Exploring the Driving Forces to Business and Leisure Passengers Air Travel Demand

抄録

This study employed back-propagation neural networks (BPN) to explore what the most influential variables are to drive business and leisure air passenger travel from Japan to Taiwan. The variables were systematically identified, evaluated and analyzed in detail. The results reveal that some factors influence both leisure and business air passenger transport, and the others only one of them. Flights from Tokyo to Taipei and Average hotel rate in Taiwan are the two most important factors for forecasting the demand of leisure air passenger transport, while variables related to business activities have more effect on the demand forecast of business air passenger transport. By using BPN, a forecasting model that considers actual market segments was established, and the results show that it is an accurate tool to forecast air transport demand. In addition, the valuable data obtained from the model may be a good reference for air carriers and aviation authorities.