Estimating Moterating effects in PLS-SEM andPLSc-SEM: interaction term gerneration* data treatment

JM Becker, CM Ringle…�- Journal of Applied�…, 2018 - epub.ub.uni-muenchen.de
Journal of Applied Structural Equation Modeling, 2018epub.ub.uni-muenchen.de
When estimating moderating effects in partial least squares structural equation modeling
(PLS-SEM), researchers can choose from a variety of approaches to model the influence of
a moderator on a relationship between two constructs by generating different interaction
terms. While prior research has evaluated the efficacy of these approaches in the context of
PLS-SEM, the impact of different data treatment options on their performance in the context
of standard PLS-SEM and consistent PLS-SEM (PLSc-SEM) is as yet unexplored. Our�…
Abstract
When estimating moderating effects in partial least squares structural equation modeling (PLS-SEM), researchers can choose from a variety of approaches to model the influence of a moderator on a relationship between two constructs by generating different interaction terms. While prior research has evaluated the efficacy of these approaches in the context of PLS-SEM, the impact of different data treatment options on their performance in the context of standard PLS-SEM and consistent PLS-SEM (PLSc-SEM) is as yet unexplored. Our simulation study addresses these limitations and explores if the choice of approach and data treatment option has a pronounced impact on the methods’ parameter recovery. An empirical application substantiates these findings. Based on our results, we offer recommendations for researchers wishing to estimate moderating effects by means of PLS-SEM and PLSc-SEM.
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