Smartpls Control Variable4/17/2021
Copyright 2020 Elsevier B.V. or its licensors or contributors.Prior PLS guidelines have not covered the entire recent developments.
Smartpls Control Variable How To Perform AndWe explain how to perform and report an up-to-date empirical analysis with PLS. ![]() 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. ![]() Jose also holds the COVIRAN-Prodware Chair of Digital Human Resource Strategy at the University of Granada, Spain. His research interests cover the study of how the firms portfolio of IT capabilities affects organizational capabilities and firm performance, and the development of PLS-PM in the field of IS. His research has been published in top IS journals such as MIS Quarterly, Information Management, European Journal of Information Systems, Journal of Information Technology, and Journal of Business Research. He currently serves as Associate Editor for Information Management, European Journal of Information Systems, and Decision Support Systems, and as Guest Editor for Decision Sciences. He is also a member of the Editorial Review Board of the Journal of the Association for Information Systems. Jose obtained a PhD in Business Administration (with concentration in IS) from the University of Granada, Spain. His broad-ranging research interests encompass empirical methods of Marketing and Design research as well as the management of design, products, services, and brands. His work has been published in Computational Statistics and Data Analysis, European Journal of Information Systems, International Journal of Research in Marketing, Journal of the Academy of Marketing Science, Journal of Supply Chain Management, MIS Quarterly, Organizational Research Methods, and Structural Equation Modeling-An Interdisciplinary Journal, among others. In her doctoral dissertation, she examines how firms leverage social media capabilities to pursue knowledge management and innovation activities. She holds a masters degree in Management from the University of Granada. ![]() Florian Schuberth obtained his PhD in Econometrics in the Faculty of Business Management and Economics at the University of Wuerzburg, Germany. Currently, he is Assistant Professor in the Faculty of Engineering Technology at the University of Twente, the Netherlands. His main research interests are focused on SEM, in particular on composite-based estimators and their enhancement. Published by Elsevier B.V. Recommended articles No articles found. Citing articles Article Metrics View article metrics About ScienceDirect Remote access Shopping cart Advertise Contact and support Terms and conditions Privacy policy We use cookies to help provide and enhance our service and tailor content and ads. Copyright 2020 Elsevier B.V.
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