时间：2018年11月2日(周五) 10:00

地点：松江校区2教220室

主讲人：高宝俊武汉大学经济与管理学院教授

主持人：陈文波副教授

主题：The Causal Inference of Online Reputation on Sales: A Regression Discontinuity Design

讲座摘要：

In this research notes, based on a setting of online reputation system, we demonstrate various issues related to using regression discontinuity design (RD) to do causal inference, meaning to study whether for a given vendor, an increase in its online reputation score causes, instead of being associated with, an increase on its online sales. In the e-commerce platform, sellers are typically assigned into different reputation levels based on their original continuous reputation scores, resulting in discontinuity in reputation and allowing a regression discontinuity (RD) design setting. Based on data from one of the largest crowdsource website in China, we find that given everything else be the same, on average, sellers with one extra reputation level improvement enjoys a 32.5% increase in their sales. The RD required manipulation test indicates that both the density of the sales and various other shop related attributes show no discontinuity. Falsification test also indicates that the impact of reputation on sales holds only at true threshold. Further cross-sectional analysis show that the effect is stronger for seller with relative low reputation, owned by individual person, without the platform VIP membership or vendors not participating in the consumer guarantee program. This is consistent with the argument that new and unknown sellers depends more on the reputation system to improve their sales, offering further corroboration to our results.

嘉宾简介：

高宝俊, 武汉大学经济与管理学院教授，研究方向为商业大数据分析、信息系统与电子商务。主要关注如何基于海量结构化和非结构化数据，利用机器学习和深度学习算法将文本数据结构化，建立计量经济模型进行因果推断。在Decision Support Systems, Tourism Management, IEEE Transactions on Systems, Man, and Cybernetics: Systems,  Information & Management,  Electronic Commerce Research and Applications等国际重要期刊发表十余篇论文。

（承办：信息管理与决策科学系，科研与师资发展办公室）