Version 1
: Received: 25 November 2023 / Approved: 27 November 2023 / Online: 27 November 2023 (11:27:51 CET)
How to cite:
Pereira, O.F.D.M.; Ravena, N. A Analysis Using R of the Methodology of Qualitative Comparative Analysis. Preprints2023, 2023111698. https://doi.org/10.20944/preprints202311.1698.v1
Pereira, O.F.D.M.; Ravena, N. A Analysis Using R of the Methodology of Qualitative Comparative Analysis. Preprints 2023, 2023111698. https://doi.org/10.20944/preprints202311.1698.v1
Pereira, O.F.D.M.; Ravena, N. A Analysis Using R of the Methodology of Qualitative Comparative Analysis. Preprints2023, 2023111698. https://doi.org/10.20944/preprints202311.1698.v1
APA Style
Pereira, O.F.D.M., & Ravena, N. (2023). A Analysis Using R of the Methodology of Qualitative Comparative Analysis. Preprints. https://doi.org/10.20944/preprints202311.1698.v1
Chicago/Turabian Style
Pereira, O.F.D.M. and Nirvia Ravena. 2023 "A Analysis Using R of the Methodology of Qualitative Comparative Analysis" Preprints. https://doi.org/10.20944/preprints202311.1698.v1
Abstract
The article explores Qualitative Comparative Analysis (QCA), an approach for establishing causal relationships between conditions and outcomes. QCA, applied in case studies and empirical analyses, facilitates generalizations for future research and addresses causal complexity by identifying various causal "recipes" leading to the same outcome. Three widely used QCA variants are Crisp-Set QCA (csQCA), Multi-value QCA (mvQCA), and Fuzzy-Set QCA (fsQCA), each with unique approaches. The article emphasizes the significance of bibliometric analysis in mapping a research field's intellectual structure, revealing key contributions and trends. In QCA, bibliometric analysis identifies leading researchers, affiliations, and influential countries. Results show QCA's widespread adoption across disciplines, with continuous growth in article production since 2013. The favored variant is fsQCA, followed by csQCA, and China notably contributes to QCA-related research. In conclusion, QCA proves a potent tool for discerning complex causal relationships in empirical studies, with its increasing interdisciplinary use indicating substantial potential for advancing scientific knowledge.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
