Objective weighting methods can produce different criterion priorities and may consequently alter TOPSIS rankings. This study compares RECA, G2M, and LOPCOW within a common TOPSIS framework using a supplier performance dataset comprising seven suppliers and six benefit criteria. Each weighting method was applied to the same decision matrix, and the resulting supplier rankings were evaluated against a reference ranking using Spearman’s rank correlation coefficient. RECA produced a moderately balanced weight distribution, G2M generated nearly uniform weights, and LOPCOW yielded the most differentiated pattern, assigning greater importance to availability, communication, and responsiveness. RECA–TOPSIS and G2M–TOPSIS generated identical rankings and each achieved a Spearman coefficient of 0.9643, whereas LOPCOW–TOPSIS obtained 0.8571 and produced more shifts among middle-ranked suppliers. The findings show that distinct objective weighting mechanisms can substantially change criterion weights while preserving broadly similar ranking structures within the analyzed case. These results should be interpreted as case-specific rather than as evidence of general methodological superiority.
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