【Mingli lecture 2022, Issue 10】

Speaker: Associate Professor Wan Xiang, Ohio State University

Time: March 9, 2022 (Wednesday) 21:00-22:30

Tencent conference number: 888 204 558

Brief introduction of the reporter:

Wan Xiang, Ph.D., is currently an associate professor at the Fisher School of Business, The Ohio State University. His main research interests include supply chain management, product and service diversification management, inventory management, supply chain coordination and cooperation, and technological innovation; his relevant scientific research results have been published in Manufacturing & Service Operations Management, Strategic Management Journal, Production and Operations Management, Journal of Operations Management, Journal of Business Logistics and other internationally renowned academic journals. Professor Wan Xiang was named one of the 12 experts in supply chain big data application by The Wall Street Journal, and is currently the associate editor of Decision Sciences and Journal of Operations Management.

Introduction to the report:

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.

Organizer: Department of Management Science and Logistics, Research and Academic Exchange Center