IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i6p1193-d1165582.html
   My bibliography  Save this article

Spatial-Temporal Distribution and Coupling Relationship of High-Speed Railway and Economic Networks in Metropolitan Areas of China

Author

Listed:
  • Guojie Ma

    (School of Statistics, Faculty of Economics and Management, East China Normal University, Shanghai 200062, China)

  • Jinxing Hu

    (School of Business Administration, Faculty of Economics and Management, East China Normal University, Shanghai 200062, China)

  • Riquan Zhang

    (School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, China)

Abstract

The planning of urban transportation infrastructure and land-related policies has a significant impact on the living conditions of urban residents and socio-economic development, particularly in emerging economies. As urbanization continues to advance, Metropolitan Areas (MAs) have become crucial for achieving industrial coordination, functional complementarity between cities, and integrated regional development. Applying Social Network Analysis (SNA), the gravity model, and Quadratic Assignment Procedure (QAP) analysis, this study investigated the spatial-temporal distribution patterns of High-Speed Railway (HSR) networks and economic networks in MAs in China and the dynamic coupling relationship between these two networks. The findings revealed that, although core cities in the Yangtze River Delta MA in China exert varying degrees of radiation and driving effects on the economic development of surrounding cities, the overall development remains immature with a noticeable disequilibrium phenomenon. The coupling relationship between the HSR networks and the economic networks also differs significantly among different MAs. It is expected that the findings and suggestions of this study will contribute to the improvement of urban planning and governance and facilitate coordinated development between urban transportation infrastructure and the economy in emerging economies.

