Spatiotemporal evolution patterns of railway freight supply and demand coordination at provincial scale in China based on geographically weighted regression
To investigate the factors influencing the coordinated development of railway freight supply and demand and its spatiotemporal evolution, this study constructs an index database of supply and de-mand coordination, encompassing 19 demand-side and 17 supply-side factors based on railway freight statistical data from 31 Chinese provinces in 2010, 2015, and 2020. After screening the influencing factors using the correlation coefficient and coefficient of variation methods, the entropy weight method is applied to determine weights and calculate provincial coupling coordination degrees. Through the Geographically Weighted Regression (GWR) model, a spatiotemporal analysis model for railway freight supply and demand coordination is developed to explain the regional variations and evo-lution patterns in China's provincial railway freight coordination. And an obstacle degree model is pro-posed to identify the primary constraints on the development of railway freight supply and demand co-ordination. Results show that during the sample study period, the agglomeration in the spatial distribu-tion of railway freight supply and demand coordination, with influencing factors exhibiting spatial non-stationary characteristics. A spatial shift and differentiation of the gravity center are observed, with higher coupling coordination in the Northeast and North China regions and lower coupling coordination in Western China. Railway freight turnover and freight volume are the key obstacle factors affecting the supply and demand coordination development. These findings provide a theoretical foundation for optimizing the railway freight network and promoting coordinated freight development.
railway freight transportationsupply and demand analysiscoupling coordinationGWRspatiotemporal evolution
万方数据
维普
