Adv Search
Volume 27 Issue 5
. 
Turn off MathJax
Article Contents
Article Navigation >  Chinese Geographical Science  > 2017  >  27(5): 697-708

GUO Jianke, WANG Shaobo, WANG Dandan, LIU Tianbao. Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network[J]. Chinese Geographical Science, 2017, 27(5): 697-708. doi: 10.1007/s11769-017-0903-9
Citation: GUO Jianke, WANG Shaobo, WANG Dandan, LIU Tianbao. Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network[J]. Chinese Geographical Science, 2017, 27(5): 697-708. doi: 10.1007/s11769-017-0903-9
shu

Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network

doi: 10.1007/s11769-017-0903-9
  • 1.

    Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, China;

  • 2.

    Institute of Finance and Economics, Shanghai University of Finance and Economics, Shanghai 200433, China

Funds:  Under the auspices of National Natural Science Foundation of China (No.41571126,41571122),Development Plan Outstanding Young Scholars in Universities of Liaoning Province (No.WJQ2015020)
More Information
  • Corresponding author: GUO Jianke,E-mail:gjianke98@126.com
  • Received Date: 2016-10-14
  • Rev Recd Date: 2016-02-10
  • Publish Date: 2017-10-27
  • The economies of China-Japan-Korea (CJK) are complementary, with their proximity resulting in the three countries having a high degree of interdependence with respect to trade. Currently, trade among these countries relies mainly on port-centered shipping. The development of the shipping network is integral for in-depth integration of CJK trade. This paper analyzes the overall characteristics, centrality, spatial structure, and vulnerability of the CJK shipping network using the methods of complex network analysis, blocking flow theory, and interruption and deletion of hub ports. The main findings are as follows:1) The CJK shipping network has a small average path length and clustering coefficient, and its degree distribution follows a power-law distribution, which make the network present obvious characteristics of a Barabási-Albert scale-free. 2) The characteristics of the multi-center point of the CJK shipping network can alleviate traffic pressure. At the same time, the network shows a clear hierarchy in the port transportation system, with cargo transport relying mainly on the ‘hub port-hub port’ connection. 3) The CJK shipping network is relatively stable. Compared with ports in Japan and Korea, the main hub ports in China have a greater impact on the stability of the shipping network, in particular those ports of the central coastal region, including Shanghai, Ningbo, and Lianyungang.
  • [1] Black W R, 2003. Transportation:A Geographical Analysis. New York:The Guilford Press.
    [2] Cai Yuanyuan, Wang Hong, Fan Yanjing, 2008. Complex networks theory and its application in public traffic network. Information Technology and Informatization, (2):18-19, 23. (in Chinese)
    [3] Coolen A C C, Sherrington D, 1993. Dynamics of fully connected attractor neural networks near saturation. Physical Review Letters, 71(23):3886-3889. doi: 10.1103/PhysRevLett.71.3886
    [4] Ducruet C, Lugo I, 2013. Structure and dynamics of transportation networks:models, methods and applications. In:Rodrigue J P, Notteboom T, Shaw J. The SAGE Handbook of Transport Studies. London:SAGE Publications, 347-364.
    [5] Fan Chenghao, 2007. Research on CRE logistics network planning based on hub and spoke theory. Beijing:Beijing Jiaotong University. (in Chinese)
    [6] Gao Ziyou, Wu Jianjun, Mao Baohua et al., 2005. Study on the complexity of traffic networks and related problems. Journal of Transportation Systems Engineering and Information Technology, 5(2):79-84. (in Chinese)
    [7] He Cheng, 2007. Complex Network Properties of the Chinese Railway Network. Guangzhou:Sun Yat-sen University. (in Chinese)
    [8] Jiao Jingjuan, Wang Jiao'e, 2014. Spatial structure and evolution of Hainan airlines network:an analysis of complex network. Geographical Research, 33(5):926-936. (in Chinese)
    [9] Kaluza P, Kölzsch A, Gastner M T et al., 2010. The complex network of global cargo ship movements. Journal of the Royal Society, Interface, 7(48):1093-1103. doi:10.1098/rsif.2009. 0495
    [10] Li Xinhua, Zhang Zhaoning, Hou Rui, 2009. Research of the structural stability of the route network system. Journal of Transportation Engineering and Information, 7(1):80-85. (in Chinese)
    [11] Mo Huihui, Wang Jiao'e, Jin Fengjun, 2008. Complexity perspectives on transportation network. Progress in Geography, 27(6):112-120. (in Chinese)
    [12] Mo Huihui, Jin Fengjun, Liu Yi et al., 2010. Network analysis on centrality of airport system. Scientia Geographica Sinica, 30(2):204-212. (in Chinese)
    [13] Mu Xiangwei, Chen Yan, Yang Ming et al., 2009. Topological features of liner shipping network. Journal of Dalian Maritime University, 35(2):34-37. (in Chinese)
    [14] Rodrigue J P, Comtois C, Slack B, 2013. The Geography of Transport Systems. 3rd ed. London:Routledge.
    [15] Scott J, 2000. Social Network Analysis:A Handbook. 2nd ed. London:SAGA Publications.
    [16] Taha A F, Piust R E, 2004. Faith nxaining systems for uifian railway tunneling projects. Geotechnical Special Publication, 1555-1565
    [17] Tian Wei, Deng Guishi, Wu Peijian et al., 2007. Analysis of complexity in global shipping network. Journal of Dalian University of Technology, 47(4):605-609. (in Chinese)
    [18] Wang Jiao'e, Mo Huihui, Jin Fengjun, 2009. Spatial structural characteristics of Chinese aviation network based on complex network theory. Acta Geographica Sinica, 64(8):899-910. (in Chinese)
    [19] Wang J J, Slack B, 2000. The evolution of a regional container port system:the Pearl River Delta. Journal of Transport Geography, 8(4):263-275. doi: 10.1016/S0966-6923(00)00013-2
    [20] Wang Nuo, Dong Lingling, Wu Nuan et al., 2016. The change of global container shipping network vulnerability under intentional attack. Acta Geographica Sinica, 71(2):293-303. (in Chinese)
    [21] Wang Shaobo, Guo Jianke, 2016. Spatial measure of traffic accessibility and market potential of the National scenic areas. Geographical Research, 35(9):1714-1726. (in Chinese)
    [22] Watts D J, 2006. Small World:The Dynamics of Networks between Order and Randomness. Chen Yu Trans. Beijing:Renmin University of China Press, 1-10.
    [23] Wirasinghe S C, Vandebona U, 1987. Some aspects of the location of subway stations and routes. In:4th International Symposium on Locational Decisions (ISOLDE). Namur, Belgium.
    [24] Woolley-Meza O, Thiemann C, Grady D et al., 2011. Complexity in human transportation networks:a comparative analysis of worldwide air transportation and global cargo-ship movements. The European Physical Journal B, 84(4):589-600. doi: 10.1140/epjb/e2011-20208-9
    [25] Wu Jinfeng, Pan Xuli, 2010. Study on the relationship between inbound tourism flows network and aviation network. Tourism Tribune, 25(11):39-43. (in Chinese)
    [26] Xu Minzheng, Xu Jun, Chen Yu, 2014. Construction of Chinese aviation hub-spoke structure based on maximum leaf spanning tree. Acta Geographica Sinica, 69(12):1847-1857. (in Chinese)
    [27] Xu X P, Hu J H, Liu F, 2007. Empirical analysis of the shiptransport network of China. Chaos, 17(2):023129. doi:10. 1063/1.2740564
    [28] Xue Junfei, 2008. Hierarchical structure and distribution pattern of Chinese urban system based on aviation network. Geographical Research, 27(1):23-32. (in Chinese)
    [29] Zeng Qingcheng, Teng Teng, 2015. Analysis of shipping network of maritime silk road based on methodology of complex networks. Navigation of China, 38(2):122-125, 134. (in Chinese)
    [30] Zhao Hang, He Shiwei, Wang Dezhan, 2008. How to optimize transport capacity allocation for freight intermodal transport service network. Logistics Technology, 27(12):55-59. (in Chinese)
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article Metrics

