2021年7月12日下午，现代供应链管理研究院第五十六期学术论坛如期举行，本次论坛采用线上方式召开。本次论坛的主讲人是新加坡国立大学商学院副教授何龙，其报告题目为“Crowd-starting a Shared (Shuttle) Service with Customer Engagement”。
何老师分享结束后，参与讲座的观众向其提出了问题，何老师依次进行了详细地解答。未来，我院会继续努力为各位学者提供高质量科研交流平台建设，促进学者间的交流讨论，从而推动相关研究的发展。
【摘要】
The recent development of smart-city operations improves social efficiency and welfare. Meanwhile, new business models and services with increasing customer engagement are becoming popular. In urban mobility, the shared shuttle service is emerging as an intermediate mode between public transport and ride-sharing services. In particular, platforms can offer new shared shuttle services based on customer suggestions in a crowd-starting manner. This new interaction reveals some information about customer needs, meanwhile poses a significant challenge in the service design for the platform–how to trade-off between service coverage that aims to share the service with more customers and service quality that aims to meet one’s personal needs to boost customer adoption. The crux of the problem is to strike a balance in this trade-off by leveraging optimization techniques and understanding how the information from customer suggestions can further lead to a better service design. To this end, we propose a service design optimization model to maximize the expected adoptions. We first employ a non-parametric preference list model to characterize how customers will respond given different service attributes and how customer suggestions are related to the responses. We then quantify the value of information from customer suggestions and investigate its relationship with information gain. Moreover, for practical implementation, we employ isotonic regression to calibrate the adoption probabilities and propose a modified approach with shrinkage for the small-data regime. Finally, we conduct a case study for the shared shuttle service and discuss practical insights, e.g., when it is beneficial to encourage customer engagement.
【主讲人简介】
Long He is an associate professor in the Department of Analytics & Operations (DAO) at NUS Business School, National University of Singapore. He received his Ph.D. in Operations Research from the University of California, Berkeley, and his B.Eng. in Logistics Management and Engineering from HKUST. His current research involves using data-driven approaches to address problems in smart city operations (e.g., vehicle sharing, last-mile delivery) and supply chain management. This line of research has been recognized with the M&SOM Journal Best Paper Award and Transportation Science & Logistics (TSL) Best Paper Award from INFORMS.
撰稿人：刘昱含
审核人：张颖
