时间：2019年10月17日（周四）下午13:00-14:30
地点：华东师范大学中山北路校区理科大楼A312会议室
题目：Costly Price Adjustment and Automated Pricing: The Case of Airbnb
报告人：潘祺博士 宾夕法尼亚大学经济系
报告摘要：
On many e-commerce platforms such as Airbnb, StubHub and TURO, where each seller sells a fixed inventory over a finite horizon, the pricing problems are intrinsically dynamic. However, many sellers on these platforms do not update prices frequently. In this paper, I develop a dynamic pricing model to study the revenue and welfare implication of automated pricing which allows sellers to update their prices without manual interference. The model focuses on three factors through which automated pricing influences sellers: price adjustment cost, buyer's varying willingness to pay and inventory structure. In the model, I also take into account competition among sellers. Utilizing a unique data set of detailed Airbnb rental history and price trajectory in New York City, I find that the price rigidity observed in the data can be rationalized by a price adjustment cost ranging from 0:9% to 2:2% of the listed price. Moreover, automated pricing can increase the platform's revenue by 4.8% and the hosts' (sellers') by 3.9%. The renters (buyers) could be either better off or worse off depending on the length of their stays.
报告人简介：
潘祺现为宾夕法尼亚大学经济系博士候选人，并将于2020年5月获得博士学位。他在中国人民大学获得经济学硕士，在中山大学获得数学学士。他的研究兴趣包括量化营销，实证产业组织，计量建模和大数据分析。他目前的研究项目为动态定价和共享经济。在他的求职论文中，他通过建立一套实证框架分析了Airbnb上的定价行为，并且他利用该实证框架研究了自动定价对使用者的影响。他的研究探索了在竞争条件下的实证动态定价问题而且让研究者对自动定价有更深入的了解。他同时还利用动态退出与进入模型研究了Airbnb对传统租赁市场的影响。他的建模方法和研究结果提供了丰富的公司管理启示。在动态定价和共享经济以外，潘祺的研究领域还包括贝叶斯计量。