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

Alkan, Nursah; Kahraman, Cengiz

doi:10.15388/22-INFOR493

Informatica

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

Volume 34, Issue 1 (2023), pp. 1–33

Nursah Alkan Cengiz Kahraman

https://doi.org/10.15388/22-INFOR493

Pub. online: 22 July 2022 Type: Research Article

Open Access

Received
1 February 2022

Accepted
1 July 2022

Published
22 July 2022

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.

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Biographies

Alkan Nursah

nalkan@itu.edu.tr

N. Alkan is a PhD candidate and a research assistant in the Department of Industrial Engineering at Istanbul Technical University since 2019. She received the MSc degree in Department of Industrial Engineering from Yildiz Technical University, Turkey, in 2019. Her research interests include fuzzy sets and their extensions, multi-criteria/objective decision making, and data analysis. She published some journal papers, conference papers and book chapters in mentioned areas.

Kahraman Cengiz

kahramanc@itu.edu.tr

C. Kahraman is a full professor at Istanbul Technical University. His research areas are engineering economics, quality management, statistical decision making, multicriteria decision making, and fuzzy decision making. He published about 300 international journal papers and about 200 conference papers. He became the guest editor of many international journals and the editor of many international books from Springer. He is a member of editorial boards of 20 international journals. He is the chair of INFUS International Conferences on fuzzy and intelligent systems ZS, Yager RR, some geometric aggregation operators based on intuitionistic fuzzy sets.

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digital transformation supply chain fermatean fuzzy sets MCDM AHP

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