CB-SEM vs PLS-SEM comparison in estimating the predictors of investment intention

Abstract

This paper compares different structural equation modeling approaches in estimating the predictors of investment intention. Covariance-based structural equation modeling (CB-SEM) and partial least squares structural equation modeling (PLS-SEM) techniques were compared in the estimation of the model according to the theory of planned behavior (TPB). Additionally, the consistent PLS algorithm (PLSc) was taken into consideration in the methods comparison. To determine which factors affect stock investment intention, a TPB model with attitude towards behavior, perceived behavioral control, and subjective norm as independent variables was estimated using three different approaches. The factors in the model were measured using survey indicators and the final sample included 200 Croatian residents. The results mostly show matching conclusions about the investment intention predictors, with a small difference observed in the PLS-SEM method. It can also be concluded that the factor loadings are higher according to PLS-SEM, as well as the indicators of convergent validity and reliability. On the other hand, CB-SEM shows stronger structural paths than PLS-SEM, and PLSc results are closer to those of CB-SEM. While CB-SEM shows better model fit, PLS-SEM shows high predictive power. This research further provides explanations of the differences and guidelines on when to use which approach.