Since its first introduction in the Schmalenbach Business Review, Hahn et al.'s (2002) finite mixture partial least squares (FIMIX-PLS) approach to response-based segmentation in variance-based structural equation modeling has received much attention from the marketing and management...

Mixture regression models are an important method for uncovering unobserved heterogeneity. A fundamental challenge in their application relates to the identification of the appropriate number of segments to retain from the data. Prior research has provided several simulation studies that compare...

The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a...

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...

Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships. A common goal of PLS-SEM analyses is to identify key success factors and sources of competitive advantage for important target...

Marketing researchers are increasingly taking advantage of the instrumental variable (IV)-free Gaussian copula approach. They use this method to identify and correct endogeneity when estimating regression models with non-experimental data. The Gaussian copula approach’s original presentation...