Optimal add-on items recommendation service strength strategy for e-commerce platform with full-reduction-promotion

Abstract

This purpose of the paper is to make an in-depth study on the selection of the optimal shopping add-on items recommendation service strength strategy of the e-commerce platform with full-reduction promotion based on consumers' heterogeneity preferences for discount amount and add-on items recommendation. With respect to the optimal decision problem consisting of an e-commerce platform who maximizes the profits and consumers who make purchase decision based on their utility, we construct a Stackelberg game model that reflects the interaction between platform' s recommendation service strength and consumers' purchase willingness. Furthermore, through the derivative function analysis method, we examine the effect of reservation price, recommended commodity price and discount amount on the platform' s optimal recommendation service strength strategy. The results show that the discount amount, reservation price and consumer preference have different effects on the optimal add-on items recommendation service strength and the profit of the platform. Additionally, appropriate recommendation services strength is beneficial to enhance consumers' willingness-To-pay and then increase the profits of the platform. Therefore, it is an effective way to improve the performance of the platform to reasonably formulate the basic discount amount, full-reduction promotion threshold and add-on items recommendation service strength.