Freight Volume Forecasting of High-Speed Rail Express: A Case Study of Henan Province, China

To accurately assess the development potential of a high-speed rail (HSR) express in the logistics system, this study constructs a forecasting method for HSR express volume. Grey relational analysis is used to identify key influencing factors, and a multiple regression model is established to predict intercity express volume. A generalized cost model for road, HSR, and air express is developed, considering infrastructure availability and delivery timeliness. Cost differences between supply and demand sides are analyzed, and a Logit model is applied to quantify mode share, deriving HSR express volume. A gravity model allocates the volume between cities. The method is validated in Henan Province, China. Results show that: (1) Intercity express volume in China will continue growing over the next decade, with HSR forming a stable share, and Henan playing a significant role as a central hub; (2) Suppliers prefer HSR for medium-to-long distances with lower timeliness demands, while consumers prefer it for shorter, time-sensitive deliveries; (3) Lower consumer prices significantly increase HSR mode share, urging suppliers to balance cost and infrastructure investment. This method supports HSR express forecasting and promotes sustainable logistics.