New paper on PLS-SEM
The paper “Segmentation of PLS Path Models by Iterative Reweighted Regressions” authored by Rainer Schlittgen (University of Hamburg), Christian M. Ringle (Hamburg University of Technology), Marko Sarstedt (OvGU), and Jan-Michael Becker (University of Cologne) has been accepted for publication in Journal of Business Research. In their paper, the authors introduce a new approach for uncovering and treating unobserved heterogeneity in partial least squares structural equation modeling (PLS). The iterative reweighted regressions segmentation method for PLS (PLS-IRRS) effectively identifies and treats unobserved heterogeneity in data sets. Compared to existing alternatives, PLS-IRRS is multiple times faster while delivering results of the same quality. Researchers should therefore routinely use PLS-IRRS to address the critical issue of unobserved heterogeneity in PLS.