A Multivariate Poisson Model of Consumer Choice in a Multi-Airport Region
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Abstract
Using the results of a unique telephone survey the frequency of consumer flights from airports in a multi-airport region are modeled using a multivariate Poisson framework, the parameters of which were estimated using a latent variable application of the expectation maximization algorithm. This offers a different perspective since other work on airport choice uses the results of airport intercept surveys that capture only a single choice per respondent, whereas the data from the phone survey is count data for the airports in the study. An airport’s own-distance had the expected negative impact on mean usage of the airport, although the cross effects were somewhat mixed. Ticket price differences between airports were not always statistically significant. Mean usage was found to be increasing in income for PHL, but was decreasing for the other airports, reflecting the increasing value of respondents’ time as their income rises. If the destination of flights is domestic (international) then the result is to increase usage of PHL, BWI and EWR (JFK). Except for JFK, if the purpose of travel is mostly pleasure then it results in more travel from JFK and less from the other three airports. The availability of a low cost carrier would result in more frequent travel.
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