contextual recommendations for selecting appropriate weighting techniques depending on the nature of the decision environment, the availability of data, and the level of stakeholder involvement.Originality/value: This paper offers a unique synthesis and structured comparison of key weighting methods within the MCDA framework, combining theoretical classification with a multi-criteria quality assessment matrix.It contributes to both academic research and practical guidance for analysts and policy-makers.