报告人学术简介
 江波，美国明尼苏达大学博士，上海财经大学信息管理与工程学院副院长（主持工作）；前沿交叉书院院长；国家级青年人才；从事运筹优化、收益管理等方向的研究。成果发表于管理科学、运筹优化的国际顶级期刊《Management Science》、《OperationsResearch》、《Mathematics of Operations Research》、《Mathematical Programming》、《SIAM Journal on Optimization》。获得了中国运筹学会青年科技奖、上海市自然科学奖二等奖、宝钢优秀教师奖等荣誉。主持多项国家自然科学基金项目包括自科重大项目课题。

报告内容
 “Hidden City Ticketing” (HCT) is a strategy where customers book flights with layovers at their intended destinations and skip the final leg of the journey. Empirical studies on airfare data have shown that HCT chances are very prevalent (about 15%–25%) in airline pricing. In this paper, we investigate the impact of HCT on airline revenue and discuss if the airline should eliminate all HCT chances from its price to achieve higher profit. We use a choice-based network revenue management model to characterize the airline’s dynamic pricing problem. As airlines may penalize customers who purchase HCT by canceling frequent flyer miles and banning future travel with the airline, we capture customers’ concerns about the risks of HCT through a choice model. Our analysis shows that adjusting prices to completely eliminate HCT chances may overly constrain the pricing strategy, and it harms the airline revenue more than customers’ HCT purchase behavior. Furthermore, the impact of HCT is two-sided: While HCT can erode the airline’s revenue, it can also boost revenue in some cases. In the worst case, if customers purchase HCT, the airline’s revenue can be half of what it would be if customers don’t purchase HCT. In the best case, the airline’s revenue in the case customers purchase HCT can be twice that of the case where customers do not purchase HCT. Furthermore, the worst-case and best-case revenue bounds are both tight.