Purpose This paper aims to critically comment Rossiter’s “How to use C-OAR-SE to design optimal standard measures” in the current issue of EJM and provides a broader perspective on Rossiter’s C-OAR-SE framework and measurement practice in marketing in general. Design/methodology/approach...

In the social science disciplines, the assumption that the data stem from a single homogeneous population is often unrealistic in respect of empirical research. When applying a causal modeling approach, such as partial least squares path modeling, segmentation is a key issue in coping with the...

Partial least squares structural equation modeling (PLS‐SEM) is an essential element of marketing researchers' methodological toolbox. During the last decade, the PLS‐SEM field has undergone massive developments, raising the question of whether the method's users are following the most...

Generalized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model...

Purpose Part I of this article ( European Business Review , Volume 28, Issue 1) offered an overview of unobserved heterogeneity in the context of partial least squares structural equation modeling (PLS-SEM), its prevalence and challenges for social sciences researchers. This paper aims to...

Purpose: This study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field....

Purpose: The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons...

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...