Correspondence: Catherine Cleophas, DS&OR Lab, Universität Paderborn, Warburger Str. 100, Paderborn 33098, Germany

¹having graduated from the University of Paderborn, Germany, with a degree in Business Computing, Catherine Cleophas now is a student of the International Graduate School of Dynamic Intelligent Systems, Paderborn. Her doctoral work is sponsored by a Lufthansa fellowship and focuses on a concept of evaluating demand forecasts for airline revenue management.

²is Head of Revenue Management Systems Development at Deutsche Lufthansa AG. He is currently in charge of a project introducing new forecasting and optimization systems. In addition, he oversees cooperations between Lufthansa and the Technical University of Clausthal, Germany, as well as the University of Paderborn.

³functions as Junior Professor since 2005 at the Decision Support & Operations Research Lab at the University of Paderborn, Germany. Her research focuses on planning for public transport with special regard to simulation and robust planning.

Received 9 March 2009; Revised 9 March 2009; Published online 12 June 2009.

Abstract

This article describes an approach to evaluating the quality of airline demand forecasting. It presents a a simulation framework that includes a detailed model for generating artificial demand. In this system forecasting methods can be compared in a stable, controllable environment. Their performance may be rated based on the overall system output in terms of revenue and bookings as well as through common error measurements. In addition, the use of a psychic forecast as a benchmark is proposed and illustrated by first results.