Fuzzy-Set Qualitative Comparative Analysis (fsQCA) in Organizational Psychology: Theoretical Overview, Research Guidelines, and A Step-By-Step Tutorial Using R Software

Abstract

Fuzzy set qualitative comparative analysis (fsQCA) is a method for assessing the effects of configurations of variables leading to an outcome. The recent growth of interest in this technique in organizational psychology is proving this method to be an important tool for addressing new and decisive research hypotheses. However, the effectiveness of fsQCA is dictated not only by its general principles, but also by how well these are understood and applied in the research community. Consequently, a guide that covers the fundamental ideas and tenets of the approach is required to aid the research community in its comprehension and practical application. The current study seeks to offer an understanding of FsQCA by providing: (a) A complete description of the method highlighting some of the most important theoretical-methodological aspects; (b) a perspective on the most used guidelines and recommendations, and (c) step-by-step instructions on how to carry out FsQCA in R using the QCA package. Data from 120 employees and supervisors derived from a company based in central Italy were used o best to illustrate how to carry out fsQCA. Codes for conducting the analyses from the QCA package for R accompany the tutorial and can be adapted to a new dataset.

Exploring the push-pull factors influencing parenting efficacy of fathers of children with ASD: a fuzzy set qualitative comparative analysis

“…In this regard, the Fuzzy-Sets Qualitative Comparison Approach (Fuzzy-Sets QCA, fsQCA) is advantageous. FsQCA is a methodology that has emerged in recent years and is now being used in many fields, including psychology and education ( 11 – 13 ). It relies on Boolean logic to realize the logical principle of comparisons between multiple samples and is a set-theoretic approach to causal analysis based on the premise that outcomes tend to be caused by more than one factor, rather than by any single factor ( 14 ).…”