A hybrid ISM and fuzzy MICMAC approach to modeling risk analysis of imported fresh food supply chain
Journal of Business & Industrial Marketing
ISSN: 0885-8624
Article publication date: 26 June 2023
Issue publication date: 13 February 2024
Abstract
Purpose
The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.
Design/methodology/approach
A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.
Findings
The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.
Research limitations/implications
The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.
Originality/value
This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.
Keywords
Acknowledgements
This research was sponsored by the Soft Science Research Funds of Science and Technology Innovation Action Plan Shanghai (Grant no. 23692107700).
Declarations of interest: None.
Citation
Hong, J., Quan, Y., Tong, X. and Lau, K.H. (2024), "A hybrid ISM and fuzzy MICMAC approach to modeling risk analysis of imported fresh food supply chain", Journal of Business & Industrial Marketing, Vol. 39 No. 2, pp. 124-141. https://doi.org/10.1108/JBIM-11-2022-0502
Publisher
:Emerald Publishing Limited
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