Modeling Cross Category Purchase Decision Making with Consumers’ Mental Budgeting Control Habit - Yang, Zhiguo (Information Management and Business Review, 2020)
Cross-category decision making is an ongoing research in decision science. Cross-category modeling is a powerful tool for big data and business analytics. Cross-category decision making involves evaluating multiple categories for complementary/substitutional utilities. This paper examines consumers’ mental budgeting control habit for its impact on cross purchase decisions. This factor has not been examined in existing cross modeling literature. This paper fits a base cross category model and a budgeting control habit cross model using a consumer grocery shopping dataset. The results show that by incorporating this variable in the cross model, model fit score and prediction accuracy are significantly improved. The budgeting control habit factor has significant moderating effects on price effects and cross price effects. In addition to providing the modeling technique, this paper also finds that consumers classify basket items into root and add-on categories. The common sense that price drop boosts sales is only true for the root category items. Price drop of add-on items may trigger consumers reconfiguring their basket items but not necessarily increase sales of the add-on items themselves.