Airport Demand Forecasting for Long-Term Planning

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Decisions on expanding airport capacity are often controversial. Environmental impacts mean airport planning decisions are subjected to thorough public scrutiny even when financed by private investors. Where public funds are to be invested, issues of competition between airports and between the regions they serve can be as important as efficient use of public funds. Demand forecasts are central to the case for investment.

Air passenger markets are highly dynamic and strongly influenced by the regulatory environment. Markets that have been de-regulated have seen rapid growth as prices fell and new, low-cost business models emerged. Liberalisation also stimulated re-organisation of network services with concentration of demand on a few hub airports. Demand for air services increases rapidly as incomes rise, but the market is not homogenous and understanding the drivers of each market is critical. Runway assets are relatively long lived and planning for the long term has to account for the risks entailed by these dynamics.

This report reviews the state of the art in forecasting airport demand. It focuses particularly on addressing demand risk, passenger behavior and uncertainty and discusses how to make more effective use of such analysis in planning decisions.




Choice models and contemporary airport demand forecasting

International Transport Forum

During the last two decades, as the air transport industry has changed rapidly, traditional data sources have struggled to keep up and continue to reflect the true state of the industry. This paper describes an alternative way of forecasting air transport demand that addresses these data issues and presents alternative data sources. It explains the econometric system approach developed by MKmetric which includes a new mathematical framework that reflects the consumers’ decision process and overcomes some of the shortfalls of traditional models.

The system approach developed is based on the classical 4 step procedure, namely generation, distribution, modal split and assignment. However it models the interdependent choices such as modal choice, airport and route choice, access and egress simultaneously. The model mirrors consumer behaviour using logistic functions whereby the mathematical form is flexible so that thresholds can be included. The elasticities of consumers to characteristics of the alternatives (e.g. time, cost, frequency, alliance) allow measurement of demand effects from changes in the transport system, e.g. services, infrastructure.

The approach uses dynamic, rather than fixed, airport catchment areas. These are a function of the attractiveness of the alternative transport opportunities available for each trip. Demand forecasts for an airport or a route consider the competitors endogenously. In addition, new methods are proposed to compute network impedance, which reflects the attractiveness of each alternative based on the infrastructure networks of all modes. The full potential of this approach is demonstrated by some examples.


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