Reservations forecasting in airline yield management

Abstract

This report shows the application of Regression Analysis in reservations forecasting in airline yield management. The first three chapters highlight the need for yield management and the automation of seat inventory control. The seat inventory control problem is related to the determination of an optimal allocation of seats among the various fare classes being offered in a flight so as to maximize revenues. In order to determine such optimal seat allocation, forecasts of final bookings need to be made. Forecasting alternatives are presented in this report. An example of application of Time Series Analysis is given as an alternative in providing such forecasts. Results obtained via Time Series Analysis were not encouraging enough in providing acceptable estimates. Regression Analysis is also presented as a forecasting tool. Although regression models were developed for each market, a generalized model structure was thought to be preferable in view of the reduction of modeling efforts, data handling and model specification, that are needed for forecasting final bookings for all markets/flights/classes. A general structure model is presented in this thesis as the result of the search for structural behavior across markets and flights. Regression Analysis results are presented for a set of five citypairs, one flight in each directional market, i.e. ten flights in total. These results evidenced that a general structure model via regression analysis can indeed be used in the forecasting module of an automated seat inventory control system, and thus provide better estimates of final bookings when compared to Time Series Analysis or historical averages.