Fair adjustment strategies for airline revenue management and reservation systems

Abstract

With the growth of Low Cost Carriers (LCC) and their use of simplified fare structures, the airline industry has seen an increased removal of many fare restrictions, especially in markets with intense LCC presence. This resulted in "semi-restricted" fare structure where there are homogenous fare classes that are undifferentiated except by price and also distinct fare classes which are still differentiated by booking restrictions and advance purchase requirements. In this new fare environment, the use of traditional Revenue Management (RM) systems, which were developed based on the assumption of independence of demand of fare classes, tend to lead to a spiral down effect. Airlines now have to deal with customers who systematically buy the lowest fare available in the absence of distinctions between the fare classes. This result in fewer bookings observed in the higher fare classes, leading to lower forecast and less protection of seats for the higher yield passengers. This thesis describes Fare Adjustment, a technique developed for network RM systems, which acts at the booking limit optimizer level as it takes into account the sell-up potential of passengers (the probability that a passenger is willing to buy a higher-fare ticket if his request is denied).

(cont.) The goal of this thesis is to provide a more comprehensive investigation into the effectiveness of fare adjustment as a tool to improve airline revenues in this new environment by 1) extending the investigation of the effectiveness of fare adjustment with standard forecasting to leg-based RM systems (namely EMSRb and HBP) and also a mixed fare structure where different fare structures are used for different markets, and 2) looking at the alternative use of fare adjustment in the reservation system. Experiments with the Passenger Origin-Destination Simulator demonstrate that RM Fare Adjustment with standard forecasting can improve an airline's network revenue by 0.8% to 1.3% over standard revenue management methods. In particular, RM Fare Adjustment reduces the aggressiveness of path forecasting through the lowering of bid prices as it takes into account the risk of buying-down. Simulations of Fare Adjustment in the Reservation System also showed positive results with revenue improvement of about 0.4% to 0.7%.