New JAMS Paper on PLS-SEM
The paper “Mirror, mirror on the wall. A comparative evaluation of composite-based structural equation modeling methods” has been accepted for publication in Journal of the Academy of Marketing Science (JAMS), one of the top-tier journals in business research in terms of impact factor and ranked in the Financial Times top 50 journal list. The paper, authored by Joe F. Hair (University of Southern Alabama), G. Tomas M. Hult (Michigan State University), Christian M. Ringle (TU Hamburg-Harburg), Marko Sarstedt (OvGU), and Kai O. Thiele (TU Hamburg-Harburg) offers a comprehensive assessment of composite-based SEM techniques on the basis of composite model data, considering a broad range of model constellations. Results of a large-scale simulation study substantiate that PLS and generalized structured component analysis are consistent estimators when the underlying population is composite model-based. While both methods outperform sum scores regression in terms of parameter recovery, PLS achieves slightly greater statistical power.
For more information: http://link.springer.com/article/10.1007/s11747-017-0517-x