期刊
TRANSPORT POLICY
卷 116, 期 -, 页码 315-326出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.tranpol.2021.12.014
关键词
High-speed rail (HSR); City economic network; Generative network model (GNM); Urban and regional planning; Yangtze River Delta (YRD)
资金
- National Natural Science Foundation of China [71704134]
- Chinese National Funding of Social Sciences [18ZDA043, 19VDL001]
- National Social Science Foundation of China [18ZDA043, 19VDL001]
This study analyzed the impact of city economic development on the formation of HSR network using a generative network model (GNM) and social network analysis, focusing on 20 cities in the Yangtze River Delta region of China. The results showed that GNM could simulate the observed City-HSR network with satisfactory performance, and city population should be given priority when planning new HSR lines. This study proposed a research framework for exploring the interaction between the city economic network and HSR network and provided data-driven analyses for regional transport policy.
As an essential transportation infrastructure, high-speed rail (HSR) plays an important role in improving con-nections and economic efficiency among cities which has been proved by numerous studies. In turn, the cities' economic development levels also influence the planning and construction of HSR. Several qualitative studies pointed out that some failed projects of HSR investment were attributed by the neglect of urban economic factors. However, there lacks a quantitative understanding of which specific city economic factors influence the formation of HSR networks and to what extent. This study intends to answer the questions by analyzing the formation process of HSR network under the influence of city economic development using a generative network model (GNM) and social network analysis. It focused on 20 cities in the Yangtze River Delta region of China and constructed a City-HSR network that coupled the city economic network and HSR network. Then, a GNM method considering transitivity, distance, boundary effect, and population, was used to generate simulated networks similar to the City-HSR network. The similarities in network metrics between the City-HSR network and the GNM networks were compared by the quadratic assignment procedure (QAP) method to determine the optimal GNM network. A sensitivity analysis was further conducted to investigate the impacts of the factors on the formation of HSR network. The results showed that GNM could simulate the observed City-HSR network with satisfactory performance, and the city population should be given priority when planning new HSR lines. This study proposed a research framework for exploring the interaction between the city economic network and HSR network and provided data-driven analyses for regional transport policy.
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