报告时间：2019年12月30日（星期一）14:00

报告地点：管理学院五楼1502会议室

报 告 人：卢向华 教授

工作单位：复旦大学

举办单位：管理学院

报告人简介：

卢向华，复旦大学，管理学院信息管理与信息系统系，教授，国家自然基金优秀青年基金项目获得者。卢向华博士的研究方向是互联网用户的在线行为量化实证分析及运营机制设计，通过大数据分析与实地实验等方法研究用户个人层面的行为偏好与规律，测度用户对不同市场干预机制或政策的响应效果。她在国内外高水平期刊上发表学术论文30余篇，包括Management Science, Information Systems Research, Journal of Marketing, Marketing science, Journal of MIS等。她目前已经作为负责人主持了5项国家自然基金项目及省部级研究课题与企业横向咨询课题。

报告简介：

Online micro-lending has experienced rapid growth worldwide. A key challenge in scaling up the business is managing the cost of debt collection incurred by late repayment and default. We study whether and how a platform can leverage on borrowers’ social connections through automatic social notifications in regulating repayment behavior. In collaboration with a large online micro-lending platform, we conduct a randomized field experiment to investigate the effect of social notifications targeted at different contact groups (core-circle vs. peripheral-circle). Our results show that notifying social contacts of a delinquent regarding the overdue payment significantly improves the repayment rate. Compared to the control group in which no notification messages are sent to the social contacts, notification-triggered social sanctions and social supports reduce the default rate by more than 50% in both core-circle and peripheral-circle groups. Further, we find that social notifications targeted at the peripheral-circle social contacts are only effective in the short term, its effectiveness decreases with repeated use. By contrast, social notifications targeted at the core-circle social contacts have a lasting effect.