喻园管理论坛2020年第39期(总第656期)
演讲主题: Effect of the Rounded Rating Display on Online Rating and Review Behavior
主 讲 人: 刘 唱，香港中文大学商学院信息系统专业博士生
主 持 人: 赵学锋，管理科学与信息管理系教授
活动时间: 2020年12月28日（周一）15:00-17:00
网络直播平台:腾讯会议，会议ID：510 780 222
主讲人简介：
刘唱，女，1996年生，2016年本科毕业于威尼斯欢乐娱人城·首页信息管理与信息系统专业，现为香港中文大学商学院信息系统专业博士生。主要研究领域包括互联网用户行为和口碑传播，人工智能，社交媒体和社会网络，大数据分析和价值挖掘等方面。主要研究方法包括数据挖掘，深度学习，自然语言处理，社会网络分析，应用计量经济学等。以一作及通讯作者身份在Pacific Asia Conference on Information Systems (PACIS)上发表会议论文2篇。受邀参加PACIS，SCECR（Statistical Challenges in eCommerce Research），ICEC（International Conference on Electronic Commerce）等国际学术会议共6次。现有数篇论文正在Information Systems Research（UTD24），Journal of Marketing（UTD24）等期刊审稿中。
活动简介：
As online review platforms have allowed people to easily access others’ opinions, potential consumers use the information displayed on these platforms to form pre-purchase expectations. In order to help consumers quickly categorize service providers into multiple levels (such as the 5-star categorization), it is now common for platform providers to display the rounded average rating. However, this rounding strategy may create a discrepancy between pre-purchase expectations and the experienced true quality when the displayed rating is different from the true average rating. Such a discrepancy may affect the consumer’s satisfaction level, which would eventually influence subsequent rating decision and review behavior. This study aims to examine the causal impact of the display of the rounded rating on subsequent rating decisions and the provision of emotional text in a subsequent online review, especially when the displayed rating differs from its true average. Using online review data collected from Yelp, we utilize a regression discontinuity design by taking advantage of Yelp’s rounded rating display. Our primary results suggest that a rounded-up rating (compared with a rounded-down rating) leads to a sharp decrease in subsequent ratings, as well in as the provision of pleasant emotions, but a sharp increase in the provision of unpleasant emotions. Furthermore, we examine the moderating effect of prior reviews’ rating dispersion and information diversity. When prior ratings are consistent, or when the content in prior reviews covers diverse topics, the main impact of the displayed rating would be intensified.
