Prioritization of Supply Chain Digital Transformation Strategies Using Multi-Expert Fermatean Fuzzy Analytic Hierarchy Process


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Alkan N., Kahraman C.

Informatica (Slovenia), vol.34, no.1, pp.1-33, 2023 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 34 Issue: 1
  • Publication Date: 2023
  • Doi Number: 10.15388/22-infor493
  • Journal Name: Informatica (Slovenia)
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Aerospace Database, Applied Science & Technology Source, Biotechnology Research Abstracts, Central & Eastern European Academic Source (CEEAS), Communication Abstracts, Compendex, Computer & Applied Sciences, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.1-33
  • Keywords: AHP, digital transformation, fermatean fuzzy sets, MCDM, supply chain
  • Istanbul Technical University Affiliated: Yes

Abstract

Innovations in technology emerged with digitalization affect all sectors, including supply chain and logistics. The term “digital supply chain” has arisen as a relatively new concept in the manufacturing and service sectors. Organizations planning to utilize the benefits of digitalization, especially in the supply chain area, have uncertainties on how to adapt digitalization, which criteria they will evaluate, what kind of strategies should be developed, and which should be given more importance. Multi-criteria decision making (MCDM) approaches can be addressed to determine the best strategy under various criteria in digital transformation. Because of the need to capture this uncertainty, fermatean fuzzy sets (FFSs) have been preferred in the study to widen the definition domain of uncertainty parameters. Interval-valued fermatean fuzzy sets (IVFFSs) are one of the most often used fuzzy set extensions to cope with uncertainty. Therefore, a new interval-valued fermatean fuzzy analytic hierarchy process (IVFF-AHP) method has been developed. After determining the main criteria and sub-criteria, the IVFF-AHP method has been used for calculating the criteria weights and ranking the alternatives. By determining the most important strategy and criteria, the study provides a comprehensive framework of digital transformation in the supply chain.