The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment
通过数字平台改变评级显示规则的准实验，发现评级膨胀虽提升平均评分、促进交易，但也降低用户尝试新卖家意愿并加剧销售集中，对平台管理有启示。
Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation. Using a differences-in-differences approach, we find that platforms benefit from one aspect of rating inflation: user purchases and seller sales increase because of the increased average rating. However, they also face negative consequences: rating inflation causes a decrease in user trial and a greater concentration of sales among popular restaurants. Overall, our results illustrate the potential consequences of rating inflation that platforms need to consider when designing and managing their rating system.