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dc.contributor.authorDaniel, Jay
dc.contributor.authorNaderpour, Mohsen
dc.contributor.authorLin, Chin-Teng
dc.date.accessioned2018-10-12T14:22:22Z
dc.date.available2018-10-12T14:22:22Z
dc.date.issued2018-10-04
dc.identifier.citationDaniel, J., Naderpour, M. and Lin, C. (2018) 'A fuzzy multi-layer assessment method for EFQM', IEEE Transactions on Fuzzy Systems. DOI:10.1109/TFUZZ.2018.2874019en
dc.identifier.issn1063-6706
dc.identifier.doi10.1109/TFUZZ.2018.2874019
dc.identifier.urihttp://hdl.handle.net/10545/623035
dc.description.abstractAlthough the European Foundation for Quality Management (EFQM) is one of the best-known business excellence frameworks, its inherent self-assessment approaches have several limitations. A critical review of self-assessment models reveals that most models are ambiguous and limited to precise data. In addition, the impact of expert knowledge on scoring is overly subjective, and most methodologies assume the relationships between variables are linear. This paper presents a new fuzzy multi-layer assessment method that relies on fuzzy inference systems (FISs) to accommodate imprecise data and varying assessor experiences to overcome uncertainty and complexity in the EFQM model. The method was implemented, tested, and verified under real conditions in a regional electricity company. The case was assessed by internal company experts and external assessors from an EFQM business excellence organization, and the model was implemented using Matlab software. When comparing the classical model with the new model, assessors and experts favored outputs from the new model.
dc.description.sponsorshipN/Aen
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttps://ieeexplore.ieee.org/document/8481412/en
dc.rightsArchived with thanks to IEEE Transactions on Fuzzy Systemsen
dc.subjectBusiness excellence modelsen
dc.subjectEFQMen
dc.subjectFuzzy inference systemsen
dc.subjectSelf-assessmenten
dc.titleA fuzzy multi-layer assessment method for EFQM.en
dc.typeArticleen
dc.identifier.eissn1941-0034
dc.contributor.departmentUniversity of Derbyen
dc.contributor.departmentUniversity of Technology Sydneyen
dc.identifier.journalIEEE Transactions on Fuzzy Systemsen
dc.internal.reviewer-note06/10/2018 SER available oline but not vol or issue yet.en
dcterms.dateAccepted2018-09-26
refterms.dateFOA2019-02-28T17:36:36Z
html.description.abstractAlthough the European Foundation for Quality Management (EFQM) is one of the best-known business excellence frameworks, its inherent self-assessment approaches have several limitations. A critical review of self-assessment models reveals that most models are ambiguous and limited to precise data. In addition, the impact of expert knowledge on scoring is overly subjective, and most methodologies assume the relationships between variables are linear. This paper presents a new fuzzy multi-layer assessment method that relies on fuzzy inference systems (FISs) to accommodate imprecise data and varying assessor experiences to overcome uncertainty and complexity in the EFQM model. The method was implemented, tested, and verified under real conditions in a regional electricity company. The case was assessed by internal company experts and external assessors from an EFQM business excellence organization, and the model was implemented using Matlab software. When comparing the classical model with the new model, assessors and experts favored outputs from the new model.


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