| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w18567 |
| 来源ID | Working Paper 18567 |
| Aggregation of Consumer Ratings: An Application to Yelp.com | |
| Weijia Dai; Ginger Z. Jin; Jungmin Lee; Michael Luca | |
| 发表日期 | 2012-11-29 |
| 出版年 | 2012 |
| 语种 | 英语 |
| 摘要 | Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average. |
| 主题 | Microeconomics ; Economics of Information ; Industrial Organization ; Market Structure and Firm Performance ; Industry Studies |
| URL | https://www.nber.org/papers/w18567 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/576242 |
| 推荐引用方式 GB/T 7714 | Weijia Dai,Ginger Z. Jin,Jungmin Lee,et al. Aggregation of Consumer Ratings: An Application to Yelp.com. 2012. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w18567.pdf（1529KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
