A linear programming-based QFD methodology under fuzzy environment to develop sustainable policies in apparel retailing industry

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dc.authoridDursun Delen / 0000-0001-8857-5148en_US
dc.authorscopusidDursun Delen / 55887961100en_US
dc.authorwosidDursun Delen / AGA-9892-2022en_US
dc.contributor.authorAydın, Nezir
dc.contributor.authorŞeker, Şükran
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorDing, Weiping
dc.contributor.authorDelen, Dursun
dc.date.accessioned2023-03-02T13:53:12Z
dc.date.available2023-03-02T13:53:12Z
dc.date.issued2023en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractAs the retailing industry becomes more customer oriented, it struggles with integrating the voice-of-customers into quality development policies, determining accurate customer expectations, and understanding how to incorporate the required store attributes in retailing activities. The aim of this study is to provide managers with a more decisive and sustainable framework to fulfill customer satisfaction by determining the most essential customer needs and gain a competitive advantage by applying a benchmarking process for the whole retailing activities. To essentially support managers in determining and implementing required store attributes, this study develops a sustainable linear programming (LP) based Quality Function Deployment (QFD) methodology under IVIF-environment. The proposed method determines more accurate customer expectations (CEs) and related service requirements (SRs). Accordingly, while Clothing Quality, Price Policy, and Staff Behavior are determined as the most important CEs, Design of Customer Persona, Production Cost, and Marketing Ap-plications are obtained as the most affecting SRs. Since no specific study in the literature addresses uncertainty in CEs and SRs in the apparel retailing industry, we developed an LP-based QFD under the IVIF-environment framework, which reflects the ambiguity and vagueness of the evaluations better. Thus, this study contributes to the literature by proposing a sustainable framework for managers to make decisions that are more effective and take sustainable actions. The companies who want to get the advantage in the apparel retailing industry should follow the methodology provided within this study by adding their business specific dimensions. Lastly, to represent the validity and feasibility of the proposed approach sensitivity and comparison analysis are con-ducted. The results of comparison show that the LP based QFD method is as consistent as other method but more effective in terms of handling ambiguity and fuzziness of expert evaluations, comprehensively.en_US
dc.identifier.citationAydin, N., Seker, S., Deveci, M., Ding, W., & Delen, D. (2023). A linear programming-based QFD methodology under fuzzy environment to develop sustainable policies in apparel retailing industry. Journal of Cleaner Production, 135887.en_US
dc.identifier.doi10.1016/j.jclepro.2023.135887en_US
dc.identifier.issn1879-1786en_US
dc.identifier.issn0959-6526en_US
dc.identifier.scopus2-s2.0-85149792637en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.jclepro.2023.135887
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3889
dc.identifier.volume387en_US
dc.identifier.wosWOS:000925284400001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.institutionauthorDelen, Dursun
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal of Cleaner Productionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectApparel Retailingen_US
dc.subjectCompetitive Analysisen_US
dc.subjectCustomer Servicesen_US
dc.subjectFuzzy Linear Programmingen_US
dc.subjectQFDen_US
dc.subjectIVIF Setsen_US
dc.titleA linear programming-based QFD methodology under fuzzy environment to develop sustainable policies in apparel retailing industryen_US
dc.typeArticleen_US

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