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.
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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.
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.
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Cleophas, C., Frank, M. & Kliewer, N. Simulation-based key performance indicators for evaluating the quality of airline demand forecasting. J Revenue Pricing Manag 8, 330–342 (2009). https://doi.org/10.1057/rpm.2009.17
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DOI: https://doi.org/10.1057/rpm.2009.17