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Intuitionistic Fuzzy Cognitive Map Based Analysis of Supply Chain Risks
Gülçin Büyüközkan, Celal Alpay Havle, Orhan Feyzioğlu

Intuitionistic Fuzzy Cognitive Map Based Analysis of Supply Chain Risks

Science & Mathematics Published 2021 Verification Pending

Overview & Synopsis

Supply chains (SCs) are network-like structures and gigantic systems. Such systems are complex and multifaceted. Therefore, they contain many components and risk factors that are directly or indirectly related to each other. The importance of SCs, which has always been important for companies, is increasing day by day. Therefore, it is vital to focus on supply chain management (SCM) and the risk factors encountered in this management process. Plus, the investigation of the cause-effect relationships, evaluation, and analysis of these factors hold a critical role for SCM. Accordingly, this study aims to reveal the risk factors that should be considered in SCM and analyze these factors. Moreover, the causal relationships of these risk factors are aimed to be revealed. For this purpose, Cognitive Map (CM) approach is utilized. The classical CM approach is expanded to the intuitionistic fuzzy (IF) environment and used as the IFCM approach to eliminate the uncertainty and intuition involved in real-life problems and decision-making processes. SC risk factors’ importance degrees and causal relations between the factors are displayed and visualized.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Intuitionistic Fuzzy Cognitive Map Based Analysis of Supply Chain Risks
Author / Organization Gülçin Büyüközkan, Celal Alpay Havle, Orhan Feyzioğlu
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2021
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-179831
Original Source Link Visit Source Page on hal.science »