报告人：南京大学 姜正瑞 教授

时间：12月17日 上午10:00-11:30

会议号：腾讯会议159 894 820

内容摘要：

In the presence of successive product generations, most consumers are repeat buyers, who may decide to purchase a future product generation before its release. Therefore, after a new product generation enters the market, its sales often exhibit a declining pattern, thus rendering traditional diffusion models unsuitable for characterizing consumers’ upgrade timing decisions. In this study, we propose an Exponential-Decay Proportional Hazard Model (Expo-Decay model) to predict consumers’ time to product upgrade. The Expo-Decay model is parsimonious, interpretable, and performs better than existing models. We apply the Expo-Decay model and three extensions to study consumers’ upgrade behaviors for a sports video game series. Empirical results reveal that consumers’ previous adoption and usage patterns can help predict their timing to upgrades. In particular, we find that consumers who have adopted the immediate past generation and those who play previous generations more often tend to upgrade earlier, whereas those who specialize in a small subset of game modes tend to upgrade later. Further, we find that complex extensions to the Expo-Decay model do not lead to better prediction performance than the baseline Expo-Decay model, while a time-variant extension that updates the values of covariates over time outperforms the baseline model with static data.

报告人简介：

姜正瑞教授是南京大学商学院营销与电子商务系教授，二级教授，博士生导师。在2019年加入南大之前，任美国爱荷华州立大学的信息系统与商业分析教授和托米讲席教授。主要研究领域是商务智能与大数据分析，其研究特色是将计算机科学研究与管理学研究有效融合，在商业数据分析、机器学习、决策支持和科技创新扩散等方向做出了重要贡献，在国际顶级期刊如  Management Science ,  MIS Quarterly ,  Information Systems Research ,  IEEE Transactions on Knowledge and Data Engineering 等发表十多篇论文。其研究成果还被应用于企业、非盈利组织和政府的实践，取得了客观的经济效益。现为国际顶尖期刊 Information Systems Research 的副主编和 Production and Operations Management 的高级主编；曾任另一顶级期刊 MIS Quarterly 的副主编，并获得该刊2016年最佳副主编奖。主持过信息系统领域多个国际性的学术会议。作为项目主持人曾收到国家自然科学基金和美国国际开发署的资助，在北美、中国和非洲从事过科研和知识传播的工作。2019年被南京市委市政府授予“南京市高层次举荐人才（A类）”的荣誉称号。