An Integration of Interpretive Structural Modeling and Fuzzy Analytical Network Process for Identifying and Ranking The Factors Affecting Supply Chain Agility

Achieving agility in manufacturing requires a set of requirements in a company’s supply chain in order to support the agility in the supply chain. There are factors that can affect this agility. Therefore, identification and ranking these factors affecting supply chain agility is a strategic issue. To find a decent answer to this problem could be important in the long run and have dramatic economic consequences. Compared to other areas, a few researches have been done to identify and rank factors affecting agility in the supply chain. In current studies there is also a greater emphasis on quantitative criteria, while qualitative criteria have been less investigated. It is perhaps due to the inaccurate nature and the interaction between those qualitative factors. In this research, using fuzzy analytical network process (FANP), factors affecting supply chain agility are identified and ranked. To establish relationships between factors, interpretive structural modeling (ISM) is used. The proposed approach is applied in a case study. Results show that this approach can be helpful in achieving effective agents.