Suggested Citation

  • Guojie Ma & Jinxing Hu & Riquan Zhang, 2023. "Spatial-Temporal Distribution and Coupling Relationship of High-Speed Railway and Economic Networks in Metropolitan Areas of China," Land, MDPI, vol. 12(6), pages 1-23, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1193-:d:1165582
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/6/1193/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/6/1193/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jin, Mengjie & Lin, Kun-Chin & Shi, Wenming & Lee, Paul T.W. & Li, Kevin X., 2020. "Impacts of high-speed railways on economic growth and disparity in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 158-171.
    2. Chia-Lin Chen & Roger Vickerman, 2017. "Can transport infrastructure change regions’ economic fortunes? Some evidence from Europe and China," Regional Studies, Taylor & Francis Journals, vol. 51(1), pages 144-160, January.
    3. Maparu, Tuhin Subhra & Mazumder, Tarak Nath, 2017. "Transport infrastructure, economic development and urbanization in India (1990–2011): Is there any causal relationship?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 319-336.
    4. Andres Monzon & Elena Lopez & Emilio Ortega, 2019. "Has HSR improved territorial cohesion in Spain? An accessibility analysis of the first 25 years: 1990–2015," European Planning Studies, Taylor & Francis Journals, vol. 27(3), pages 513-532, March.
    5. Komikado, Hiroshi & Morikawa, So & Bhatt, Ayushman & Kato, Hironori, 2021. "High-speed rail, inter-regional accessibility, and regional innovation: Evidence from Japan," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    6. Gabriel M Ahlfeldt & Arne Feddersen, 2018. "From periphery to core: measuring agglomeration effects using high-speed rail," Journal of Economic Geography, Oxford University Press, vol. 18(2), pages 355-390.
    7. Wang, Lvhua & Liu, Yongxue & Sun, Chao & Liu, Yahui, 2016. "Accessibility impact of the present and future high-speed rail network: A case study of Jiangsu Province, China," Journal of Transport Geography, Elsevier, vol. 54(C), pages 161-172.
    8. Benedikt Mandel & Marc Gaudry & Werner Rothengatter, 1997. "A disaggregate Box-Cox Logit mode choice model of intercity passenger travel in Germany and its implications for high-speed rail demand forecasts," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(2), pages 99-120.
    9. Liu, Liwen & Zhang, Ming, 2018. "High-speed rail impacts on travel times, accessibility, and economic productivity: A benchmarking analysis in city-cluster regions of China," Journal of Transport Geography, Elsevier, vol. 73(C), pages 25-40.
    10. Wang, Yao & Dong, Weijia, 2022. "How China's high-speed rail promote local economy: New evidence from county-level panel data," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 67-81.
    11. Begoña Guirao & Natalia Casado-Sanz & Juan Luis Campa, 2020. "Labour opportunities provided by Spanish high-speed rail (HSR) commuting services in a period of financial crisis: an approach based on regional wage disparities and housing rental prices," Regional Studies, Taylor & Francis Journals, vol. 54(4), pages 539-549, April.
    12. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    13. Yong Fan & Shengdi Zhang & Zongyi He & Biao He & Haicong Yu & Xiaoxiao Ye & Hao Yang & Xiangmin Zhang & Zhifeng Chi, 2018. "Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-11, June.
    14. Kim, Hyojin & Sultana, Selima, 2015. "The impacts of high-speed rail extensions on accessibility and spatial equity changes in South Korea from 2004 to 2018," Journal of Transport Geography, Elsevier, vol. 45(C), pages 48-61.
    15. Jiao, Jingjuan & Wang, Jiaoe & Zhang, Fangni & Jin, Fengjun & Liu, Wei, 2020. "Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China," Transport Policy, Elsevier, vol. 91(C), pages 1-15.
    16. Jinxing Hu & Guojie Ma & Chaohai Shen & Xiaolan Zhou, 2022. "Impact of Urbanization through High-Speed Rail on Regional Development with the Interaction of Socioeconomic Factors: A View of Regional Industrial Structure," Land, MDPI, vol. 11(10), pages 1-21, October.
    17. Daniel F Heuermann & Johannes F Schmieder, 2019. "The effect of infrastructure on worker mobility: evidence from high-speed rail expansion in Germany," Journal of Economic Geography, Oxford University Press, vol. 19(2), pages 335-372.
    18. (Ato) Xu, Wangtu & Huang, Ying, 2019. "The correlation between HSR construction and economic development – Empirical study of Chinese cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 24-36.
    19. Shao, Shuai & Tian, Zhihua & Yang, Lili, 2017. "High speed rail and urban service industry agglomeration: Evidence from China's Yangtze River Delta region," Journal of Transport Geography, Elsevier, vol. 64(C), pages 174-183.
    20. Guo, Ying & Cao, Lingyan & Song, Ying & Wang, Yan & Li, Yongkui, 2022. "Understanding the formation of City-HSR network: A case study of Yangtze River Delta, China," Transport Policy, Elsevier, vol. 116(C), pages 315-326.
    21. Chen, Zhenhua & Haynes, Kingsley E., 2017. "Impact of high-speed rail on regional economic disparity in China," Journal of Transport Geography, Elsevier, vol. 65(C), pages 80-91.
    22. Glaeser, Edward L. & Kahn, Matthew E. & Rappaport, Jordan, 2008. "Why do the poor live in cities The role of public transportation," Journal of Urban Economics, Elsevier, vol. 63(1), pages 1-24, January.
