Publication
Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations
| dc.contributor.author | Cheah, Jun-Hwa | |
| dc.contributor.author | Amaro, Suzanne | |
| dc.contributor.author | Roldán, José L. | |
| dc.date.accessioned | 2023-01-04T15:05:45Z | |
| dc.date.available | 2023-01-04T15:05:45Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | 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. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1016/j.jbusres.2022.113539 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.19/7499 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.subject | Non-parametric Permutation-Based Test | pt_PT |
| dc.subject | Partial Least Squares Structural Equation Modeling | pt_PT |
| dc.subject | Multigroup AnalysisGroup Comparison | pt_PT |
| dc.subject | Non-parametric Distance-Based Test | pt_PT |
| dc.subject | Omnibus Test Group Differences | pt_PT |
| dc.title | Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.startPage | 113539 | pt_PT |
| oaire.citation.title | Journal of Business Research | pt_PT |
| oaire.citation.volume | 156 | pt_PT |
| person.familyName | Amaro | |
| person.givenName | Suzanne | |
| person.identifier.ciencia-id | E918-24FC-5C4A | |
| person.identifier.orcid | 0000-0001-9263-6951 | |
| person.identifier.scopus-author-id | 55934788900 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 3af4cea2-a02e-46b4-8e2e-d274f9d2b3ec | |
| relation.isAuthorOfPublication.latestForDiscovery | 3af4cea2-a02e-46b4-8e2e-d274f9d2b3ec |