Modeling and Forecasting Passenger Demand for a New Domestic Airport with Limited Data

Abstract

Because adequate information on people's travel behavior is often unavailable in developing countries, demand modeling for a new airport is difficult. This study presents a simple modeling approach that uses limited aggregate information about a country to generate a forecast for passenger patronage in a new airport. The model uses aggregate time-series information on the national level and patronage at other airports to develop a gravity-type demand model for the country. The demand model incorporates the possible competition with a substitute mode, which is often the case for air travel demand in a small country. Demand for the specific new airport is then calibrated by using the parameters from this demand model and a small passenger survey. This modeling approach is applied to forecast the demand for a new airport in a divisional capital in Bangladesh, for which no regional data on gross domestic product or population are available. The modeling approach can be useful to researchers and practitioners when extensive data about air travel behavior are not available.