Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations

Detalhes bibliográficos
Autor(a) principal: Cheah, Jun-Hwa
Data de Publicação: 2023
Outros Autores: Amaro, Suzanne, Roldán, José L.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.19/7499
Resumo: Multigroup analysis (MGA) in partial least squares structural equation modeling (PLS-SEM) has grown considerably in the past few years in many different research fields, particularly in the business area. However, a close examination of MGA in PLS-SEM articles revealed much less research that compared more than two groups. Furthermore, research applying MGA in PLS-SEM with more than two groups has several constraints. For instance, most researchers need clarification about using either the omnibus test of group differences (OTG) or non-parametric distance-based tests (NDT) for an overall difference across the groups. Moreover, they do not handle family-wise error when comparing more than two groups, nor do they check for measurement invariance. This article uses an empirical illustration to fully understand multigroup analysis with more than two groups, providing valuable guidelines and comprehensible recommendations for researchers applying PLS-MGA.
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spelling Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendationsNon-parametric Permutation-Based TestPartial Least Squares Structural Equation ModelingMultigroup AnalysisGroup ComparisonNon-parametric Distance-Based TestOmnibus Test Group DifferencesMultigroup analysis (MGA) in partial least squares structural equation modeling (PLS-SEM) has grown considerably in the past few years in many different research fields, particularly in the business area. However, a close examination of MGA in PLS-SEM articles revealed much less research that compared more than two groups. Furthermore, research applying MGA in PLS-SEM with more than two groups has several constraints. For instance, most researchers need clarification about using either the omnibus test of group differences (OTG) or non-parametric distance-based tests (NDT) for an overall difference across the groups. Moreover, they do not handle family-wise error when comparing more than two groups, nor do they check for measurement invariance. This article uses an empirical illustration to fully understand multigroup analysis with more than two groups, providing valuable guidelines and comprehensible recommendations for researchers applying PLS-MGA.Repositório Científico do Instituto Politécnico de ViseuCheah, Jun-HwaAmaro, SuzanneRoldán, José L.2023-01-04T15:05:45Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.19/7499eng10.1016/j.jbusres.2022.113539info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-01-16T15:29:38Zoai:repositorio.ipv.pt:10400.19/7499Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:45:13.793690Repositório 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 Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
title Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
spellingShingle Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
Cheah, Jun-Hwa
Non-parametric Permutation-Based Test
Partial Least Squares Structural Equation Modeling
Multigroup AnalysisGroup Comparison
Non-parametric Distance-Based Test
Omnibus Test Group Differences
title_short Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
title_full Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
title_fullStr Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
title_full_unstemmed Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
title_sort Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
author Cheah, Jun-Hwa
author_facet Cheah, Jun-Hwa
Amaro, Suzanne
Roldán, José L.
author_role author
author2 Amaro, Suzanne
Roldán, José L.
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico de Viseu
dc.contributor.author.fl_str_mv Cheah, Jun-Hwa
Amaro, Suzanne
Roldán, José L.
dc.subject.por.fl_str_mv Non-parametric Permutation-Based Test
Partial Least Squares Structural Equation Modeling
Multigroup AnalysisGroup Comparison
Non-parametric Distance-Based Test
Omnibus Test Group Differences
topic Non-parametric Permutation-Based Test
Partial Least Squares Structural Equation Modeling
Multigroup AnalysisGroup Comparison
Non-parametric Distance-Based Test
Omnibus Test Group Differences
description Multigroup analysis (MGA) in partial least squares structural equation modeling (PLS-SEM) has grown considerably in the past few years in many different research fields, particularly in the business area. However, a close examination of MGA in PLS-SEM articles revealed much less research that compared more than two groups. Furthermore, research applying MGA in PLS-SEM with more than two groups has several constraints. For instance, most researchers need clarification about using either the omnibus test of group differences (OTG) or non-parametric distance-based tests (NDT) for an overall difference across the groups. Moreover, they do not handle family-wise error when comparing more than two groups, nor do they check for measurement invariance. This article uses an empirical illustration to fully understand multigroup analysis with more than two groups, providing valuable guidelines and comprehensible recommendations for researchers applying PLS-MGA.
publishDate 2023
dc.date.none.fl_str_mv 2023-01-04T15:05:45Z
2023
2023-01-01T00:00:00Z
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.19/7499
url http://hdl.handle.net/10400.19/7499
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.jbusres.2022.113539
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dc.format.none.fl_str_mv application/pdf
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