Covariance-based path analysis with maximum likelihood estimation (AMOS 20.0) was used to estimate the theoretical model. Interaction terms were included in the model to test for the interaction hypotheses. For interpretative purposes (Echambadi and Fless, 2007) process
control and process-based reward were mean-centered prior to the creation of the interaction terms. Because multicollinearity is an endemic problem in models that simultaneously contain linear and interaction terms of the same variables, collinearity was examined by calculating variance inflation factors (VIF). All VIF values were below 10, indicating no severe multicollinearity problems. We checked whether parameter estimates were sensitive to the addition or deletion of the interaction terms by estimating a main-effect-only model. Because the coefficients’ signs and magnitudes did not change only the final model (model with main and interaction effects) is shown.