Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool

Detalhes bibliográficos
Autor(a) principal: Hair Jr., Joseph F.
Data de Publicação: 2014
Outros Autores: Gabriel, Marcelo Luiz Dias da Silva, Patel, Vijay K.
Tipo de documento: Artigo
Idioma: por
Título da fonte: REMark - Revista Brasileira de Marketing
Texto Completo: https://periodicos.uninove.br/remark/article/view/12031
Resumo: Structural equation modeling (SEM) is increasingly a method of choice for concept and theory development in the social sciences, particularly the marketing discipline. In marketing research there increasingly is a need to assess complex multiple latent constructs and relationships. Second-order constructs can be modeled providing an improved theoretical understanding of relationships as well as parsimony. SEM in particular is well suited to investigating complex relationships among multiple constructs. The two most prevalent SEM based analytical methods are covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM). While each technique has advantages and limitations, in this article we focus on CB-SEM with AMOS to illustrate its application in examining the relationships between customer orientation, employee orientation, and firm performance. We also demonstrate how higher-order constructs are useful in modeling both responsive and proactive components of customer and employee orientation.
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spelling Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research ToolModelagem de Equações Estruturais Baseada em Covariância (CB-SEM) com o AMOS: Orientações sobre a sua aplicação como uma Ferramenta de Pesquisa de MarketingStructural Equation Modeling (SEM); Covariance-Based SEM; AMOS; Marketing Research.Modelagem de Equações Estruturais (SEM), baseado em covariância SEM, AMOS, Pesquisa de Marketing.Structural equation modeling (SEM) is increasingly a method of choice for concept and theory development in the social sciences, particularly the marketing discipline. In marketing research there increasingly is a need to assess complex multiple latent constructs and relationships. Second-order constructs can be modeled providing an improved theoretical understanding of relationships as well as parsimony. SEM in particular is well suited to investigating complex relationships among multiple constructs. The two most prevalent SEM based analytical methods are covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM). While each technique has advantages and limitations, in this article we focus on CB-SEM with AMOS to illustrate its application in examining the relationships between customer orientation, employee orientation, and firm performance. We also demonstrate how higher-order constructs are useful in modeling both responsive and proactive components of customer and employee orientation.A modelagem de equaes estruturais (Structural Equation Modeling -SEM) cada vez mais usada como um mtodo para a conceituao e desenvolvimento de aspectos tericos nas cincias sociais aplicadas, em particular na rea de marketing, pois mais e mais h a necessidade de avaliar vrios constructos e relaes latentes complexas. Tambm, constructos de segunda ordem podem ser modelados fornecendo uma melhor compreenso terica de relaes com boa parcimnia. Modelagens do tipo SEM so, em particular, bem adequadas para investigar as relaes complexas entre os vrios constructos. Os dois mtodos analticos SEM mais prevalentes so os baseados em covarincia SEM (CB-SEM) e os baseados em varincia SEM (PLS-SEM). Embora cada tcnica tenha suas vantagens e limitaes, neste artigo vamos nos concentrar no CB-SEM com o AMOS para ilustrar sua aplicao na anlise das relaes entre orientao para o cliente, a orientao para os funcionrios e desempenho da empresa. Tambm ser demonstrado como constructos de segunda ordem so teis para modelar os componentes de pr-atividade e responsividade dessas relaes.DOI: 10.5585/remark.v13i2.2718Universidade Nove de Julho - Uninove2014-05-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado por ParesPeer-reviewed Articleapplication/pdfapplication/pdfhttps://periodicos.uninove.br/remark/article/view/1203110.5585/remark.v13i2.2718ReMark - Revista Brasileira de Marketing; v. 13, n. 2 (2014): Edição Especial; 44-552177-5184reponame:REMark - Revista Brasileira de Marketinginstname:Universidade Nove de Julho (UNINOVE)instacron:RBMporhttps://periodicos.uninove.br/remark/article/view/12031/5662https://periodicos.uninove.br/remark/article/view/12031/5663Direitos autorais 2019 Revista Brasileira de Marketing – Remarkinfo:eu-repo/semantics/openAccessHair Jr., Joseph F.Gabriel, Marcelo Luiz Dias da SilvaPatel, Vijay K.2019-02-19T17:43:54Zoai:https://periodicos.uninove.br:article/12031Revistahttps://periodicos.uninove.br/remarkPRIhttps://periodicos.uninove.br/remark/oaiclaudiaraac@uol.com.br || admin@revistabrasileiramarketing.org || admin@revistabrasileiramarketing.org2177-51842177-5184opendoar:2019-02-19T17:43:54REMark - Revista Brasileira de Marketing - Universidade Nove de Julho (UNINOVE)false
dc.title.none.fl_str_mv Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
Modelagem de Equações Estruturais Baseada em Covariância (CB-SEM) com o AMOS: Orientações sobre a sua aplicação como uma Ferramenta de Pesquisa de Marketing
title Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
spellingShingle Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
Hair Jr., Joseph F.
