Comparing passenger flow and time schedule data to analyse High-Speed Railways and urban networks in China (Record no. 11404)
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| fixed length control field | 02306nab a2200253 4500 |
| 005 - DATE & TIME | |
| control field | 20210226150052.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210226b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Yang, Haoran |
| 245 ## - TITLE STATEMENT | |
| Title | Comparing passenger flow and time schedule data to analyse High-Speed Railways and urban networks in China |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc | Sage |
| Date of publication, distribution, etc | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pages | Vol 56, Issue 6, 2019 : (1267-1287 p.) |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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.<br/> |
| 650 ## - Subject | |
| Subject | China |
| 650 ## - Subject | |
| Subject | time schedule |
| 650 ## - Subject | |
| Subject | passenger flow |
| 650 ## - Subject | |
| Subject | High-Speed Railways (HSR) |
| 700 ## - Added Entry Personal Name | |
| Added Entry Personal Name | Dijst, Martin |
| 700 ## - Added Entry Personal Name | |
| Added Entry Personal Name | Witte, Patrick |
| 773 0# - HOST ITEM ENTRY | |
| Host Biblionumber | 11188 |
| Host Itemnumber | 15499 |
| Place, publisher, and date of publication | sage, 2019. |
| Title | Urban studies |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1177/0042098018761498 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Articles |
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| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
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