本期论坛将由来自 康奈尔大学的崔耀教授 分享他的研究——“Supply Chain Finance Application and Innovation”。

活动时间：2020年8月28日 08:45-10:30（北京时间）

线上平台：腾讯会议 ( 或 VooV meeting 腾讯会议国际版）

论坛语言：中文/英文

活动日程

08:45-08:55 线上签到

08:55-09:00 论坛介绍 

09:00-10:00 主题演讲

10:00-10:30 提问环节 

嘉宾介绍

主讲人 崔 耀

Yao Cui is an assistant professor of operations, technology and information management at the Samuel Curtis Johnson Graduate School of Management at Cornell University. Prior to joining Johnson, he received his doctoral degree from the Stephen M. Ross School of Business at the University of Michigan and his bachelor’s degree from Department of Industrial Engineering at Tsinghua University.

Professor Cui’s current research interests include: 1) platform operations, and 2) technology innovation in supply chains. In the first stream, he studies operations and revenue management in the sharing/gig economy. In the second stream, he studies how supply chain operations are impacted by new technologies such as blockchain and 3D printing. Professor Cui’s research combines both analytical and empirical methodologies. At Cornell, Professor Cui teaches the operations management core course in the EMBA and MBA programs.

论文简介

Tax-Induced Inequalities in the Sharing Economy

Abstract:

The growth of sharing economy marketplaces like Airbnb has generated discussions on their socioeconomic impact and lack of regulation. As a result, most major cities in the United States have started to charge an “occupancy tax” (which is common for hotels) to Airbnb bookings. In this study, we investigate the effects of the occupancy tax policy on Airbnb listings, using a combination of a generalized causal forest methodology and a difference-in-differences framework. Further, given the considerable variety among listings on Airbnb, we also estimate the heterogeneous treatment effects of the tax. One key finding is that the tax reduces listing revenues substantially, but Airbnb hosts are reluctant to respond by reducing the listing prices. A second important result is that the tax policy is more favorable to commercial hosts with multiple properties or entire-space (“target”) listings, versus residential hosts with single shared-space (“non-target”) listings. We further show evidence that this heterogeneous treatment effect is caused by customers’ discriminatory tax aversion against residential hosts. Stemming from these empirical results we prescribe how hosts should optimally set prices in response to the occupancy tax and also identify the discriminatory tax rates that would equalize the tax’s effect across target and non-target listings.

主持人介绍

主持人  翟  昕

光华管理学院管理科学与信息系统系副教授，高层管理教育中心执行主任。清华大学硕士、双学士，美国普渡大学博士。她的研究兴趣是运营管理、供应链金融。

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