This paper proposes a robust multi-criteria decision-making (MCDM) framework for evaluating and selecting Point-of-Sale (POS) systems in the context of Retail 5.0, where decisions involve multiple criteria and inherent uncertainty. The approach integrates entropy-based objective weighting with fuzzy AHP for subjective assessment, while incorporating Z-number theory to explicitly account for decision-makers’ confidence. Unlike conventional methods that assume equal importance between subjective and objective components, the proposed framework introduces a confidence-adjusted integration mechanism, in which Z-numbers are used to dynamically modulate the influence of subjective judgments based on their reliability. This enables a more balanced and context-sensitive weighting process that better reflects both data characteristics and human uncertainty. The contribution of this study is twofold: methodologically, it develops a reliability-driven integration framework that enhances the robustness and credibility of criteria weighting; practically, it demonstrates the applicability of the approach through a real-world POS system selection case. The results confirm that the proposed method provides more stable and informative decision outcomes, highlighting its effectiveness in complex decision-making environments.
Shyur et al. (Mon,) studied this question.