Unraveling the dynamic changes of high-speed rail network with urban development: Evidence from China

Abstract

Previous studies have used complex network theory to examine the characteristics of China's High-Speed Rail (HSR). Nevertheless, little attention is paid to China's HSR network's dynamic evolution and the coevolution of node attributes and embedded structural characteristics. Our study builds China's HSR network using a complex network approach and spatial analysis technique to address this issue. Additionally, we employ a stochastic actor-oriented model (SAOM) to properly decompose the three types of effects on the generation of China's HSR network (i.e., network structure, attribute-based similarity, and exogenous control variables). This study discusses the underlying hypotheses and indicates that 3-cycles is a critical structural factor for the formation of China's HSR network. In terms of the effects of attribute-based similarity, cities with similar Gross Domestic Product (GDP) and geographical proximity are essential nodal drivers for the evolution of the HSR network. Notably, the administrative rank of cities exhibits a significantly negative driving force and a alter effect. These findings shed light on the interactive process of urban regional development and the dynamic evolution of the HSR network, assisting the central and local governments in enacting and implementing appropriate HSR planning policies, ultimately achieving effective urban planning and management.