Optimal Pricing Strategy For Customized Bundles With Shipping Policy In Online Retailing

Bundling refers to selling multiple products with a certain discount while the products are mainly selected by retailers.In contrast,customized bundling is a new practice that allows customers to choose their own items to bundle and retailers decide the bundle prices in response to customers' choices.However,bundle customization means more possible bundles to be priced.Therefore,pricing customized bundles becomes a problem for retailers.The customized bundle pricing problem is addressed from the online retailer's perspective.In particular,two commonly employed shipping promotion policies are investigated: ① contingent free shipping policy,i.e.allowing consumers to enjoy free shipping when purchases exceed a threshold;and ② add-on policy,i.e.recommending lowprice products to consumers to help them reach the threshold.In practice,these two promotion policies are often used jointly.By considering shipping fee and shipping promotion policies into consumers' shopping process,a non-linear integer programming model for consumer decision-making with maximum consumer surplus is given.Then a large-scale non-linear mix-integer programming model to maximize the online retailer's profit by pricing customized bundles is given.A near-optimal heuristic is designed to solve the problem.Extensive numerical studies using real data show that our pricing model with both shipping promotion policies produces win-win outcomes on retailer's profit and consumers' surplus,with 8.77% and 10.96% improvement,respectively.Compared to using contingent free shipping policy only,the retailer gains additional 2.97% profit after incorporating add-on policy.Sensitivity analyses show that the model is robust.