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讲座题目：The Role of On-Demand Delivery Platforms in Restaurants
讲座人：王刚博士
主持人：李凯教授
讲座时间：2021年11月26日（星期五）下午4：00
讲座地点：腾讯会议（欢迎有兴趣参与讲座的师生于2021年11月25日前发邮件至8160589@sqdhcn.com获取腾讯会议ID，来邮烦请注明学校和姓名！）
讲座摘要：
Restaurants are increasingly relying on on-demand delivery platforms (e.g., DoorDash, Grubhub, and Uber Eats) to reach customers and fulfill takeout orders. Although on-demand delivery is a valuable option for consumers, whether restaurants benefit from or are being hurt by partnering with these platforms remains unclear. This paper investigates whether and to what extent the platform delivery channel substitutes restaurants’ own takeout/dine-in channels and the net impact on restaurant revenue. Empirical analyses show that restaurants overall benefit from on-demand delivery platforms—these platforms increase restaurants’ total takeout sales while creating positive spillovers to customer dine-in visits. However, the platform effects are substantially heterogeneous, depending on the type of restaurants (independent vs. chain) and the type of customer channels (takeout vs. dine-in). The overall positive effect on fast-food chains is four times as large as that on independent restaurants. For takeout, delivery platforms substitute independent restaurants’ but complement chain restaurants’ own takeout sales. For dine-in, delivery platforms increase both independent and chain restaurants’ dine-in visits by a similar magnitude. Therefore, the value of delivery platforms to independent restaurants mostly comes from the increase in dine-in visits, whereas the value to chain restaurants primarily comes from the gain in takeout sales. Further, the platform delivery channel reduces geographic frictions and the opportunity for independent restaurants to differentiate with premium services and dine-in experience, which may explain why independent restaurants do not benefit as much from on-demand delivery platforms.
讲座人简介：
王刚，现为特拉华大学色情导航 终身教授。本科、研究生毕业于南开大学管理科学与工程系，博士毕业于康涅狄格大学色情导航 运营管理与信息管理系。主要研究方向包括多边平台的运营机制及社会影响、社交媒体与同群效应。研究成果发表在MIS Quarterly, Information Systems Research等多个顶级或知名期刊。
