Sourcing for online marketplaces with demand and price uncertainty

• 成果类型: Article
• 署名作者: Gaur, Vishal; Osadchiy, Nikolay; Seshadri, Sridhar; Subrahmanyam, Marti G.
• 署名单位: Cornell University; Emory University; University of Illinois System; University of Illinois Urbana-Champaign; New York University; Emory University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.14023
• 发表日期: 2023
• 页码: 3062-3080
• 关键词: Online Marketplaces; optimal stopping; stochastic inventory theory; Supply chain management

摘要

Our paper is motivated by a manufacturer that sells a seasonal product through multiple retailers competing on an online marketplace, such as the Amazon marketplace. Demand and selling price uncertainty are key features of the online marketplace. Sourcing choices are differentiated by cost and available lead times-delaying shortens the lead time which is more expensive but yields more accurate information about future selling price and demand. Thus, ahead of the season, each retailer faces a continuous-time decision problem about when to place an order with the manufacturer and in what quantity. The manufacturer is interested in knowing the ordering pattern of the retailers in order to plan production. We consider two sourcing strategies varying in the flexibility of order timing: an optimal precommitted ordering time strategy and an optimal time-flexible ordering strategy. We prove that the former is optimal when the selling price is constant and the latter when the selling price is uncertain. We show that time-flexible ordering can be mutually beneficial for the retailer and the manufacturer in a wide range of scenarios and that the manufacturer can favorably influence order timing by adjusting its wholesale price trajectory. The predictions of our model are consistent with the experience of a large U.S. manufacturer that motivated our study.