Yield Optimization for Airlines from Ticket Resell

During the reservation period of some flights, the demand significantly fluctuates due to changes in the business environment. Some demand variations can hardly be anticipated by airline revenue management systems. Therefore, it often happens that the sales policy applied at a given time in a flight turns out to be suboptimal a posteriori. A mechanism of ticket buy-back can then be an interesting tool for the airlines aiming at boosting revenue from these flights. This paper addresses the main stages of a buy-back process triggered by an airline. The process includes the revenue management-based solutions to support the selection of the tickets and the computation of the proposed prices to get them back. The main contribution of this paper is a new mathematical model which optimizes airline-expected revenue from buy-back according to the probability of passenger acceptance. This model can be applied for many different compensation schemes that could be put in place by an airline to spur some of their passengers to sell back air tickets to the airline. Three of them are further analyzed. We simulate buy-back campaigns for four flights with data drawn from real operations and compare additional revenue due to buy-back, according to the selected compensation scheme. Results emphasize our intuition that business benefits can be expected from a well-automated mechanism of ticket buy-back and resell in the airline industry. Depending on the flight and demand characteristics, up to over 10% additional revenue can be expected to be added on top of the revenue obtained from a standard revenue management system on a single flight.