主题: An Inventory Perspective for Omnichannel Design
报告人简介：杨翼，浙江大学管理学院教授，博士生导师，数据驱动决策研究所所长，国家自然科学基金优秀青年科学基金获得者。2011年毕业于香港中文大学系统工程与工程管理学系。主要研究方向包括库存管理、收益管理以及运营管理。在高水平国际期刊上发表论文十余篇，特别是在《Operations Research》,《Manufacturing & Service Operations Management》,《Production and Operations Management》等UT/Dallas24种经济管理类国际公认顶级期刊上发表学术论文多篇。承担多项国家及省部级课题，现担任中国运筹学会的英文期刊JORSC (Journal of the Operations Research Society of China)的Associate Editor、运筹学会随机服务与运作管理分会理事、系统工程学会物流系统工程专业委员会理事等工作。
报告摘要: Many traditional retailers and etailers such as Walmart and Amazon have been implementing omnichannel strategies, such as buy-online pickup-at-store (BOPS) and buy-online ship-to-store (BOSS). We build a stylized model to investigate the impact of these omnichannel strategies on store operations from the inventory perspective. For BOPS, we find that it may benefit or hurt the retailer depending on his two key capabilities: the brick-and-mortar (B&M) store density and the online delivery efficiency. For a retailer with a relatively low density of B&M stores and a high delivery efficiency, BOPS incentives certain customers to migrate from the online channel to BOPS, leading to a demand pooling at the B&M store. It generates two benefits for the retailer: 1) it allows a higher utilization of the local inventory and saves overstocking cost (risk hedging effect); and 2) it results in a higher fill rate at the B&M store (availability improvement effect), which benefits the existing customers and attracts more additional customers to visit it. On the contrary, for a retailer with a modest density of B&M stores and a low delivery efficiency, BOPS may hurt the retailer and customers due to a demand depooling effect as (a portion of) customers who originally shop offline are likely to switch to BOPS. It will reduce the fill rate at the B&M store, driving out of customers who previously remained stubbornly in-store and forcing those who originally prefer the offline channel to purchase online. For BOSS, it is in general beneficial to both the retailer due to the cost savings of last mileage delivery and customers due to the reduction of waiting cost. However, BOSS aggravates the depooling effect compared with BOPS. Moreover, we use many real examples to empirically illustrate the practical implications of our theoretical results.