SPEAKER: Xiang(Sean) Wan, Fisher College of Business, The Ohio State University

TIME/DATE: 2024年6月28日下午 3:00

CLASSROOM: 同济大厦A楼308教室 （线上腾讯会议同步）

TENCENT：317 758 043

PW：809135

ABSTRACT:

This paper examines the influence of an artificial intelligence (AI) application – facial recognition technology at airports – on both on-time performance (an objective service quality) and passenger sentiment (a subjective service quality). As for on-time performance, while facial recognition at airports has the potential to save time during check-in and boarding procedures, flight departures could be delayed due to the inaccuracy of this immature technology. As for passenger experience, while facial recognition provides a more convenient method of verifying travel documents, privacy concerns may offset the passengers’ positive sentiment on convenience. Therefore, the impacts of facial recognition on both objective and subjective service quality remain uncertain and require further empirical investigation. In this study, we exploit the first terminal-wide implementation of facial recognition in the U.S. and examine its impact on both objective and subjective measures of service quality. For objective service quality, our analysis of flight on-time status data reveals a reduction in departure delays and arrival delays but no increase in early departures or early arrivals. Interestingly, the improvement in on-time performance is smaller for flights to destinations in Asia and Africa with fewer non-white passengers, and greater for flights with larger seat capacity. For subjective service quality, we apply topic models and sentimental analyses of Twitter data, and find that overall passenger sentiment decreases after the launch of facial recognition, contrary to the improvement in the objective service quality: the on-time performance. A deeper investigation uncovers that privacy concerns emerge as a latent theme in passenger tweets, whereas the theme of convenience does not significantly increase after the launch of facial recognition.

GUEST BIO:

Dr. Wan earned his Ph.D. in Business Administration with a major in Supply Chain Management from the Robert H. Smith School of Business at the University of Maryland. During his doctoral program, he received Top 15% Teaching Awards in 2009 and 2010 at the Robert H. Smith School of Business as well as the Krowe Award for Teaching Excellence in 2010 and the Allan N. Nash Award for outstanding doctoral student in 2011.

Dr. Wan’s research interests include product and service variety management, order fulfillment, and innovative technology. His research work has been published in highly recognized journals including Manufacturing and Service Operations Management, Strategic Management Journal, Production and Operations Management, Journal of Operations Management, Decision Sciences Journal, and Journal of Business Logistics, among others.

Dr. Wan’s research has made significant impacts in academia and industry. He received the Doctoral Dissertation Award from the Council of Supply Chain Management Professionals in 2012.  Additionally, his research has been cited and discussed in practitioner articles, including  “SKU Proliferation: Too Much or Not Enough?” published at Deloitte University Press and “A Key To Entrepreneurial Success: Stick To What You Know” published at Forbes.

Furthermore, an article from the Wall Street Journal recognized Dr. Wan as one of “12 Academic Experts [Who] Make Sense of Consumer-Centric Big Data with Adaptive Analytics.”