View article

Fuzzy set Qualitative Comparative Analysis (fsQCA) can help researchers to address causal complexity, especially in relation to the interactions between different conditions leading to the outcome in question. FsQCA helps investigate how alternative solutions (different configurations of conditions) make up the outcome, and considers the asymmetrical nature of social phenomena. An important challenge that researchers often face when they apply fsQCA to qualitative data is the lack of distinct and operationalizable anchor points for fuzzy set calibration. This study offers the Generic Membership Evaluation Template (GMET) to support the decision making about assigning fuzzy set values to conditions, and therefore improves the transparency of the qualitative calibration process. This paper aims to highlight why and how fsQCA can be carried out to obtain a more in-depth understanding of complex problems using …