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...

Structural equation modeling (SEM) has become a mainstream method in many fields of business research, but its use in family business research remains in its infancy. This lag in SEM's application holds especially true for partial least squares SEM (PLS-SEM), an alternative to covariance-based...

Applications of the partial least squares (PLS) path modeling approach — which have gained increasing dissemination in business research — usually build on the assumption that the data stem from a single population. However, in empirical applications, this assumption of homogeneity is...