Impact of High-Speed Rail on Spatial Structure in Prefecture-Level Cities: Evidence from the Central Plains Urban Agglomeration, China

Abstract

The impact of high-speed rail (HSR) on urban spatial structure has attracted much attention since the 1970s. It mainly realizes the change of urban spatial structure by affecting the spatial distribution of population and economy. Based on population and industry data on 29 cities in the Central Plains Urban Agglomeration (CPUA) located in central China during 2005–2017, in this paper difference-in-difference (DID) models are utilized to explore the influence of HSR on the spatial structure of prefecture-level cities at the single/multicenter levels according to the dimensions of polycentricity and dispersion. The main conclusions are shown as: (1) HSR on the spatial structure of the CPUA has a monocentric trend, but the characteristics of different prefecture-level cities vary. Currently, agglomeration remains the dominant force of the spatial structure of the CPUA in prefecture-level cities. (2) HSR have a noticeable effect on the spatial structure of industry, whereas the influences of the HSR on the spatial structure of the population are insignificant. Its development is the result of the combined effects of many factors, including natural factors, socioeconomic factors, policies, and transportation factors. Among the controlling factors, the administrative area, economic development level, urban population, and number of research units are the critical factors having a hold on the population spatial structure of the CPUA.

Analysis of changes in the spatiotemporal characteristics of impervious surfaces and their influencing factors in the Central Plains Urban Agglomeration of China from 2000 to 2018

“…As such,the explanatory power of F3 increases in the T2 period, probably because the growth rate of per capita GDP in the CPUA is greater than the expansion rate of ISA, and urban spatial expansion lags behind economic development. Thus, cities with good traffic conditions can form competitive location advantages [ 36 ], and traffic development to a certain extent promotes the rapid expansion of urban lands [ 37 , 38 ], and the planning and construction of the Central Plains City Cluster “meter” type high-speed railway has promoted the rapid expansion of urban construction land. The explanatory power of both the T1 and T2 periods is small, which also indicates that the region's traffic has reached a certain scale and is more mature, and its incremental spillover effect on urban spatial growth will further diminish.…”

“…Economic prosperity and development provide a source of funding for medical construction that can support the construction and development of medical institutions, which may account for the increased explanatory power of F3 interacting with the other factors for ISA changes in the CPUA. By improving urban transportation, HSR promotes population mobility, increases employment opportunities, and boosts population growth in cities along the route [ 36 ], which may be the reason for the more prominent performance of F4 in the interaction. By improving urban transportation, HSR promotes population mobility, increases employment opportunities, and boosts population growth in cities along the route, which may be the reason for the more prominent performance of F4 in the interaction.…”

A study on the evaluation of competitiveness in the aviation logistics industry cluster in Zhengzhou

“…Secondly, advances in technology such as e-commerce, big data, artificial intelligence, and vehicle networking accelerate the construction of logistics information system platforms, promote the intelligent and networked development of logistics equipment, and improve the efficiency of logistics industry and supply chain operations. Therefore, technological innovation constitutes the "engine" of core competitiveness [23][24][25][26][27] .…”

“…This iterative process ensures that the evaluation captures the nuances of each level and provides a comprehensive understanding of the overall competitiveness of aviation logistics industry clusters [26][27][28][29][30] .…”

Spatiotemporal Linkages between Administrative Division Adjustment and Urban Form: Political Drivers of the Urban Polycentric Structure

“…However, the coefficient of GDP is negative, which may be related to the different economic levels of cities. Cities usually move towards monocentric development to promote agglomeration economies when the economic levels are low [74]. POLY is usually adopted at higher economic levels to solve the problem of agglomeration diseconomies.…”