Purpose - Partial least squares (PLS) has been introduced as a “causal-predictive” approach to structural equation modeling (SEM), designed to overcome the apparent dichotomy between explanation and prediction. However, while researchers using PLS-SEM routinely stress the predictive nature...

Purpose – Researchers often use partial least squares structural equation modeling (PLS-SEM) to estimate path models that include formatively specified constructs. Their validation requires running a redundancy analysis, which tests whether the formatively measured construct is highly...

Part I Methodology -- Chapter 1 Empirical Validation of the 10-Times Rule for SEM -- Chapter 2 Missing Values in RGCCA: Algorithms and Comparisons -- Chapter 3 Comparing Local vs Global Clustering with FIMIX-PLS. Application to Marketing -- Chapter 4 Partial Least Squares Structural Equation...

Purpose – Partial least squares (PLS) path modeling has become a pivotal empirical research method in international marketing. Owing to group comparisons’ important role in research on international marketing, we provide researchers with recommendations on how to conduct multigroup analyses...

Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity — one population and one model — but has...