Evaluating the Consistency Indices of Pairwise Comparisons Based on Fuzzy Evaluations

Veysel Çoban*, Cengiz Kahraman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Consistency studies are an important step in making correct evaluations in the decision-making process. Consistency is a measure value that reflects whether pairwise comparison operations are done correctly. Evaluation tools used by decision makers in pairwise comparison evaluations are of great importance in achieving consistency. Crisp scales restrict decision makers’ ability to make pairwise evaluations and also remain incapable to reflect their opinions. Fuzzy scales, which give decision makers the opportunity to make a more comfortable assessment, are used as an important tool in reflecting pairwise comparisons more accurately. The success of commonly used fuzzy evaluation scales in pairwise comparison is examined in the study. Fuzzy and crisp evaluation scales are compared using different inconsistency indices, and the most appropriate scale for pairwise comparisons is determined. The study attempts to demonstrate the help of fuzzy judgements in expressing uncertainties for pairwise comparisons. The results show that the use of fuzzy terms based on linguistic expressions in the decision-making process allows decision-makers to make a more comfortable and easy evaluation.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
EditorsCengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783030856250
Publication statusPublished - 2022
EventInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Turkey
Duration: 24 Aug 202126 Aug 2021

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Interval trapezoidal fuzzy number
  • Interval-valued Pythagorean fuzzy linguistic number
  • Pairwise comparison
  • Triangular fuzzy number


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