Spatial pricing and warehouse assortment in online retailing - Wang, Xuchen (Nanyang Technological University, 2025)
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.