Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments
Esposito Vinzi, Vincenzo
Ringle, Christian M.
Segmentation in PLS path modeling framework results is a critical issue in social sciences. The assumption that data is collected from a single homogeneous population is often unrealistic. Sequential clustering techniques on the manifest variables level are ineffective to account for heterogeneity in path model estimates. Three PLS path model related statistical approaches have been developed as solutions for this problem. The purpose of this paper is to present a study on sets of simulated data with different characteristics that allows a primary assessment of these methodologies.
Partial Least Squares; Path Modeling; Unobserved Heterogeneity
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