Supply Chain Risk Gap Analysis using the Modified Two-Tuple Fuzzy Linguistic Computing (FLC) Model and Fuzzy Vicor (Case Study: the SHIFOO Food Industry in Fars Province)

Document Type : Original Article

Authors

1 Assistant Professor, Hormozgan University.

2 M.Sc., Fars Science and Research Unit, Islamic Azad University.

Abstract

In the last few years, as the complexity increases, so does the level of uncertainty; Therefore, supply chain risk management is one of the topics that has been considered by organizations. One of the risks existing in the supply chain is the risk of suppliers. This research provides a model for evaluating supply chain risk management, with a focus on a real-world case: SHIFOO food industry. The model used is a combination of Fuzzy Linguistic Computing (FLC) to calculate the risk of factors in accordance with the verbal semantic spectrum, and the VIKOR method to measure the level of importance of these factors. By reviewing the studies and also using the opinions of experts, 5 factors of available capacity, lack of trust to the company, lack of skilled staff and distance between the supplier and organization were identified as factors affecting risk creation in the supply chain. Then, by using the modified two-tuple FLC (Fuzzy Linguistic Computing) model, the food supply chain risk of SHIFOO was obtained between "low" and "medium" options. Finally, by using the supply chain risk gap analysis technique, it was found that inability of supplier for provide a certain number of raw materials has importance risk among other criteria. 

Keywords

Main Subjects

References

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