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Ferreira, F., Jalali, M. & Ferreira, J. (2015). Integrating Qualitative Comparative Analysis (QCA) and Fuzzy Cognitive Maps (FCM) to Enhance the Selection of Independent Variables. 2015 GIKA International Conference.

F. A. Ferreira et al.,  "Integrating Qualitative Comparative Analysis (QCA) and Fuzzy Cognitive Maps (FCM) to Enhance the Selection of Independent Variables", in 2015 GIKA Int. Conf., Valência, 2015

@misc{ferreira2015_1732200657305,
	author = "Ferreira, F. and Jalali, M. and Ferreira, J.",
	title = "Integrating Qualitative Comparative Analysis (QCA) and Fuzzy Cognitive Maps (FCM) to Enhance the Selection of Independent Variables",
	year = "2015",
	howpublished = "Ambos (impresso e digital)",
	url = "http://www.uv.es/gika/"
}

TY  - CPAPER
TI  - Integrating Qualitative Comparative Analysis (QCA) and Fuzzy Cognitive Maps (FCM) to Enhance the Selection of Independent Variables
T2  - 2015 GIKA International Conference
AU  - Ferreira, F.
AU  - Jalali, M.
AU  - Ferreira, J.
PY  - 2015
CY  - Valência
UR  - http://www.uv.es/gika/
AB  - This study proposes the integrated 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 are often used 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, on the other hand, 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.
ER  -