单商品动态定价问题的状态依赖近似

Regime-Dependent Approximations for the Single-Item Dynamic Pricing Problem

Operations Research · 2026
被引 0
人大 AFT50UTD24ABS 4*

中文导读

研究了当产品需求激增而库存稀缺时,传统动态定价模型失效的问题,发现直觉性的“高价等待”策略无效,而动态耗尽率策略能实现最优定价,为供需严重失衡环境下的定价提供理论框架。

Abstract

Optimizing Prices for Viral Demand and Scarcity Dynamic pricing models often assume that inventory and demand scale proportionally, but this “fluid” view breaks down when products go viral. In “Regime-Dependent Approximations for the Single-Item Dynamic Pricing Problem,” Tarek Abdallah and Josh Reed investigate market extremes, specifically the “large market regime,” where inventory is scarce relative to surging demand. Their analysis reveals critical pitfalls in common heuristic approaches. The authors demonstrate that intuitive “price high and wait” policies are ineffective and, remarkably, that fluid static policies are not even first-order optimal in this context. Instead, they establish that a dynamic run-out-rate policy is essential to achieve both first- and second-order asymptotic optimality. Leveraging Extreme Value Theory, this research provides a robust framework for managing severe supply-demand imbalances, ensuring that firms can effectively capture value in inventory-constrained environments.

动态定价收益管理启发式算法极端值理论