管理科学系学术讲座（5月26日）

时   间：2025年5月26日（周一） 15:00-16:30

地   点：管理学院思源楼524室

主题：  Newsvendor under Mean-Variance Ambiguity and Misspecification

主讲人： Zhi Chen（陈植）, Assistant Professor

The Chinese University of Hong Kong（香港中文大学）

主持人：周明龙 复旦大学管理学院青年副研究员

Abstract:

Consider a newsvendor problem with an unknown demand distribution. When addressing the issue of distributional uncertainty, we distinguish ambiguity under which the newsvendor does not differentiate demand distributions of common distributional characteristics (e.g., mean and variance) and misspecification under which such characteristics might be misspecified (due to, e.g., estimation error and/or distribution shift). Focusing on the popular mean-variance ambiguity set and optimal-transport cost for the misspecification, we derive the closed-form optimal order quantity that generalizes the solution of the seminal Scarf model under only ambiguity aversion. We quantify the finite-sample performance guarantee, which consists of two parts: the in-sample optimal value and the out-of-sample effect of misspecification that can be decoupled into estimation error and distribution shift. This theoretically justifies the necessity of incorporating misspecification aversion in a non-stationary environment, which is also well demonstrated in our experiments with real-world retailing data. Our framework can be extended to consider multiple products, distributional characteristics specified via optimal transport, and misspecification measured by phi-divergence.

Bio:

Zhi Chen is an Assistant Professor in the CUHK Business School, the Chinese University of Hong Kong. His research interests include (1) developing models and designing algorithms for decision-making under uncertainty with different levels of data availability as well as applications in business, economics, finance, and operations; (2) how to compete or cooperate in joint activities such as resource allocation and risk management.