Publications

Authors:

Cheah, Jun-Hwa; Magno, Francesca; Cassia, Fabio

Title:

Reviewing the SmartPLS 4 software: the latest features and enhancements

Year:

2024

Type of item:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Language:

Inglese

Referee:

No

Name of journal:

JOURNAL OF MARKETING ANALYTICS

ISSN of journal:

2050-3318

N° Volume:

12

Number or Folder:

1

Page numbers:

97-107

Keyword:

Partial least squares structural equation modeling; Partial least squares path modeling; PLS-SEM; Composite modeling; SmartPLS; Multivariate data analysis

Short description of contents:

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.

Note:

AJG 1

Web page:

https://link.springer.com/article/10.1057/s41270-023-00266-y

Product ID:

136544

Handle IRIS:

11562/1115426

Last Modified:

July 25, 2024

Bibliographic citation:

Cheah, Jun-Hwa; Magno, Francesca; Cassia, Fabio, Reviewing the SmartPLS 4 software: the latest features and enhancements «JOURNAL OF MARKETING ANALYTICS» , vol. 12 , n. 1 , 2024 , pp. 97-107

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