Optimizing E-tailer Profits and Customer Savings: Pricing Multi-Stage Customized Online Bundles

Online retailing provides an opportunity for new pricing options that are not feasible in traditional retail settings. This paper proposes an interactive, dynamic pricing strategy from the perspective of customized bundling to derive savings for customers while maximizing profits for e-tailers. Given product costs, posted prices, shipping fees and customers’ reservation prices, we propose a nonlinear mixed-integer programming model to increase e-tailers’ profits by sequentially pricing customized bundles. The model is flexible in terms of the number and the variety of products customers may choose to incorporate during the various stages of their online shopping process. Our computational study suggests that the proposed model not only attracts more customers to purchase the discounted bundle, but also noticeably increases profits for etailers. The ODBP model is robust under various bundle sizes and scenarios. It performs the best when confronted with divergent views about product values, lower budgets, and higher cost