Optimizing E‐tailer Profits and Customer Savings: Pricing Multistage 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 electronic retailers (‘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 variety of products customers may choose to incorporate during the various stages of their online shopping. Our computational study suggests that the proposed model not only attracts more customers to purchase the discounted bundle but also noticeably increases profits for e‐tailers. This online dynamic bundle pricing model is robust under various bundle sizes and scenarios. It improves e‐tailer profit and customer savings the most when facing divergent views about product values, lower budgets, and higher cost ratios.