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Modeling supply chain resilience drivers in the context of COVID-19 in manufacturing industries: leveraging the advantages of approximate fuzzy DEMATEL.

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Title: Modeling supply chain resilience drivers in the context of COVID-19 in manufacturing industries: leveraging the advantages of approximate fuzzy DEMATEL.
Authors: Sarker, Md. Rayhan1,2, md.sarkerdu.rayhan@gmail.com, Rahman, Md. Sazid3, sazidrahmanipe@gmail.com, Ali, Syed Mithun1, syed.mithun@gmail.com, Hossain, Niamat Ullah Ibne4, nibnehossain@astate.edu, Gonzalez, Ernesto D. R. Santibanez5, santibanez.ernesto@gmail.com
Source: Journal of Intelligent Manufacturing; Jun2025, Vol. 36 Issue 5, p2939-2958, 20p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 185281387
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Modeling supply chain resilience drivers in the context of COVID-19 in manufacturing industries: leveraging the advantages of approximate fuzzy DEMATEL.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=185281387
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        Value: 10.1007/s10845-023-02181-6
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      – Code: eng
        Text: English
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        PageCount: 20
        StartPage: 2939
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      – TitleFull: Modeling supply chain resilience drivers in the context of COVID-19 in manufacturing industries: leveraging the advantages of approximate fuzzy DEMATEL.
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            NameFull: Hossain, Niamat Ullah Ibne
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            NameFull: Gonzalez, Ernesto D. R. Santibanez
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            – D: 01
              M: 06
              Text: Jun2025
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              Y: 2025
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