Charles Ragin's Fuzzy Set Qualitative Comparative Analysis (fsQCA) used for linguistic summarizations

Authors:
Jerry M. Mendel;Mohammad M. Korjani
Affiliations:
Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Ave., Los Angeles, CA 90089-2564, United States;Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Ave., Los Angeles, CA 90089-2564, United States
Venue:
Information Sciences: an International Journal
Year:
2012

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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 eminent social scientist Prof. Charles C. Ragin, but has, as of this date, not been applied by engineers or computer scientists. Unlike more quantitative methods that are based on correlation, fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that summarize the sufficiency between subsets of all of the possible combinations of the causal conditions (or their complements) and the outcome. The rules are connected by the word OR to the output. Each rule is a possible path from the causal conditions to the outcome. This paper, for the first time, explains fsQCA in a very quantitative way, something that is needed if engineers and computer scientists are to use fsQCA.