Dynamic network relationship between transportation and urban economy: A case study of China's high-speed rail as a new transportation technology
Mingzhen Li,
Hongchang Li,
Kun Wang and
Shuohua Shen
Research in Transportation Economics, 2023, vol. 102, issue C
Abstract:
High-speed rail (HSR) stands as one of the most significant transportation technological advancements in the global railway industry over the past half-century, attracting considerable scholarly attention regarding its impact on urban economies. However, researches remain rare as to the dynamic evolution of the HSR netwok and the economic network, as well as their relationship. Our research tackles this issue by employing social network analysis (SNA) and a complex gravity model to construct China's HSR network and economic network. Furthermore, we apply the quadratic assignment procedure (QAP) and nonlinear Granger causality test to analyze the relationship between the two networks. Results reveal a significant correlation between China's HSR and economic network from 2008 to 2020, exhibiting heterogeneity in nonlinear causal relationships across different spatial scales. Notably, the strength of the relationship between the HSR netwok and the economic network follows an inverted “U” shape. This correlation is more pronounced within smaller administrative boundaries than inter-administrative regions. Additionally, the HSR netwok and the economic network in China's central and western regions tend to foster mutually reinforcing patterns of evolution. These findings shed light on the interactive processes between HSR development and economic growth in China, providing a foundation for policy formulation in emerging economies seeking to develop a new transportation technology and promote synergistic economic growth.
Keywords: HSR network; Economic network; New transportation technologies; Network relationship (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:retrec:v:102:y:2023:i:c:s0739885923001002
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DOI: 10.1016/j.retrec.2023.101360
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