Graduate Seminar, 2023/11/8
Speaker:
Sean Zhou (周翔)
Position:
香港中文大學 Department of Decision Sciences and Managerial Economics
Bio:
Sean Zhou (周翔) is Professor and Chair of Department of Decision Sciences and Managerial Economics, CUHK Business School, and Professor in Department of Systems Engineering and Engineering Management (by courtesy), at The Chinese University of Hong Kong (CUHK). He has held visiting positions at National University of Singapore and University of Toronto. He received his bachelor’s degree in Electrical Engineering from Zhejiang University and PhD in Operations Research from North Carolina State University. His main research interests are inventory management, pricing, sustainable operations, data-driven supply chain optimization, and operations and marketing interface. He serves on editorial board of various journals including Naval Research Logistics, OR Letters, and Service Science.
Topic:
Dynamic Pricing for Multi-Product Consumer Electronics Trade-in Program
Abstract
We consider a dynamic pricing problem for consumer electronics trade-in program, where a firm buys and sells multiple types of pre-owned (used) products over a finite selling horizon. The trade-in program offers two options: trade-in for cash and trade-in for upgrade, where in the former customers sell their products to the firm and receive cash payment while in the latter, they exchange their products for new products at discounted prices. The firm sets trade-in prices (both cash rewards and new products' discounts) to acquire used products and selling prices to resell them (refurbished products) to maximize its total expected profit. Customer arrivals follow independent Poisson processes and their choices on either used product trade-in or refurbished product purchase follow the Multinomial Logit (MNL) model. In view of the challenge of solving the optimal prices using dynamic programming due to high dimensional state space, we develop simple and provably effective heuristic policies based on the solution to a deterministic upper bound problem. In the first policy called the Static Control (SC) policy, by setting some inventory buffers of refurbished products at the beginning of the selling horizon, we show that the profit loss of SC policy is in the order of O(T^(1/2) ), where T is the number of selling periods. Meanwhile, we derive a profit loss lower bound in the order of Ω(T^(1/2) ) of any static stationary policy. To improve the SC policy, we design the second policy called the Batched-Adjustment Control (BAC) policy. Under the BAC policy, the selling horizon is divided into different consecutive and disjoint batches for different products and the prices in one batch are updated based on the realized uncertainties in the previous batch. The profit loss of BAC policy is in the order of O(T^(1/3) ). We numerically show that both policies perform well and the BAC policy has superior performance over the SC policy. Finally, we study three extensions of our model: initial stocking of new products (for upgrade purposes), vertically differentiated products/choices, and additional practical trade-in features, and adapt the heuristics and their theoretical performance analysis to these extensions. This is joint work with Murray Lei (Queen’s University) and Zhuoluo Zhang (CUHK).
