Many retailers sell products both online and in brick-and-mortar stores. In such omnichannel systems, the retailers need to decide what products to offer at what prices in which channels, and how online orders will be fulfilled, either from distribution centers or from store inventory. This project will use mathematical models to optimize retailers' decisions in omnichannel systems. Specifically, researchers will identify policies that retailers can use to identify the assortment of products to be sold in each channel and their prices while accounting for fulfillment considerations such as inventory imbalance and expedited shipping. This project has the potential to positively impact retail operations of companies of all sizes. In addition, it will provide educational opportunities for doctoral and master's students, as well as undergraduate students. The latter will participate in this project through the university's Undergraduate Research Opportunity Program.
The objective of this research is to develop algorithms and identify policies that are optimal or near-optimal for decisions arising in retail operations with multiple channels. These decisions include (1) assortment and inventory policies that prescribe which products, and how many units per product, should be stocked in each store and distribution center; (2) fulfillment policies that prescribe from which store, or distribution center, online orders should be fulfilled; and (3) pricing policies that dynamically adjust the price of products sold in certain channels to maintain a balanced system-wide inventory distribution. Researchers will formulate these problems as mathematical programs and use their solutions to construct near-optimal policies. Existing literature typically only considers the problem of optimizing retail operations in brick-and-mortar stores without considering the online channel. By considering both these channels, this project will contribute to the emerging academic literature on retail operations.
