Application of Discrete Choice Models in Forecasting the Number of Air Trips: Case Study of Tehran Imam Khomeini Airport

The role of air transportation in development and its impact on the economy of the country has made transportation demand forecasting interesting to planners in the past decades. In this research, the application of discrete choice models in forecasting air trips is considered and a binary logit model for the case study of Imam Khomeini airport is calibrated using maximum likelihood method taking into account the economic and social characteristics of passengers. Result of the model calibrated based on the data gathered from 1280 air passengers at Tehran Imam Khomeini airport, show that effective socio-economic factors in air trip generation, has a decreasing order: 1- income greater than 2.5 million Tomans, 2- trip purpose, 3- income from 1.5 to 2.5 million Tomans, 4- income from 1 to 1.5 million tomans, 5- age, 6- male education level and 7- car ownership.