The orthogonalizing approach is an extension of the product indicator approach.

This approach uses residuals that are calculated by regressing all possible pairwise product terms of the indicators of the latent predictor and the latent moderator variable (i.e., product indicators) on all indicators of the latent predictor and the latent moderator variable. These residuals serve as indicators of the interaction term in the structural model.

The residuals will be orthogonal to all indicators of the predictor and moderator variable to ensure that the indicators of the interaction term do not share any variance with any of the indicators of the predictor or moderator variable.

Little, Bovaird, and Widaman (2006) developed the approach to address two issues that are the result of the standardization of variables as implemented in the product indicator approach.

First, while indicator standardization reduces the level of collinearity in the PLS path model, it does not fully eliminate it. So despite the standardization, collinearity in the path model may still be substantial, yielding inflated standard errors or biased path coefficient estimates

Second, when the variables are standardized, one cannot readily compare the direct effect between Y1 and Y2 when no interaction term is included (i.e., the main effect), with the effect between Y1 and Y2 when the interaction term is included (i.e., the simple effect).

Because of its reliance on product indicators, the orthogonalizing approach is only applicable when the exogenous construct and the moderator variable are measured reflectively.