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Abstract
A comprehensive review of airport choice modeling studies is presented in this paper, highlighting
the key determinants of passenger preferences. Empirical research presented which models
using binary logistic regression in the likelihood that airline travelers in the Fargo-Moorhead
Metropolitan Statistical Area will not use the local airport, but instead use the competing major hub
airport in Minneapolis-St. Paul, located 250 miles away as a viable origin airport. Moreover, this
study investigates whether collecting empirical data from local travel agents may perhaps allow
airport planners and airport managers to identify important passenger choice behaviors without
incurring the added time and expense of administering formal passenger surveys. This study found
that it is possible to obtain useful data from travel agents at significantly less time and effort. The
significant factors obtained from the regression analysis were trip purpose, trip duration, number
of connections, and airline.