Requirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties

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dc.authorscopusidWitold Pedrycz / 58861905800
dc.authorwosidWitold Pedrycz / HJZ-2779-2023
dc.contributor.authorChang, Jian-Peng
dc.contributor.authorRen, Heng-Xin
dc.contributor.authorMartinez, Luis
dc.contributor.authorPedrycz, Witold
dc.contributor.authorChen, Zhen-Song
dc.date.accessioned2025-04-18T10:23:35Z
dc.date.available2025-04-18T10:23:35Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractSupplier selection (SS) has emerged as a critical challenge for companies aiming to enhance the operational management of their supply chains, a task that has grown in complexity with the advent of Industry 4.0 and the ongoing digital transformation. Recognizing the gaps in current literature-specifically, the lack of consideration for stakeholders' expectations in guiding SS, as well as the inadequate handling of epistemic and stochastic uncertainties-this paper introduces a multiple-criteria Quality Function Deployment (QFD)-based model for SS. To address epistemic uncertainty, we put forward a novel subjective judgment representation method, which is named as linguistic term set integrated with discrete subjective probability distribution (LTS-DSPD), to enable decision-makers to express their judgments in a manner that is both simpler and more nuanced. Furthermore, we also give the elicitation methods and computing techniques for LTS-DSPD. Then, we integrate stakeholders' requirements, along with their preferences and expectations for these requirements to inform and guide SS. To effectively operationalize this guidance, we design the QFD-based methods to transform stakeholders' inputs into the assessment criteria for SS, the weights of criteria, and the expectations for the performances of suppliers on each criterion, respectively. To address stochastic uncertainty, we have developed an innovative methodology for characterizing it, and adopt prospect theory to quantify the overall utility of alternative suppliers. The paper concludes with a case study to demonstrate its practical application and effectiveness in streamlining SS process.
dc.description.sponsorshipNational Natural Science Foundation of China (NSFC)
dc.identifier.citationChang, J. P., Ren, H. X., Martínez, L., Pedrycz, W., & Chen, Z. S. (2024). Requirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties. Annals of Operations Research, 1-50.
dc.identifier.doi10.1007/s10479-024-06131-0
dc.identifier.endpage1128
dc.identifier.issn0254-5330
dc.identifier.issn1572-9338
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85198367595
dc.identifier.scopusqualityQ1
dc.identifier.startpage1079
dc.identifier.urihttp://dx.doi.org/10.1007/s10479-024-06131-0
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7045
dc.identifier.volume342
dc.identifier.wosWOS:001270194400001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorPedrycz, Witold
dc.institutionauthoridWitold Pedrycz / 0000-0002-9335-9930
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofAnnals of operations research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectRequirement-Driven Supplier Selection
dc.subjectQuality Function Deployment (QFD)
dc.subjectEpistemic Uncertainty
dc.subjectStochastic Uncertainty
dc.subjectProspect Theory
dc.titleRequirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties
dc.title.alternativeRequirement-driven supplier selection: a multi-criteria QFD-based approach under epistemic and stochastic uncertainties
dc.typeArticle

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