Dispersed fares within a fare class: How can the reality be harnessed?

Most revenue management seat allocation models require inputs of the revenue value associated with the bookings expected in each fare class. This paper examines the impacts of more realistic fare value assumptions on the revenue performance of a commonly used seat allocation optimisation model (EMSR) and a new heuristic decision rule, called dispersed fare rule (DFR). Typical fare data for airlines, hotels, cruise lines and rental car companies show that the fares in each fare class follow a probability distribution, rather than the typical assumption of a single fare value. The revenue performance of this new DFR approach on a single leg is compared. Simulation analysis of many different scenarios is applied, using actual airline data, to show that the new decision rule can take advantage of the variability of actual fare values around the mean fare values to generate a significant revenue improvement over EMSR (2–6 per cent).