Evaluation of Industry 4.0 strategies for digital transformation in the automotive manufacturing industry using an integrated fuzzy decision-making model

dc.authorscopusid57194545622
dc.authorscopusid58662062600
dc.authorscopusid57221536835
dc.authorscopusid7005545253
dc.authorscopusid58203687800
dc.contributor.authorGörçün, Ömer Faruk
dc.contributor.authorMishra, Arunodaya Raj
dc.contributor.authorAytekin, Ahmet
dc.contributor.authorSimic, Vladimir
dc.contributor.authorKorucuk, Selcuk
dc.date.accessioned2024-06-23T21:38:08Z
dc.date.available2024-06-23T21:38:08Z
dc.date.issued2024
dc.departmentKadir Has Universityen_US
dc.department-temp[Gorcun, Omer Faruk] Kadir Has Univ, Fac Econ Adm & Social Sci, Dept Business Adm, Istanbul, Turkiye; [Mishra, Arunodaya Raj] Govt Coll Raigaon, Dept Math, Satna 485441, Madhya Pradesh, India; [Aytekin, Ahmet] Artvin Coruh Univ, Hopa Fac Econ & Adm Sci, Dept Business Adm, TR-08100 Hopa, Artvin, Turkiye; [Simic, Vladimir] Univ Belgrade, Fac Transport & Traff Engn, Vojvode Stepe 305, Belgrade 11010, Serbia; [Simic, Vladimir] Yuan Ze Univ, Coll Engn, Dept Ind Engn & Management, Taoyuan 320315, Taiwan; [Simic, Vladimir] Korea Univ, Coll Informat, Dept Comp Sci & Engn, Seoul 02841, South Korea; [Korucuk, Selcuk] Giresun Univ, Bulancak Kadir Karabas Vocat Sch, Dept Logist Management, Giresun, Turkiyeen_US
dc.description.abstractThe current paper proposes a methodological frame to identify the best Industry 4.0 (I4) strategy for the automotive manufacturing industry as a roadmap for companies to make a more straightforward digital transformation. We noticed a critical research gap when we performed an extensive literature review. Although there are many studies available that assess the readiness of companies for I4, only a few deal with decision -making in terms of sustainable development, and none have applied that to the automotive industry. Practitioners can apply the proposed model to determine the strategy based on technological developments in I4. The current paper proposes an extended version of the combined compromise solution approach with the help of the picture fuzzy sets. According to the paper 's results, by using the proposed model, developing a new business model based on technological improvements is the best strategy for the digital transformation of the automotive industry. Also, the lack of research and development implementations on I4 implementation is the most influential factor. Hence, practitioners in the automotive industry know the significance of research and development in reaching successful results for digital transformation. The acquired outcomes of the paper show that developing technology -based new business models is the best strategy for the automotive manufacturing industry concerning digital transformation instead of accommodating traditional business models and high technology utilization.en_US
dc.identifier.citation0
dc.identifier.doi10.1016/j.jmsy.2024.05.005
dc.identifier.endpage948en_US
dc.identifier.issn0278-6125
dc.identifier.issn1878-6642
dc.identifier.scopus2-s2.0-85193641387
dc.identifier.scopusqualityQ1
dc.identifier.startpage922en_US
dc.identifier.urihttps://doi.org/10.1016/j.jmsy.2024.05.005
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5748
dc.identifier.volume74en_US
dc.identifier.wosWOS:001244546800001
dc.identifier.wosqualityQ1
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectIndustry 4.0en_US
dc.subjectStrategyen_US
dc.subjectPicture Fuzzy Setsen_US
dc.subjectCombined Compromise Solutionen_US
dc.subjectRenyi Entropyen_US
dc.subjectPicture Fuzzy Delphien_US
dc.titleEvaluation of Industry 4.0 strategies for digital transformation in the automotive manufacturing industry using an integrated fuzzy decision-making modelen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication4d0f6004-dbe4-4e79-befd-457af3bb133f
relation.isAuthorOfPublication.latestForDiscovery4d0f6004-dbe4-4e79-befd-457af3bb133f

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