Affiliation:
1. Department of Leadership and Organizational Behaviour, BI Norwegian Business School, Oslo, Norway
Abstract
Based on the INUS theory of causality, the search target of qualitative comparative analysis (QCA) is to find all the minimally sufficient conditions for the outcome’s occurrence in a data set, where the condition’s sufficiency, the necessity of the condition’s components, and the completeness of the solution are three core requirements. However, QCA’s current top-down approach, which relies on a truth table and Boolean minimization, cannot meet the main objective of QCA. Conditions generated by the top-down approach can be insufficient for the outcome or contain unnecessary components that can be removed. We found evidence supporting our arguments by examining the correctness of top-down QCA in Study 1. Then, we show that QCA can also proceed with a “bottom-up” search strategy in sufficiency analysis, similar to coincidence analysis (CNA). We contrast solutions of the top-down and bottom-up QCA approaches by analyzing a simulated crisp-set data set in Study 2 and a real-world fuzzy-set data set in Study 3. Both results show that only the bottom-up approach can produce all the minimally sufficient conditions. We contribute to the ongoing debate pertain QCA solution types and QCA algorithms by critically evaluating the limitations of QCA’s top-down approach and introducing a bottom-up approach for QCA.
Funder
BI Norwegian Business School
Cited by
2 articles.
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