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The Usage of Fuzzy MCDM Methods for Empowering Human-Centric Digital Transformation: A Bibliometric Analysis

dc.contributor.authorOnar, Sezi Cevik
dc.contributor.authorKahraman, Cengiz
dc.contributor.authorCebi, Selcuk
dc.contributor.authorOztaysi, Basar
dc.date.accessioned2026-06-27T15:32:53Z
dc.date.issued2025
dc.description.abstractIn this study, a bibliometric analysis of the use of fuzzy multi-criteria decision-making (MCDM) methods in human-centric digital transformation is conducted. In order to support responsible technological transformation with values like sustainability, transparency, and fairness, a systematic decision-making framework is necessary. The fuzzy MCDM techniques offer effective tools since they are able to deal with uncertainty and human judgement in complex decisionmaking problems. In this study we analyzed the usage areas of these methods in the literature by using Scopus database. The results indicate a growing interest in this field. Fuzzy AHP, TOPSIS, and DEMATEL are the most frequently applied methods, often used with extensions of fuzzy sets. Human centricity and sustainability concepts are often considered together.en
dc.description.urihttps://doi.org/10.1007/978-3-031-97985-9_93
dc.identifier.doi10.1007/978-3-031-97985-9_93
dc.identifier.eissn2367-3389
dc.identifier.endpage845
dc.identifier.isbn978-3-031-97984-2; 978-3-031-97985-9
dc.identifier.issn2367-3370
dc.identifier.startpage839
dc.identifier.urihttps://hdl.handle.net/20.500.14981/71801
dc.identifier.volume1528
dc.identifier.wos001587459200093
dc.language.isoeng
dc.publisherSPRINGER INTERNATIONAL PUBLISHING AG
dc.relation.conference2025 International Conference on Intelligent and Fuzzy Systems-INFUS-Annual
dc.relation.ispartofINTELLIGENT AND FUZZY SYSTEMS, INFUS 2025, VOL 1
dc.subjectFuzzy AHP
dc.subjectFuzzy TOPSIS
dc.subjectFuzzy DEMATEL
dc.subjectFuzzy MCDM
dc.subjectHuman Centric
dc.subjectLiterature Review
dc.subjectINDUSTRY
dc.subjectComputer Science
dc.titleThe Usage of Fuzzy MCDM Methods for Empowering Human-Centric Digital Transformation: A Bibliometric Analysis
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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