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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
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Soumis le : jeudi 21 juillet 2022 - 11:17:38
Dernière modification le : vendredi 5 août 2022 - 14:48:22
Archivage à long terme le : : samedi 22 octobre 2022 - 21:55:56

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Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale 4.0 International License

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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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