Passenger demand forecasting is essential for an airline route and network strategy planning decisions that are normally based on forecasts for several periods ahead. In today’s digital world forecasts are frequently derived with the use of modern electronic data analysis programs which are designed to store and manipulate vast amounts of data with the highest level of precision.
The research presents several methods for forecasting air passenger traffic on a state and a route aggregate levels by using a time series data and relevant economic indicators for modelling. The best fit model is identified for forecasting passenger traffic on a direct route between the two Eastern European neighboring states – Georgia and Ukraine.