Competition in Multi-Airport Regions: Measuring airport catchments through spatial interaction models

The paper makes use of a novel dataset of the surface access flows of passengers departing from the four main airports surrounding London to construct a spatial interaction model for the region. This model explains the spatial variability in the flows through four separate components being [1] spatial separation between the origin of the flow and the destination airport, [2] the demand characteristics at the origin, [3] the attractiveness of the service offered by the airport, and [4] the presence of intervening opportunities. A spatial econometric approach is taken in the modelling to account for the presence of spatial dependence in the data.

The output of the model reveals a strong distance decay effect, where the level of interaction between origins and airports displays a negative spatial gradient. Each of the four airports dominate passenger flows in their immediate vicinity, with the market in the region being hotly contested in central London. All four components of the model are useful in explaining spatial variation in passenger flows, demonstrating the efficacy of this approach in considering how airports source their demand in a Multi-Airport Region. The performance of the model is superior when considering passenger surface access flows for scheduled flights, while the explanatory power is reduced for flows associated with chartered flights. Having verified the applicability of the model, it is possible for policy makers to utilise the approach to consider such issues of expanding, limiting or reducing capacity at existing airports in the region, establishing new airport facilities, and the effect of population growth on the geographic form of airport demand.