Two New Papers on PLS-SEM
We are happy to announce the publication of two new papers on partial least squares structural equation modeling (PLS-SEM). The first paper titled “When to use and how to report the results of PLS-SEM,” authored by Joe F. Hair (University of South Alabama), Jeffrey J. Risher (University of West Florida), Marko Sarstedt (OVGU), and Christian M. Ringle (Hamburg University of Technology Hamburg) and published in European Business Review provides a comprehensive overview of the considerations and metrics required for PLS-SEM analysis and result reporting. Besides covering established PLS-SEM evaluation criteria, the overview includes new guidelines for applying (1) PLSpredict, a novel approach for assessing a model’s out-of-sample prediction, (2) metrics for model comparisons, and (3) several complementary methods for checking the results’ robustness.
The latter topic is covered in much greater detail in the second article titled “Structural model robustness checks in PLS-SEM,” which has just been published in Tourism Economics. Authored by Marko Sarstedt (OVGU), Christian M. Ringle (Hamburg University of Technology), Jun-Hwa Cheah (Univetrsiti Putra Malaysia), Hiram Ting (UCSI University), Ovidiu I. Moisescu (Babes-Bolyai University), and Lacramioara Radomir (Babes-Bolyai University), the article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework.
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