Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods

Journal
Journal of the Academy of Marketing Science  
Volume
45
Issue
5
Start Page
616
End Page
632
Citation
Journal of the Academy of Marketing Science 5 (45): 616-632 (2017-09-01)
Publisher DOI
10.1007/s11747-017-0517-x
Scopus ID
2-s2.0-85013096195
Publisher
Springer Netherlands
Composite-based structural equation modeling (SEM), and especially partial least squares path modeling (PLS), has gained increasing dissemination in marketing. To fully exploit the potential of these methods, researchers must know about their relative performance and the settings that favor each method’s use. While numerous simulation studies have aimed to evaluate the performance of composite-based SEM methods, practically all of them defined populations using common factor models, thereby assessing the methods on erroneous grounds. This study is the first to offer 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.
Subjects
Composite
Generalized structured component analysis
GSCA
Partial least squares
PLS
SEM
Simulation
Structural equation modeling
Sum scores regression
DDC Class
330: Wirtschaft