When to Broadcast? Inventory Disclosure Policies for Online Sales of Limited Inventory
研究了在线限时抢购中零售商披露库存信息的最佳时机，提出了时间依赖阈值政策，发现其优于简单披露策略，并分析了从众效应和稀缺效应对政策效果的影响。
Online sales of limited inventory such as flash sales and lightning deals have become popular among e-commerce retailers including Amazon and eBay. This study focuses on the retailer’s best timing of disclosing inventory information to maximize the expected sales in a finite horizon. We consider how two prominent customer mechanisms, herding effect and scarcity effect, affect the relative performance of different policies. We analyze the following common policies in practice: “always disclose,” “never disclose,” and the fixed threshold policy, which broadcasts the inventory level once it drops below a predetermined level. We also propose a novel time-dependent threshold policy, which we prove to be the optimal policy under reasonable assumptions. We devise efficient algorithms to optimize the policy parameters, and we compare all policies through a numerical study. We find that both threshold policies significantly outperform the two simple policies. Moreover, herding effect and scarcity effect have significant impacts on the relative performance of different policies. Our study provides not only effective and efficient algorithms for policy optimization but also guidelines for policy selection. Policymakers can refer to our study to identify the most appropriate policy, depending on the relative strength of the two customer mechanisms on the platform.