Structural equation modeling (SEM) is a methodology used to represent assumptions about the means, variances, and covariances of observed data using a limited number of “structural” parameters defined by an underlying theoretical model. According to Kaplan (2000), it allows for a more concise synthesis of this information. Two main categories of models are predominant within these methodologies: covariance structure analysis (CSA), exemplified by the LISREL2 model, and partial least squares (PLS3).