Dynamic Online Bundling Pricing Model and Heuristics Analysis

Abstract

We propose a modeling method for the real-time and multi-stage online purchase decisions, construct an online dynamic bundle pricing model. An emergency replenishment model and a lost sale model were built for replenishment shortage. And then, heuristic algorithm is proposed to solve dynamic pricing and binding decisions. The validity and robustness of the bundling and pricing decision in ER and LS models are compared with. The results show that the two stage heuristic is the best choice when the number of products is low. The DRO heuristic in attrition rate algorithm is more effective when customers are less sensitive to product bundled price. The analysis helps to select packaging complements and choose the appropriate heuristic to calculate the bundled structure and the price of product package.