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Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables

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  • Ferreira, Fernando A.F.
  • Jalali, Marjan S.
  • Ferreira, João J.M.

Abstract

This study proposes the use of fuzzy cognitive maps (FCMs) in qualitative comparative analysis (QCA) applications to enhance the selection of independent variables in the QCA framework. QCA techniques hold great potential to identify the causal models that exist among different but comparable cases. Due to the complexity of causality issues, however, such techniques may not be able to uncover the “true” causal foundation of a given phenomenon. FCMs typically offer a fuller view of the cause-and-effect relationships between variables, thus allowing for a better understanding of their behavior; for instance, the manner in which variables relate to each other, or the measure of their intensity. This study thus proposes that such maps can be a useful support in the selection of independent variables for a QCA model, and provides specific guidelines and an illustrative example of how to integrate FCMs in QCA applications.

Suggested Citation

  • Ferreira, Fernando A.F. & Jalali, Marjan S. & Ferreira, João J.M., 2016. "Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables," Journal of Business Research, Elsevier, vol. 69(4), pages 1471-1478.
    • Handle: RePEc:eee:jbrese:v:69:y:2016:i:4:p:1471-1478
    DOI: 10.1016/j.jbusres.2015.10.127
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    References listed on IDEAS

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    Cited by:

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    2. Braga, Irina F.B. & Ferreira, Fernando A.F. & Ferreira, João J.M. & Correia, Ricardo J.C. & Pereira, Leandro F. & Falcão, Pedro F., 2021. "A DEMATEL analysis of smart city determinants," Technology in Society, Elsevier, vol. 66(C).
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    4. Ferreira, João J.M. & Jalali, Marjan S. & Ferreira, Fernando A.F., 2018. "Enhancing the decision-making virtuous cycle of ethical banking practices using the Choquet integral," Journal of Business Research, Elsevier, vol. 88(C), pages 492-497.
    5. Tselykh, Alexander & Vasilev, Vladislav & Tselykh, Larisa, 2019. "Clustering method based on the elastic energy functional of directed signed weighted graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 392-407.
    6. Maria J. M. Ladeira & Fernando A. F. Ferreira & João J. M. Ferreira & Wenchang Fang & Pedro F. Falcão & Álvaro A. Rosa, 2019. "Exploring the determinants of digital entrepreneurship using fuzzy cognitive maps," International Entrepreneurship and Management Journal, Springer, vol. 15(4), pages 1077-1101, December.
    7. Kaklauskas, A. & Zavadskas, E.K. & Banaitis, A. & Meidute-Kavaliauskiene, I. & Liberman, A. & Dzitac, S. & Ubarte, I. & Binkyte, A. & Cerkauskas, J. & Kuzminske, A. & Naumcik, A., 2018. "A neuro-advertising property video recommendation system," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 78-93.
    8. Kabengele, Christian & Hahn, Rüdiger, 2021. "Institutional and firm-level factors for mobile money adoption in emerging markets–A configurational analysis," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    9. Jing Du & Hongyue Wu & Xianbo Zhao, 2018. "Critical Factors on the Capital Structure of Public–Private Partnership Projects: A Sustainability Perspective," Sustainability, MDPI, vol. 10(6), pages 1-27, June.
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