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.

The history of unconstraining models in revenue management

“…In the early 2010s, Karmarkar et al (2011) looked at two fare classes, and included correlation of demand between the classes when estimating the uncensored demand and found the improved demand estimates generated simulated revenue increases of 1-2 per cent. Guo et al (2011) derived formulas for EM and PD when nominal demand is assumed to follow distributions such as Gamma, Weibull, Exponential and Poisson.…”

A Demand Estimation Algorithm for Inventory Management Systems Using Censored Data

“…Empirical studies show that an amount between 45% and 84% of demand can be substituted [5,6]. In [7], it is showed that the cost of ignoring demand dependency is 1% higher than ignoring censorship. To illustrate this problem, suppose that an online library offers 2 types of books for each ISBN: 1-new book, 2-used books and their quantities are 30 for new books and 15 for used books.…”