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  4. Covariance-based structural equation modeling (CB-SEM): a SmartPLS 4 software tutorial
 
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Covariance-based structural equation modeling (CB-SEM): a SmartPLS 4 software tutorial

Citation Link: https://doi.org/10.15480/882.16174
Publikationstyp
Journal Article
Date Issued
2025-06-07
Sprache
English
Author(s)
Hair, Joseph F.  
Babin, Barry J.  
Ringle, Christian M.  orcid-logo
Management und Entscheidungswissenschaften W-9  
Sarstedt, Marko  
Becker, Jan-Michael  
TORE-DOI
10.15480/882.16174
TORE-URI
https://hdl.handle.net/11420/58851
Journal
Journal of marketing analytics  
Volume
13
Issue
3
Start Page
709
End Page
724
Citation
Journal of Marketing Analytics 13 (3): 709–724 (2025)
Publisher DOI
10.1057/s41270-025-00414-6
Publisher
Springer Science and Business Media LLC
Covariance-based structural equation modeling (CB-SEM) enables researchers to estimate models with hypothesized cause-effect relationships between latent variables (i.e., constructs), each of which is operationalized by several items (i.e., indicators). To conduct CB-SEM analyses, researchers can rely on a range of software applications. However, many of these applications require researchers to engage in sometimes complicated and error-prone programming tasks. While IBM SPSS AMOS provides a graphical user interface (GUI), it does not fully meet the expectations of contemporary software. In order to address these challenges, the statistical SmartPLS 4 software has recently introduced a new CB-SEM module, which improves the user experience through a modern and intuitive graphical interface and comprehensive result reports. This tutorial describes the key CB-SEM analysis steps (i.e., model setup, estimation, and results evaluation) using the SmartPLS software.
Subjects
CB-SEM
CFA
Confirmatory factor analysis
Covariance-based structural equation modeling
SEM
SmartPLS
DDC Class
300: Social Sciences
510: Mathematics
Funding(s)
Projekt DEAL  
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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Format

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