Description:

Bio:

Professor Liying Song is a Professor at Beijing Jiaotong University, specializing in multimodal transportation. With a Ph.D. from Univeristy of Southampton, Professor Sng has published 20+ papers in academic journals and led 10+ national research projects. Her work focuses on freight transportation, with applications in sea-rail intermodal transportation network modelling. She serves as a reviewer for IEEE ITS Society and mentors 4+PhD students and 12+ master students.

Abstract:

This research explores how airlines can dynamically optimize the inventory of various products under the classic assumption of independent demand to maximize revenue. In revenue management research, it is crucial to first assume a passenger demand model, specifically whether passenger choice behavior during the ticket purchase process is influenced by external factors. When passenger demand is entirely unaffected by the availability of other similar products, passengers will choose only their preferred product, which is referred to as independent demand. Under this demand assumption, airlines only need to optimize the supply quantity of their own products. Compared to adjusting ticket prices, airlines' distribution capabilities are more constrained by the real-time performance of information systems and technical architecture, making it easier to control the supply quantity of different fare classes, i.e., to optimize inventory control. In fact, quantity-based revenue management has already been widely adopted in the airline industry. Essentially, both price-based and quantity-based revenue management serve similar purposes; if an airline offers multiple fare classes on a specific origin-destination (OD) pair, ceasing to offer discounted products on that OD effectively narrows the price range, thereby increasing the average price. This research improves upon the classic inventory control optimization model and tests its optimization effects through simulation cases.