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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Heralded as the single most important factor effecting revenue management, demand forecasting is neither simple in concept nor practice. Using the airline industry as an illustrative example, we begin by tracing how demand models have been influenced by data availability, computational limitations, optimization models, user requirements, and disagreements about the fundamental nature of demand itself. In doing so, we establish a foundation for examining a demand model that provides an analytical solution to a perceived industry problem arising from the cyclic interaction of forecasting and optimization. Computational results are presented demonstrating the potential for substantial revenue loss when applying a demand model that doesn't coincide with consumer behavior. A property of robust demand models for revenue management applications is proposed, and research directions with practical applicability are discussed.
