PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement

TLDR: The authors introduce the development of new estimation modes and schemes for multidimen- sional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the uses of path analysis on latent variable scores to estimate path coefficients.

Abstract: In this chapter the authors first present the basic algorithm of PLS Path Modeling by discussing some recently proposed estimation options. Namely, they introduce the development of new estimation modes and schemes for multidimen- sional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the use of path analysis on latent variable scores to estimate path coefficients Furthermore, they focus on the quality indexes classically used to assess the perfor- mance of the model in terms of explained variances. They also present some recent developments in PLS Path Modeling framework for model assessment and improve- ment, including a non-parametric GoF-based procedure for assessing the statistical significance of path coefficients. Finally, they discuss the REBUS-PLS algorithm that enables to improve the prediction performance of the model by capturing unob- served heterogeneity. The chapter ends with a brief sketch of open issues in the area that, in the Authors' opinion, currently represent major research challenges.