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Configurational theory in business and management research: Status quo and guidelines for the application of qualitative comparative analysis (QCA)

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  • Di Paola, Nadia
  • Chari, Simos
  • Iannacci, Federico
  • Kraus, Sascha

Abstract

Qualitative Comparative Analysis (QCA) has become a key method in Business and Management research, sparking significant discussions about its use. While many studies have explored QCA's application across various research contexts, there has been limited focus on the critical link between its theoretical foundations and methodological applications. Our review of QCA literature in Business and Management research (n = 675 articles) reveals that many studies focus more on methodological aspects than configurational theorizing. Despite repeated calls for stronger theoretical integration, only a limited number of studies have successfully employed QCA in a way that aligns theoretical principles with empirical investigation. Additionally, we found a predominant use of QCA in inductive research, though a surprising number of deductive studies misuse QCA for hypothesis testing—despite its incompatibility with set-theoretic approaches. We clarify that QCA should not be employed for hypothesis testing and emphasize its proper deductive use in evaluating theory through the alignment of theoretical propositions and empirical findings. Furthermore, we provide guidelines for conducting rigorous QCA and offer a research protocol to better align theoretical foundations with methodological applications. With this, the study contributes to the field by addressing gaps in how QCA is applied and enhancing its use in configurational theorizing.

Suggested Citation

  • Di Paola, Nadia & Chari, Simos & Iannacci, Federico & Kraus, Sascha, 2025. "Configurational theory in business and management research: Status quo and guidelines for the application of qualitative comparative analysis (QCA)," Technological Forecasting and Social Change, Elsevier, vol. 211(C).
  • Handle: RePEc:eee:tefoso:v:211:y:2025:i:c:s0040162524007054
    DOI: 10.1016/j.techfore.2024.123907
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