A least squares approach to latent variables extraction in formative-reflective models

In this paper, we propose a new least-squares based procedure to extract exogenous and endogenous latent variables in formative-reflective structural equation models. The procedure is a valuable alternative to PLS-PM and Lisrel; it is fully consistent with the causal structure of formative-reflective schemes and extracts both the structural parameters and the factor scores, without identification or indeterminacy problems. The algorithm can be applied to virtually any kind of formative-reflective scheme, with unidimensional and even multidimensional formative blocks. To show the effectiveness of the proposal, some simulated examples are discussed. A real data application, pertaining to customer equity management, is also provided, comparing the outputs of our approach with those of PLS-PM, which may produce inconsistent results when applied to formative-reflective schemes.