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.
Authors
- Joseph F. Hair (ORCID: https://orcid.org/0000-0002-9226-9693)
- Marko Sarstedt (ORCID: https://orcid.org/0000-0002-5424-4268)
- Barry J. Babin (ORCID: https://orcid.org/0000-0002-0393-2810)
- Christian M. Ringle (ORCID: https://orcid.org/0000-0002-7027-8804)
- Jan-Michael Becker (ORCID: https://orcid.org/0000-0003-3013-3739)
Institutions
- 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)
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