声誉
共享经济
领域(数学)
白色(突变)
信誉制度
空白
住宿
业务
广告
营销
互联网隐私
计算机科学
心理学
政治学
万维网
法学
电信
神经科学
生物化学
无线
基因
认知无线电
数学
化学
纯数学
作者
Ruomeng Cui,Jun Li,Dennis Zhang
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2019-08-01
卷期号:66 (3): 1071-1094
被引量:284
标识
DOI:10.1287/mnsc.2018.3273
摘要
Recent research has found widespread discrimination by hosts against guests of certain races in online marketplaces. In this paper, we explore ways to reduce such discrimination using online reputation systems. We conducted four randomized field experiments among 1,801 hosts on Airbnb by creating fictitious guest accounts and sending accommodation requests to them. We find that requests from guests with African American–sounding names are 19.2 percentage points less likely to be accepted than those with white-sounding names. However, a positive review posted on a guest’s page significantly reduces discrimination: when guest accounts receive a positive review, the acceptance rates of guest accounts with white- and African American–sounding names are statistically indistinguishable. We further show that a nonpositive review and a blank review without any content can also help attenuate discrimination, but self-claimed information on tidiness and friendliness cannot reduce discrimination, which indicates the importance of encouraging credible peer-generated reviews. Our results offer direct and clear guidance for sharing-economy platforms to reduce discrimination. This paper was accepted by Vishal Gaur, operations management.
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