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This research discusses alternative latent class techniques and calls for the joint use of FIMIX-PLS and PLS prediction-oriented segmentation. These techniques address some of the limitations of the approach relating to, for example, its failure to handle heterogeneity in measurement models, or its distributional assumptions. Research limitations/implications – Since the introduction of FIMIX-PLS, a range of alternative latent class techniques has appeared. Furthermore, it shows that FIMIX-PLS is particularly useful for determining the number of segments to extract from the data. Findings – The case study demonstrates the capability of FIMIX-PLS to identify whether unobserved heterogeneity significantly affects structural model relationships. Design/methodology/approach – This case study illustrates the application of FIMIX-PLS using a popular corporate reputation model.
#Smartpls 3 bootstraping settings how to
This paper aims to provide an example that explains how to identify and treat unobserved heterogeneity in PLS-SEM by using the finite mixture PLS (FIMIX-PLS) module in the SmartPLS 3 software (Part II). 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. Matthews, Lucy M Sarstedt, Marko Hair, Joseph F. Identifying and treating unobserved heterogeneity with FIMIX-PLS Identifying and treating unobserved heterogeneity with FIMIX-PLS