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

Joseph F. Hair, Barry J. Babin, Christian M. Ringle (), Marko Sarstedt and Jan-Michael Becker
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Joseph F. Hair: University of South Alabama
Barry J. Babin: The University of Mississippi
Christian M. Ringle: Hamburg University of Technology
Marko Sarstedt: Ludwig-Maximilians-University Munich
Jan-Michael Becker: BI Norwegian Business School

Journal of Marketing Analytics, 2025, vol. 13, issue 3, No 9, 709-724

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.

Keywords: CB-SEM; CFA; Confirmatory factor analysis; Covariance-based structural equation modeling; SEM; SmartPLS (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41270-025-00414-6

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