NOVEL DISTANCE MEASURE IN FUZZY TOPSIS TO IMPROVE RANKING PROCESS: AN APPLICATION TO THE SPANISH GROCERY INDUSTRY

Abstract

In this paper, a novel approach to measuring distances between triangular fuzzy numbers is suggested. This new method allows to improve sensitivity of results. We also apply several methods together with our proposal to rank the financial performance of Spanish grocery store companies. Methods such as Fuzzy Analytic Network Process (FANP) and fuzzy TOPSIS are integrated in the proposed model. The weights for criteria and subcriteria are computed based on the judgments of experts using FANP. Then, these weights and financial ratios are inputs to the fuzzy TOPSIS method to rank the companies. In the case of fuzzy TOPSIS, several distance measures are applied and a novel measure based on the Spearman distance is introduced. We conclude that results applying fuzzy TOPSIS depend on the selected distance and therefore the decision maker has to apply different distance measures to improve conclusions. Finally, a sensitivity analysis of the analyzed measures has been performed.