Simulated revenue impact of a new revenue management strategy under the assumption of realistic fare data

Most revenue management allocation models require inputs of the revenue value associated with the bookings expected in each price class. This paper examines the impacts of more realistic fare value assumptions on the revenue performance of a commonly used unit allocation optimisation model (EMSR) and a new heuristic decision rule, called Leg Bid Price. Typical fare data for airlines, hotels, cruise lines and rental car companies show that: (1) the prices in each fare class follow a probability distribution, rather than the typical assumption of a single fare value, and (2) the average fare values across price classes do not always follow the proper hierarchical order. The revenue performance of this new threshold approach was compared on a single leg. Simulation analysis of many different scenarios, using actual cruiseline data, are used to show that the new decision rule can take advantage of the variability of actual price values around the mean price values and fare inversions to generate a significant revenue improvement over EMSR (10–15 per cent).