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经济研究中心学术讲座第44期:Field Experiments and Their Applications

作者:经济研究中心  来源:宣传   /  更新日期: 2017-07-05  点击量:813

题 目:Field Experiments and Their Applications

主讲人:崔若濛 教 授

主持人:慕银平 教 授

时 间:2017年7月10日(周一)10:15-11:30

地 点:清水河经管楼 C101

内容简介:

Top 1: The Value of Information Sharing: Field Experiments

Most companies must contend with demand and supply uncertainties. In response, companies use information as a lever to balance supply and demand. I will talk about my two papers that explore the value of inventory information in a retail context and the value of review information to reduce racial discrimination on the sharing economy platform.

Top 2: Learning from Inventory Information: Field Evidence from Amazon.

Many online retailers provide real-time inventory availability information. Customers can learn from the inventory level and update their beliefs about product quality. Thus, consumer purchasing behavior may be impacted by the availability information. Based on a unique setting from Amazon lightning deals, which displays the percentage of inventory consumed in real time, we explore whether and how consumers learn from inventory availability information. Identifying the effect of learning on consumer decisions has been a notoriously difficult empirical question due to endogeneity concerns. We address this issue by running a randomized field experiment on Amazon. In our experiment, we create exogenous shocks on the inventory availability information to a random subset of Amazon lightning deals. In addition, we track the dynamic purchasing behavior and inventory information for 23,665 lightning deals offered by Amazon in August 2016 and exploit their panel structure to further explore the underlying mechanisms behind learning. We find evidence of consumer learning from inventory information: a decrease in product availability causally attracts more sales in the future; in particular, a 10% increase in past sales leads to a 2.08% increase in cart add-ins in the next hour.

Top 3:Discrimination with Incomplete Information in the Sharing Economy: Field Evidence from Airbnb.

Recent research has found widespread discrimination by hosts against guests of certain races in online marketplaces, which endangers the very basis of a sharing economy — building trust in the communities. In this paper, we explore the root cause of discrimination and how to eliminate discrimination. We conducted two randomized field experiments among 1,256 hosts on Airbnb by creating fictitious guest accounts and sending accommodation requests to them. We find that requests from guests with distinctively African American names are 19 percentage points less likely to be accepted than those with distinctively White names. However, a public review posted on a guest page mitigates discrimination: when guest accounts receive a positive review, the acceptance rates of guest accounts with distinctively White and African American names are statistically indistinguishable. We further demonstrate that a negative review also eliminates discrimination.

 

主讲人简介:

Ruomeng Cui is an assistant professor in the Department of Information Systems & Operations Management Department at Goizueta Business School, Emory University. She received her Ph.D. in operations management from the Kellogg School of Management, Northwestern  University in 2014. She received her B.S. degree from Industrial Engineering Department at Tsinghua University in 2009. Prof. Cui's primary research interests are empirical operations management, data-driven decision making, supply chain management, information sharing, retail operations and consumer behavior.

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