Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/12724 |
Resumo: | 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. |
id |
RCAP_3052efbdf948472aeaceaae1250c7e08 |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/12724 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variablesQualitative comparative analysisFuzzy cognitive mapsIndependent variable selectionDecision supportThis 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.Elsevier2017-04-04T11:51:48Z2016-01-01T00:00:00Z20162019-04-11T17:52:14Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/12724eng0148-296310.1016/j.jbusres.2015.10.127Ferreira, F. A. F.Jalali, M. S.Ferreira, J. J. M.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:54:42Zoai:repositorio.iscte-iul.pt:10071/12724Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:27:41.378905Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
title |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
spellingShingle |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables Ferreira, F. A. F. Qualitative comparative analysis Fuzzy cognitive maps Independent variable selection Decision support |
title_short |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
title_full |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
title_fullStr |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
title_full_unstemmed |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
title_sort |
Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables |
author |
Ferreira, F. A. F. |
author_facet |
Ferreira, F. A. F. Jalali, M. S. Ferreira, J. J. M. |
author_role |
author |
author2 |
Jalali, M. S. Ferreira, J. J. M. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ferreira, F. A. F. Jalali, M. S. Ferreira, J. J. M. |
dc.subject.por.fl_str_mv |
Qualitative comparative analysis Fuzzy cognitive maps Independent variable selection Decision support |
topic |
Qualitative comparative analysis Fuzzy cognitive maps Independent variable selection Decision support |
description |
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. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2017-04-04T11:51:48Z 2019-04-11T17:52:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/12724 |
url |
http://hdl.handle.net/10071/12724 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0148-2963 10.1016/j.jbusres.2015.10.127 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134839531634688 |