Structural Equation Modeling (SEM); Covariance-Based SEM; AMOS; Marketing Research.
Modelagem de Equações Estruturais (SEM), baseado em covariância SEM, AMOS, Pesquisa de Marketing.
title_short Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
title_full Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
title_fullStr Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
title_full_unstemmed Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
title_sort Amos Covariance-Based Structural Equation Modeling (Cb-Sem): Guidelines on its Application as a Marketing Research Tool
author Hair Jr., Joseph F.
author_facet Hair Jr., Joseph F.
Gabriel, Marcelo Luiz Dias da Silva
Patel, Vijay K.
author_role author
author2 Gabriel, Marcelo Luiz Dias da Silva
Patel, Vijay K.
author2_role author
author
dc.contributor.author.fl_str_mv Hair Jr., Joseph F.
Gabriel, Marcelo Luiz Dias da Silva
Patel, Vijay K.
dc.subject.por.fl_str_mv Structural Equation Modeling (SEM); Covariance-Based SEM; AMOS; Marketing Research.
Modelagem de Equações Estruturais (SEM), baseado em covariância SEM, AMOS, Pesquisa de Marketing.
topic Structural Equation Modeling (SEM); Covariance-Based SEM; AMOS; Marketing Research.
Modelagem de Equações Estruturais (SEM), baseado em covariância SEM, AMOS, Pesquisa de Marketing.
description Structural equation modeling (SEM) is increasingly a method of choice for concept and theory development in the social sciences, particularly the marketing discipline. In marketing research there increasingly is a need to assess complex multiple latent constructs and relationships. Second-order constructs can be modeled providing an improved theoretical understanding of relationships as well as parsimony. SEM in particular is well suited to investigating complex relationships among multiple constructs. The two most prevalent SEM based analytical methods are covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM). While each technique has advantages and limitations, in this article we focus on CB-SEM with AMOS to illustrate its application in examining the relationships between customer orientation, employee orientation, and firm performance. We also demonstrate how higher-order constructs are useful in modeling both responsive and proactive components of customer and employee orientation.
publishDate 2014
dc.date.none.fl_str_mv 2014-05-23
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado por Pares
Peer-reviewed Article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.uninove.br/remark/article/view/12031
10.5585/remark.v13i2.2718
url https://periodicos.uninove.br/remark/article/view/12031
identifier_str_mv 10.5585/remark.v13i2.2718
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.uninove.br/remark/article/view/12031/5662
https://periodicos.uninove.br/remark/article/view/12031/5663
dc.rights.driver.fl_str_mv Direitos autorais 2019 Revista Brasileira de Marketing – Remark
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Direitos autorais 2019 Revista Brasileira de Marketing – Remark
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Nove de Julho - Uninove
publisher.none.fl_str_mv Universidade Nove de Julho - Uninove
dc.source.none.fl_str_mv ReMark - Revista Brasileira de Marketing; v. 13, n. 2 (2014): Edição Especial; 44-55
2177-5184
reponame:REMark - Revista Brasileira de Marketing
instname:Universidade Nove de Julho (UNINOVE)
instacron:RBM
instname_str Universidade Nove de Julho (UNINOVE)
instacron_str RBM
institution RBM
reponame_str REMark - Revista Brasileira de Marketing
collection REMark - Revista Brasileira de Marketing
repository.name.fl_str_mv REMark - Revista Brasileira de Marketing - Universidade Nove de Julho (UNINOVE)
repository.mail.fl_str_mv claudiaraac@uol.com.br || admin@revistabrasileiramarketing.org || admin@revistabrasileiramarketing.org
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