摘要：随着网购普及，消费者日益依赖在线评论来获取信息，特别是产品评分，其已成为衡量卖家水平的重要指标。因此，深入理解电商平台的评分规则，即平台是如何统计评分的，显得尤为重要。现有评分规则主要有两种：传统评分规则和动态评分规则。尽管评分规则的影响深远，但相关研究仍显匮乏。本研究采用仿真实验方法，对比两种规则对评论系统设计的影响。研究发现，传统评分规则在提升评论系统效率性方面通常更佳，例如加快评论数量的积累和减少尾部卖家的客户流失。动态评分规则在促进竞争公平性方面总是更有效，特别是当计分周期极短时，动态评分规则反而能推动搜索型产品更快地积累评论数量。因此，平台应根据自身的经营目标，选择适合的评分规则。

Abstract: With the prevailing of online shopping, consumers increasingly depend on online reviews for product information, particularly product ratings, which have become a key metric for assessing the performance of online sellers.Therefore, it is crucial to have a thorough understanding of the rating rules established by e-commerce platforms, specifically how ratings are calculated.Presently, there are two main rating rules: the traditional rating rule(Trad-R) and the dynamic rating rule(Dyn-R).Despite the far-reaching influence of rating rules, there is a lack of comprehensive research in this stream.This study employs a simulation experiment approach to compare the effects of the two rating rules on the design of review systems.The findings indicate that Trad-R is usually superior in enhancing the efficiency of review systems, such as accelerating the accumulation of reviews and reducing customer attrition for lower-ranked sellers.Dyn-R is always more effective in promoting competitive fairness, but especially, when its rating cycle is set to extremely short, Dyn-R can drive a faster accumulation of reviews for search products.Therefore, e-commerce platforms should select the appropriate rating rules based on their business objectives.