Addressing and Benchmarking Variations in Airport Demand in the U.S. Domestic Market

Abstract

A framework quantifies and benchmarks the factors that contribute to airport demand variations for the 100 largest airports in the U.S. domestic market. First, a time series modeling approach is proposed to address and quantify factors that contribute to airport demand variations. The airport demand variation is represented by the quarterly percentile change in the number of passengers flying to and from the airport. The quarterly demand data for each airport are used, with local traffic of the airport separated from its connecting traffic. This separation allows better analysis of demand variations and avoids a portfolio effect on variation attenuation. Factors considered in the modeling approach include seasonality, financial conditions, and incidents. Next, the parameters of the estimated models for the 100 largest airports in the U.S. domestic markets are analyzed to gain more insight into how these parameters vary by airport. Several airport characteristics are considered to explain the parameter differences, which include demand level, number of operations, and airport geographical locations.

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