A new fuzzy linguistic approach to qualitative cross impact analysis

Abstract

Scenario Planning helps explore how the possible futures may look like and establishing plans to deal with them, something essential for any company, institution or country that wants to be competitive in this globalize world. In this context, Cross Impact Analysis is one of the most used methods to study the possible futures or scenarios by identifying the system's variables and the role they play in it. In this paper, we focus on the method called MICMAC (Impact Matrix Cross-Reference Multiplication Applied to a Classification), for which we propose a new version based on Computing with Words techniques and fuzzy sets, namely Fuzzy Linguistic MICMAC (FLMICMAC). The new method allows linguistic assessment of the mutual influence between variables, captures and handles the vagueness of these assessments, expresses the results linguistically, provides information in absolute terms and incorporates two new ways to visualize the results. Our proposal has been applied to a real case study and the results have been compared to the original MICMAC, showing the superiority of FLMICMAC as it gives more robust, accurate, complete and easier to interpret information, which can be very useful for a better understanding of the system.