Comparing passenger flow and time schedule data to analyse High-Speed Railways and urban networks in China

Haoran Yang, Martin Dijst, Patrick Witte, Hans van Ginkel and Jiao’e Wang
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Haoran Yang: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China; Utrecht University, The Netherlands
Martin Dijst: Utrecht University, The Netherlands; LISER, Luxembourg
Patrick Witte: Utrecht University, The Netherlands
Hans van Ginkel: Utrecht University, The Netherlands
Jiao’e Wang: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China

Urban Studies, 2019, vol. 56, issue 6, 1267-1287

Abstract: China’s High-Speed Railways (HSR) network is the biggest in the world, transporting large numbers of passengers by high-speed trains through urban networks. Little is known about the analytical meaning of the use of two types of flow data, namely, time schedule (transportation mode flow) and passenger flow data, to characterise the configuration of urban networks regarding the potential spatial effects of HSR networks on urban networks. In this article, we compare HSR passenger flow data with time schedule data from 2013 in China within the same analytical framework. The findings show great differences in the strength of cities and links generated using the two different types of flow data. These differences can be explained largely by the socio-economic attributes of the cities involved, such as tertiary employment, GDP per capita, the cities’ topological properties (closeness centrality) in HSR networks and institutional factors (hub status), especially for the difference in link strength. The strength of first-tier cities in China with high socio-economic performance and the HSR links connecting core cites and major cities within respective regions tends to be underestimated when using time schedule flows compared with passenger flows. When analysing the spatial structure of HSR and urban networks by means of flows, it is important for urban geographers and transportation planners to consider the meaning of the different types of data with the analytical results.

Keywords: China; High-Speed Railways (HSR); passenger flow; time schedule; transport; urban networks; urbanisation and developing countries; 中国; 高é“; 客æµ; 时刻表; 交通; 城市网络; åŸŽå¸‚åŒ–å’Œå ‘å±•ä¸­å›½å®¶ (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:urbstu:v:56:y:2019:i:6:p:1267-1287

DOI: 10.1177/0042098018761498

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