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.
