Research Note--Partial Least Squares and Models with Formatively Specified Endogenous Constructs: A Cautionary Note

Author List: Aguirre-Urreta, Miguel I.; Marakas, George M.;

Information Systems Research, 2014, Volume 25, Issue 4, Page 761-778.

Information systems researchers have recently begun to propose models that include formatively specified constructs, and largely rely on partial least squares (PLS) to estimate the parameters of interest in those models. In this research, we focus on those cases where the formatively specified constructs are endogenous to other constructs in the research model in addition to their own manifest indicators, which are quite common in published research in the discipline, and analyze whether PLS is a valid statistical technique for estimating those models. Although there is evidence that covariance-based approaches can accurately estimate them, this is the first research that examines whether PLS can indeed do so. Through a theoretical analysis based on the inner workings of the PLS algorithm, which is later validated and extended through a series of Monte Carlo simulations, we conclude that is not the case. Specifically, estimates obtained from PLS are capturing something other than the relationship of interest when the formatively specified constructs are endogenous to others in the model. We show how our results apply more generally to a class of models, and discuss implications for future research practice.

Keywords: formative specification;partial least squares;research methods;structural equation modeling

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#11	0.631	structural pls measurement modeling equation research formative squares partial using indicators constructs construct statistical models researchers latent analysis results sem
#21	0.088	research information systems science field discipline researchers principles practice core methods area reference relevance conclude set focus propose perspective inquiry
#222	0.086	research researchers framework future information systems important present agenda identify areas provide understanding contributions using literature studies paper potential review
#17	0.064	empirical model relationships causal framework theoretical construct results models terms paper relationship based argue proposed literature issues assumptions provide suggest
#116	0.051	research study influence effects literature theoretical use understanding theory using impact behavior insights examine influences mechanisms specifically context perspective findings