A Contemporary Approach for Solving Selection Problems: The Entropy-Based Performance Measurement Method

Authors : Furkan Fahri Altıntaş
Pages : 1373-1400
Doi:10.34248/bsengineering.1699472
View : 101 | Download : 105
Publication Date : 2025-09-15
Article Type : Research Paper
Abstract :In this study, the applicability of the widely used entropy method traditionally employed for calculating criterion weights in the Multi-Criteria Decision-Making (MCDM) literature is investigated as a novel approach for measuring the performance of alternatives. The proposed method, termed Entropy-Based Performance Measurement (EBPM), is grounded in the principle of continuously increasing uncertainty inherent in both natural and social systems. The primary motivation of this approach is to demonstrate, through sensitivity, comparative, and simulation analyses, that the method can produce ideally sensitive, reliable, consistent, stable, and robust results. The study aims to expand the application domain of the entropy method and to contribute to both the MCDM and entropy literature. EBPM is theoretically based on entropy’s inherent capability to quantify and enhance informational performance. Without manipulating the original entropy equation, the entropy function is reformulated into a positively increasing structure, enabling it to measure the performance of alternatives. In the methodology section, the characteristics of 15 widely recognized MCDM methods are introduced, the theoretical and mathematical foundations of the proposed approach are explained, and its applicability is demonstrated using the innovation performance data of seven countries selected from the 2024 Global Innovation Index. In the results and discussion section, the quantitative findings and comprehensive explanations of the proposed method are presented in detail. Thus, this study aims to broaden the potential of the entropy method within the field of MCDM and to offer a novel perspective for decision-making processes.
Keywords : MCDM, Entropy, EBPM

ORIGINAL ARTICLE URL