Spatial pricing and warehouse assortment in online retailing

• Main Author: Wang, Xuchen
• Other Authors: Yan Zhenzhen
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2025
• Subjects: Business and Management; Mathematical Sciences
• Online Access: https://hdl.handle.net/10356/182186
• Institution: Nanyang Technological University

This thesis focuses on two pivotal topics in online retailing: the spatial pricing problem and the warehouse assortment selection problem. Spatial pricing involves adjusting demands or service costs based on geographic location. In the first part of the thesis, we develop a profit-maximization model to make spatial pricing decisions consisting of indiscriminate product prices and a shipping policy that shares shipping costs with consumers. This model assumes consumer responses follow a BundleMVL-K choice model, which captures multi-item purchase behavior. Solving the spatial pricing problem is challenging due to nonconvex constraints and a bilinear objective function. To address this, we formulate a mixed-integer linear program (MIP) using piecewise linear functions to approximate the continuous functions with given approximation errors. The MIP is an upper bound problem of the spatial pricing model. Based on the solution of the upper bound problem, a heuristic strategy is proposed. This strategy ensures a profit with an approximation gap that is upper bounded by the accuracy of the piecewise linear approximation. The gap is sufficiently small when the piecewise linear approximation function is tight enough. Building on the profit-maximization model, the second part of the thesis integrates the multi-warehouse assortment decision, considering SKU capacity limitations. We develop a two-stage optimization problem: the first stage focuses on profit maximization, while the second stage, with spatial pricing and warehouse assortment decisions fixed, aims to minimize fulfillment costs. We use a similar framework to manage the intricacies of the optimization problem and propose a strategy for the joint spatial pricing and warehouse assortment problem, ensuring near-optimal profit with a small optimality gap. The thesis emphasizes the benefits of the shipment pooling effect, which is the ability to reduce shipping costs by consolidating products in an order. The practical implications of the retailer's model are explored through numerical studies, where an online retailer manages two warehouses, each selling three different products to customers located in two distinct districts. The results of this study yield several intriguing insights. For instance, it is observed that the optimal pricing strategy does not necessarily align with the ranking of consumer preferences for the products. Furthermore, the study reveals that, under certain SKU restrictions, it is not always advantageous to stock high-value products in the warehouse. This insight challenges conventional wisdom and underscores the importance of considering a holistic view of warehouse management and spatial pricing strategies. Overall, this research contributes to the field of online retailing by providing a comprehensive and tractable framework for addressing complex spatial pricing and warehouse assortment problems. Technically, the framework provide near optimal solutions with performance guarantee. The findings have practical implications for online retailers seeking to optimize their operations and enhance profitability.