The Consumers' Purchase Intention on Social Commerce: Using BMA Algorithm

Abstract

The study aims to identify factors impacting consumers' purchase intention on social commerce (SC) by applying the Bayesian model averaging (BMA) algorithm. The background theory of the study is the theory of planned behavior (TPB). The BMA approach not only chooses a single optimal model among the workable choice models but can choose several models to interpret the predicted variable in the linear regression analysis. The findings disclosed the best 4 models for factors affecting consumers' purchase intention on SC. Which, the 4 dominant factors (attitude, subjective norm, trust, and perceived enjoyment) appeared in all models. The 2 factors (perceived behavior control and social commerce constructs) appeared at 80% and 59,7% respectively in the models.