Bass plus BL plus seasonality forecasting method for demand trends in air rail integrated service

The fast expansion of high speed train network acts as a double-edged sword for the development of air passenger transport all over the world. An air-rail integrated service (ARIS) has been regarded as a new trend for the air passenger transport. However, the launch of ARIS involves multiple stakeholders, mainly includes airport, regional railway bureau, airlines and passengers. Thus, the passenger demand forecasting of ARIS, directly impacts on the operations of both airports and airlines, further the development of both regional transport market and economics. This paper proposed a Bass + BL + Seasonality model, which combined Bass diffusion model, disaggregate choice model, and seasonal fluctuations to forecast the passenger demand and trend of ARIS. The ARIS of Shijiazhuang Airport in China was taken as an example to verify its performance. The results showed that compared with other typical methods, the proposed Bass + BL + Seasonality model could forecast the passenger demand trend of ARIS with higher accuracy.