    23. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2020. "Does China’s high-speed rail development lead to regional disparities? A network perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 299-321.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fanlong Zeng & Huaping Sun, 2024. "Spatial Network Analysis of Coupling Coordination between Digital Financial Inclusion and Common Prosperity in the Yangtze River Delta Urban Agglomeration," Mathematics, MDPI, vol. 12(9), pages 1-25, April.
    2. Yuan Yi & Fang He & Yuxuan Si, 2023. "Spatial Effects of Railway Network Construction on Urban Sprawl and Its Mechanisms: Evidence from Yangtze River Delta Urban Agglomeration, China," Land, MDPI, vol. 13(1), pages 1-20, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiao, Jingjuan & Zhao, Hongyu & Lyu, Guowei, 2024. "How does high-speed rail affect off-site investments? Evidence from the Yangtze River Delta, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    2. Di Matteo, Dante & Cardinale, Bernardo, 2023. "Impact of high-speed rail on income inequalities in Italy," Journal of Transport Geography, Elsevier, vol. 111(C).
    3. Jin, Mengjie & Gu, Ruyue & Li, Kevin X. & Shi, Wenming & Xiao, Yi, 2024. "Heterogeneous impacts of the high-speed railway network on urban–rural income disparity: Spatiotemporal evidence from Yangtze River Delta of China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    4. Jin, Wenwan & Zhu, Shengjun, 2023. "High-speed rail network and regional convergence/divergence in industrial structure," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    5. Huang, Yan & Zong, Huiming, 2020. "The spatial distribution and determinants of China’s high-speed train services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 56-70.
    6. Yu, Danlin & Murakami, Daisuke & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Wang, Xiaoxi & Li, Guangdong, 2020. "Investigating high-speed rail construction's support to county level regional development in China: An eigenvector based spatial filtering panel data analysis," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 21-37.
    7. Wu, Bingyu & Levinson, David M., 2024. "A multi-modal analysis of the effect of transport on population and productivity in China," Journal of Transport Geography, Elsevier, vol. 116(C).
    8. Ziyang Chen & Xiao Feng & Ziwen He, 2022. "A Key to Stimulate Green Technology Innovation in China: The Expansion of High-Speed Railways," IJERPH, MDPI, vol. 20(1), pages 1-21, December.
    9. Liu, Jingyang & Yang, Haoran, 2023. "Income allocation and distribution along with high-speed rail development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    10. Huang, Ying & Xu, Wangtu (Ato), 2021. "Spatial and temporal heterogeneity of the impact of high-speed railway on urban economy: Empirical study of Chinese cities," Journal of Transport Geography, Elsevier, vol. 91(C).
    11. Liu, Mengsha & Jiang, Yan & Wei, Xiaokun & Ruan, Qingsong & Lv, Dayong, 2023. "Effect of high-speed rail on entrepreneurial activities: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    12. Jinxing Hu & Guojie Ma & Chaohai Shen & Xiaolan Zhou, 2022. "Impact of Urbanization through High-Speed Rail on Regional Development with the Interaction of Socioeconomic Factors: A View of Regional Industrial Structure," Land, MDPI, vol. 11(10), pages 1-21, October.
    13. Yu, Danlin & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Li, Guangdong, 2021. "The varying effects of accessing high-speed rail system on China’s county development: A geographically weighted panel regression analysis," Land Use Policy, Elsevier, vol. 100(C).
    14. Jing Fan & Hironori Kato & Xinghua Liu & Ye Li & Changxi Ma & Liang Zhou & Mingzhang Liang, 2022. "High-Speed Railway Network Development, Inter-County Accessibility Improvements, and Regional Poverty Alleviation: Evidence from China," Land, MDPI, vol. 11(10), pages 1-22, October.
    15. de Freitas, Lucas Meyer & Blum, Salem, 2024. "An accessibility-based methodology to identify corridor speed upgrades in the European rail network," Journal of Transport Geography, Elsevier, vol. 114(C).
    16. Li, Xiang & Cheng, Zhonghua, 2022. "Does high-speed rail improve urban carbon emission efficiency in China?," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    17. Lan, Xiujuan & Hu, Zheneng & Wen, Chuanhao, 2023. "Does the opening of high-speed rail enhance urban entrepreneurial activity? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    18. Fan, Xiaomin & Xu, Yingzhi, 2023. "Does high-speed railway promote urban innovation? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    19. Di Matteo, Dante & Mariotti, Ilaria & Rossi, Federica, 2023. "Transport infrastructure and economic performance: An evaluation of the Milan-Bologna high-speed rail corridor," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    20. Weichen Liu & Jiaying Guo & Wei Wu & Youhui Cao, 2022. "The evolution of regional spatial structure influenced by passenger rail service: A case study of the Yangtze River Delta," Growth and Change, Wiley Blackwell, vol. 53(2), pages 651-679, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1193-:d:1165582. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.