Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database

• 成果类型: Article
• 署名作者: Anderson, Michael; Magruder, Jeremy
• 署名单位: University of California System; University of California Berkeley
• 刊物名称: ECONOMIC JOURNAL
• ISSN/ISSBN: 0013-0133
• DOI: 10.1111/j.1468-0297.2012.02512.x
• 发表日期: 2012
• 页码: 957-989
• 关键词: Reputation; ebay; MARKET; DESIGN; price; plan

摘要

Internet review forums increasingly supplement expert opinion and social networks in informing consumers about product quality. However, limited empirical evidence links digital word-of-mouth to purchasing decisions. We implement a regression discontinuity design to estimate the effect of positive Yelp.com ratings on restaurant reservation availability. An extra half-star rating causes restaurants to sell out 19 percentage points (49%) more frequently, with larger impacts when alternate information is more scarce. These returns suggest that restaurateurs face incentives to leave fake reviews but a rich set of robustness checks confirm that restaurants do not manipulate ratings in a confounding, discontinuous manner.