Matching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based method

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dc.contributor.authorGunduz, Mehmet Akif
dc.contributor.authorDemir, Sercan
dc.contributor.authorPaksoy, Turan
dc.date.accessioned2024-02-23T14:02:26Z
dc.date.available2024-02-23T14:02:26Z
dc.date.issued2021
dc.departmentNEÜen_US
dc.description.abstractIn recent years, there is a noticeable increase in interest in supply chain smartness and sustainability since a growing number of companies are adopting smart technologies and sustainable practices in the functions of supply chain management. Therefore, scholars and practitioners seek to make sense of how this phenomenon can be addressed concerning companies' maturity level of supply chain smartness and sustainability. This paper proposes a novel hybrid methodology combining the Best-Worst Method (BWM) and Quality Function Deployment (QFD) to assess the level of maturity for supply chain smartness and sustainability by weighting the functions of supply chain management. A twin-QFD technique is used to obtain a conceptual design to determine the relationship between the functions of supply chain smartness tools and sustainability indicators to assess the level of maturity, whereas the BWM is used to determine the weights of the functions of supply chain management. A case study in the automotive manufacturing industry is applied to demonstrate the applicability of the proposed approach. The findings disclose the prominent smart technologies (simulation, big data analytics, cloud computing) and sustainability indicators (costs, lead time, and damage and loss) in integrating Industry 4.0 technologies and sustainable supply chain practices. Findings also suggest a guideline to compare the current and targeted levels of smartness and sustainability maturity. This study provides insights for scholars and practitioners and contributes to the body of knowledge by evaluating companies' maturity of digital transformation and sustainable practices in the supply chain functions.en_US
dc.identifier.doi10.1016/j.cie.2021.107676
dc.identifier.issn0360-8352
dc.identifier.issn1879-0550
dc.identifier.scopus2-s2.0-85115421753en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.cie.2021.107676
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11713
dc.identifier.volume162en_US
dc.identifier.wosWOS:000757022700004en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofComputers & Industrial Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBest-Worst Methoden_US
dc.subjectQuality Function Deploymenten_US
dc.subjectSupply Chain Managementen_US
dc.subjectSmartnessen_US
dc.subjectSustainabilityen_US
dc.titleMatching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based methoden_US
dc.typeArticleen_US

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