报告人：美国俄亥俄州立大学万翔 副教授

时间：2022年3月9日(周三)21:00-22:30

腾讯会议号：888 204 558

报告人简介：

万翔，博士，现任美国俄亥俄州立大学费舍尔商学院副教授，主要研究方向包括供应链管理、产品和服务多样化管理、库存管理、供应链的协调合作和科技创新；其相关科研成果发表在Manufacturing & Service Operations Management、Strategic Management Journal、Production and Operations Management、Journal of Operations Management、Journal of Business Logistics等国际知名学术期刊。万翔教授被华尔街日报评为12个供应链大数据应用专家之一，现任Decision Sciences和Journal of Operations Management副主编。

报告内容简介：

We explore the influence of an artificial intelligence (AI) application in the airline industry: facial recognition at airports on flight on-time performance and passenger sentiment. Implementing facial recognition at airports has two potential benefits to passengers: time-saving and travel convenience.The contactless technology speeds up the curb-to-gate process and generates convenience for passengers by reducing the travel document requirements. However, there are some uncertainties associated with these potential benefits. First, the time-saving of document checks at check-in, baggage drop, security check, and boarding may not be successfully transferred to better on-time performance. If not, passengers may board quicker but wait in an airplane longer for departures. Second, some passengers may be concerned about the private information used by the facial recognition technology and resistant to it. In this study, we exploit the first terminal-wide implementation of facial recognition in the U.S. Our results suggest that facial recognition reduces departure and arrival delays of flights but does not increase early departure or early arrivals. This improvement on on-time performance is larger for flights on monopoly routes and flights with larger seat capacity. Meanwhile, the overall passenger sentiment decreases after facial recognition. We unveil the mechanism that increases in passengers' negative sentiment due to the concern on privacy leakage is greater than their positive sentiment through improved on-time performance and travel convenience. These findings offer an understanding of facial recognition implementation and provide guidance toairlines, airport managers, and policymakers that consider implementing curb-to-gate biometric terminals.

承办：管理科学与物流系、科研与学术交流中心