Reviewing the SmartPLS 4 software: the latest features and enhancements

Jun-Hwa Cheah (Jacky) (), Francesca Magno () and Fabio Cassia ()
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Jun-Hwa Cheah (Jacky): University of East Anglia
Francesca Magno: University of Bergamo
Fabio Cassia: University of Verona

Journal of Marketing Analytics, 2024, vol. 12, issue 1, No 7, 97-107

Abstract: Abstract Partial least squares structural equation modeling (PLS-SEM) is a highly popular multivariate data analysis method. The SmartPLS 3 software program helped many marketing researchers analyze the complex relationships between latent variables (i.e., mediation, moderation, etc.), which they measured by means of sets of observed variables. This program’s intuitive graphical user interface and various features, such as new metrics (e.g., HTMT, model fit indexes), advanced techniques (multigroup analysis, PLSpredict), and complementary techniques (e.g., confirmatory tetrad analysis, importance-performance map analysis), which impacted many business disciplines. SmartPLS 4 represents a significant leap forward in development with its completely revamped graphical user interface, faster processing speed for data estimation, and new model assessment features (i.e., cross-validated predictive ability test, endogeneity assessment, and a necessary condition analysis). This paper reviews SmartPLS 4 and discusses its various features, thereby providing researchers with concrete guidance that fits their analytical research goals.

Keywords: Partial least squares structural equation modeling; Partial least squares path modeling; PLS-SEM; Composite modeling; SmartPLS; Multivariate data analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1057/s41270-023-00266-y

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