{"title":"Divide and conquer? A combination of judgments method for comparing DSSs. Pairwise comparison vs. holistic paradigms","authors":"Carlos Sáenz-Royo , Francisco Chiclana","doi":"10.1016/j.inffus.2025.103157","DOIUrl":null,"url":null,"abstract":"<div><div>Despite the prevalence of Decision Support Systems (DSSs) in the field of decision-making, there is a paucity of research dedicated to the evaluation and comparison of these systems. This paper put forward a novel approach to symbolically encoding a DSS, which enables the generalization of comparisons between DSSs for any distribution of performances of the alternatives. The only hypothesis required in the proposed methodology is that the probability of choosing each alternative is proportional to its latent performance. The approach developed is demonstrated with its application to compare two paradigms commonly employed in DSS: holistic versus pairwise. Using a set of three alternatives, the present study provides mathematical proof that a DSS based on the pairwise comparison paradigm achieves higher expected performance than a DSS based on the holistic evaluation paradigm. This result challenges the emerging preference for holistic evaluation of alternatives and suggests that this result may apply to any number of alternatives.</div></div>","PeriodicalId":50367,"journal":{"name":"Information Fusion","volume":"121 ","pages":"Article 103157"},"PeriodicalIF":14.7000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Fusion","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1566253525002301","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Despite the prevalence of Decision Support Systems (DSSs) in the field of decision-making, there is a paucity of research dedicated to the evaluation and comparison of these systems. This paper put forward a novel approach to symbolically encoding a DSS, which enables the generalization of comparisons between DSSs for any distribution of performances of the alternatives. The only hypothesis required in the proposed methodology is that the probability of choosing each alternative is proportional to its latent performance. The approach developed is demonstrated with its application to compare two paradigms commonly employed in DSS: holistic versus pairwise. Using a set of three alternatives, the present study provides mathematical proof that a DSS based on the pairwise comparison paradigm achieves higher expected performance than a DSS based on the holistic evaluation paradigm. This result challenges the emerging preference for holistic evaluation of alternatives and suggests that this result may apply to any number of alternatives.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.