Understanding the distribution of online consumer ratings for food products can provide insights that aid supply chain decisions. Using a researcher‐collected web‐scraped panel data set from Amazon, this article quantifies the effect of number of ratings, average rating, variance of ratings, and skewness of the rating distribution. Results show that the number of ratings and each of these moments of the distribution of online consumer ratings affect ground coffee sales ranking. The size of the effect of the distribution of ratings was found to vary with respect to the sales level of the coffee products. The results suggest that the distribution of online ratings plays an important informational role in e‐commerce platforms. As online grocery shopping continues to increase in popularity, a greater understanding of how online ratings and reviews may impact sales or products are needed by those in the agricultural and food supply chain. In particular, these results provide retail managers with an array of online consumer rating attributes to use in their demand forecasts. [EconLit citations: D12, D83, L81, M31, Q11].

中文翻译：

---

评分的分布是否会影响在线杂货销售？来自亚马逊的证据

了解食品在线消费者评级的分布可以提供有助于供应链决策的见解。本文使用研究人员从亚马逊收集的网络刮板面板数据集，量化了评分数量，平均评分，评分差异和评分分布偏斜的影响。结果表明，评分的数量以及在线消费者评分的分布的各个时刻都会影响咖啡粉的销售排名。发现评级分布的影响大小随咖啡产品的销售水平而变化。结果表明，在线评分的分布在电子商务平台中起着重要的信息作用。随着在线杂货店购物的持续普及，农业和食品供应链中的人们需要对在线评级和评论如何影响销售或产品有更多的了解。尤其是，这些结果为零售经理提供了一系列在线消费者评分属性，以用于他们的需求预测。[EconLit引文：D12，D83，L81，M31，Q11]。