Abstract
Structural equation modelling (SEM) has been increasingly utilized in marketing and management areas. This increasing deployment of SEM suggests that a comparison should be made of the different SEM approaches. This would help researchers choose the SEM approach that is most appropriate for their studies. After a brief review of the SEM theoretical background, this study analyzes two models with different sample sizes by applying two different SEM techniques to the same set of data. The two SEM techniques compared are: Covariance-based SEM (CBSEM) – specifically, maximum likelihood (ML) estimation – and Partial Least Squares (PLS). After presenting the study findings, the paper provides insights regarding when researchers should analyze models with CBSEM and when with PLS. Finally, practical suggestions concerning PLS use are presented and we discuss whether researcher considered these.
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Barroso, C., Carrión, G.C., Roldán, J.L. (2010). Applying Maximum Likelihood and PLS on Different Sample Sizes: Studies on SERVQUAL Model and Employee Behavior Model. In: Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds) Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_20
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