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How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research

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.
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https://hal-rennes-sb.archives-ouvertes.fr/hal-02567449
Contributor : Steven Gouin <>
Submitted on : Thursday, May 7, 2020 - 6:42:13 PM
Last modification on : Thursday, June 4, 2020 - 6:26:03 PM

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Jose Benitez, Jörg Henseler, Ana Castillo, Florian Schuberth. How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 2020, 57 (2), pp.103168. ⟨10.1016/j.im.2019.05.003⟩. ⟨hal-02567449⟩

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