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

被引:241
作者
Anderson, Michael [1 ]
Magruder, Jeremy [1 ]
机构
[1] Univ Calif Berkeley, Dept Agr & Resource Econ, Berkeley, CA 94720 USA
关键词
FIELD EXPERIMENT; REPUTATION; EBAY; AUCTIONS; DESIGN; MARKET; SALES; PRICE; PLAN;
D O I
10.1111/j.1468-0297.2012.02512.x
中图分类号
F [经济];
学科分类号
02 ;
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.
引用
收藏
页码:957 / 989
页数:33
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