<![CDATA[This study presents a multi-scenario comparative analysis of objective weighting techniques integrated with the MOORA method in decision support systems to evaluate their consistency, robustness, and reliability in alternative ranking. Various objective weighting methods, including WENSLO, LOGSTA, RECA, LODECI, ITARA, CRISUS, MPSI, and SITDE, were applied to a decision matrix representing candidate store locations with multiple criteria such as rental cost, building area, accessibility, consumer traffic, parking availability, and infrastructure. The analysis was conducted under different data scenarios to examine the sensitivity of each method to variations in data characteristics. The results show that although there are differences in the weight distributions generated by each method, the final rankings produced by the MOORA approach remain highly consistent, with NSL 5 consistently ranked as the best alternative. Furthermore, the Spearman correlation analysis reveals very strong agreement among the methods, with correlation values of 0.9762 for WENSLO, LOGSTA, LODECI, ITARA, CRISUS, and MPSI, and perfect correlation values of 1.000 for RECA and SITDE. These findings indicate that the proposed approach is stable and not sensitive to the choice of weighting method, thereby enhancing confidence in the decision-making process. Overall, this study demonstrates that integrating multiple objective weighting techniques within a MOORA-based framework provides a reliable, objective, and consistent solution for multi-criteria decision-making problems.]]>
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