MAZUREK, Jiří and Pedro LINARES. Some notes on non-reciprocal matrices in the multiplicative pairwise comparisons framework. Journal of the Operational Research Society. 2023, neuvedeno, neuvedeno, p. 1-13. ISSN 0160-5682.
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Basic information
Original name Some notes on non-reciprocal matrices in the multiplicative pairwise comparisons framework
Authors MAZUREK, Jiří (203 Czech Republic, guarantor, belonging to the institution) and Pedro LINARES (724 Spain).
Edition Journal of the Operational Research Society, 2023, 0160-5682.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/47813059:19520/23:A0000370
Organization unit School of Business Administration in Karvina
UT WoS 001019850500001
Keywords in English pairwise comparisons; multiple-criteria decision making; reciprocity; consistency
Tags International impact, Reviewed
Links GA21-03085S, research and development project.
Changed by Changed by: Miroslava Snopková, učo 43819. Changed: 2/4/2024 08:10.
Abstract
In most pairwise comparisons methods such as the Analytic Hierarchy Process (AHP) it is assumed that pairwise comparisons are reciprocal, since this is a necessary condition for consistent judgments. However, several empirical studies have shown that the condition of reciprocity is not satisfied when dealing with real human preferences, which might be significantly non-reciprocal due to inherent cognitive biases. This empirical evidence indicates that the study of non-reciprocal pairwise comparisons matrices should not be neglected when dealing with real decision-making processes. However, the literature on this topic is scarce and fragmented. The aim of our study is to fill this gap by discussing advantages and disadvantages of using non-reciprocal judgements multiplicative pairwise comparisons (MPCs), reviewing existing literature and introducing a new measure of non-reciprocity with some natural and desirable properties. In addition, we perform Monte Carlo simulations on randomly generated non-reciprocal MPC matrices and provide percentile tables allowing decision makers to decide whether a level of non-reciprocity of a given MPC matrix is acceptable or not.
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