Covariance-based structural equation modeling (CB-SEM): a SmartPLS 4 software tutorial - Joseph F. Hair; Barry J. Babin; Christian M. Ringle; Marko Sarstedt; Jan-Michael Becker (Journal of Marketing Analytics, 2025)
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: 650; CB-SEM; CFA; Confirmatory factor analysis; Covariance-based structural equation modeling; SEM; SmartPLS