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

Abstract 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.

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Publication Details

Journal
Journal of Marketing Analytics
Published
2025-06-07
DOI
https://doi.org/10.1057/s41270-025-00414-6
Citations
48
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
200.11
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article

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

Joseph F. Hair, Marko Sarstedt, Barry J. Babin, Christian M. Ringle et al.
48 citations
Journal of Marketing Analytics
Technology Adoption and User Behaviour
200.11
article

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

Joseph F. Hair, Marko Sarstedt, Barry J. Babin, Christian M. Ringle, Jan-Michael Becker
article en
48 citations

Abstract

Abstract 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.

Journal of Marketing AnalyticsVol. 13(3)
Universität Hamburg (DE), Mitchell College (US), BI Norwegian Business School (NO), Babeș-Bolyai University (RO), University of Mississippi (US), Munich Business School (DE), Ludwig-Maximilians-Universität München (DE), University of South Alabama (US), James Cook University (AU), Hamburg University of Technology (DE)
Openalex Percentile: Top 0%
Technology Adoption and User Behaviour
200.11
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