Inaccuracies in Expert Judgment: Comparative Analysis of RANCOM and AHP Methods in Housing Location Selection Problem

Abstract

The effective extraction of expert knowledge is paramount for ensuring reliable results in decision support systems, especially considering the complexities inherent in decision-making and the potential inaccuracies of expert judgment. Identifying criteria weights based on expert knowledge is essential for reducing the impact of emerging uncertainties. In this study, we apply the Ranking Comparison (RANCOM) and Analytic Hierarchy Process (AHP) methods to determine criteria importance, focusing on their practical application in the context of a housing location selection problem. The novelty of this study lies in the comprehensive verification of the performance of the RANCOM and AHP methods, combined with selected Multi-Criteria Decision Analysis (MCDA) methods. The proposed approach provides a more comprehensive understanding of how these techniques perform in different decision-making scenarios, enriching the knowledge base in this field. Through the analysis, we underscore the practical effectiveness of RANCOM in navigating complex decision-making problems. This highlights the significance of methodological advancements in subjective weighting techniques and emphasizes the need for robust approaches to address uncertainties and inaccuracies in expert judgments.

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