Abstract
Partial least squares path modeling (PLS-PM)is an estimator that has found widespread application for causal information systems (IS)research. Recently, the method has been subject to many improvements, such as consistent PLS (PLSc)for latent variable models, a bootstrap-based test for overall model fit, and the heterotrait-to-monotrait ratio of correlations for assessing discriminant validity. Scholars who would like to rigorously apply PLS-PM need updated guidelines for its use. This paper explains how to perform and report empirical analyses using PLS-PM including the latest enhancements, and illustrates its application with a fictive example on business value of social media.
| Original language | English |
|---|---|
| Article number | 103168 |
| Number of pages | 16 |
| Journal | Information and Management |
| Volume | 57 |
| Issue number | 2 |
| Early online date | 23 May 2019 |
| DOIs | |
| Publication status | Published - Mar 2020 |
Keywords
- Composite model
- Confirmatory and explanatory information systems research
- Guidelines
- Model validation
- Partial least squares path modeling
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Cite this
Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information and Management, 57(2), [103168]. https://doi.org/10.1016/j.im.2019.05.003