How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research - Rennes School of Business Access content directly
Journal Articles Information and Management Year : 2020

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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Dates and versions

hal-02567449 , version 1 (21-07-2022)

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Attribution - NonCommercial

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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 and Management, 2020, 57 (2), pp.103168. ⟨10.1016/j.im.2019.05.003⟩. ⟨hal-02567449⟩
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