Fuzzy set Qualitative Comparative Analysis (fsQCA): Challenges and applications

Abstract

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the social scientist Prof. Charles C. Ragin. fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that describe how combinations of causal conditions would cause the desired outcome. So, each rule is a possible path from the causal conditions to the outcome. The rules are connected by the word OR to the output. To actually apply fsQCA to some engineering data problems, there are some challenges that had to be overcome. We explain the challenges and how they have been overcome. We also illustrate the application of fsQCA to the well-known Auto MPG dataset to obtain causal combinations that explain Low MPG 4-cylinder cars.