Revenue impacts of demand unconstraining and accounting for dependency

Abstract

Accurate forecasts are crucial to an airline revenue management system. Historical demand data for two fare classes used for forecasting in an airline are often censored and correlated. In this article, we propose a methodology that takes into account both censorship and correlation of demands. We then study its impact on the expected revenue and compare it with three standard methodologies available in the literature by using extensive simulation. Our results show that the opportunity cost of neglecting demand censorship is upto 1 per cent whereas that for neglecting the dependency of demands can be of the order of 2 per cent. Consideration of both truncated demand and dependency between fare classes can lead to a significant (of the order of 2.5 per cent) revenue increase.