Article views(349) PDF downloads(608) Cited by()

Proportional views
Related

Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network

doi: 10.1007/s11769-017-0903-9
  • 1. Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, China;
  • 2. Institute of Finance and Economics, Shanghai University of Finance and Economics, Shanghai 200433, China
Funds:  Under the auspices of National Natural Science Foundation of China (No.41571126,41571122),Development Plan Outstanding Young Scholars in Universities of Liaoning Province (No.WJQ2015020)
    Corresponding author: GUO Jianke,E-mail:gjianke98@126.com
  • Received Date: 2016-10-14
  • Rev Recd Date: 2016-02-10
  • Publish Date: 2017-10-27

Abstract: The economies of China-Japan-Korea (CJK) are complementary, with their proximity resulting in the three countries having a high degree of interdependence with respect to trade. Currently, trade among these countries relies mainly on port-centered shipping. The development of the shipping network is integral for in-depth integration of CJK trade. This paper analyzes the overall characteristics, centrality, spatial structure, and vulnerability of the CJK shipping network using the methods of complex network analysis, blocking flow theory, and interruption and deletion of hub ports. The main findings are as follows:1) The CJK shipping network has a small average path length and clustering coefficient, and its degree distribution follows a power-law distribution, which make the network present obvious characteristics of a Barabási-Albert scale-free. 2) The characteristics of the multi-center point of the CJK shipping network can alleviate traffic pressure. At the same time, the network shows a clear hierarchy in the port transportation system, with cargo transport relying mainly on the ‘hub port-hub port’ connection. 3) The CJK shipping network is relatively stable. Compared with ports in Japan and Korea, the main hub ports in China have a greater impact on the stability of the shipping network, in particular those ports of the central coastal region, including Shanghai, Ningbo, and Lianyungang.

GUO Jianke, WANG Shaobo, WANG Dandan, LIU Tianbao. Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network[J]. Chinese Geographical Science, 2017, 27(5): 697-708. doi: 10.1007/s11769-017-0903-9
Citation: GUO Jianke, WANG Shaobo, WANG Dandan, LIU Tianbao. Spatial Structural Pattern and Vulnerability of China-Japan-Korea Shipping Network[J]. Chinese Geographical Science, 2017, 27(5): 697-708. doi: 10.1007/s11769-017-0903-9
shu

    HTML

Reference (30)

Catalog

    Copyright © Editorial office of Chinese Geographical Science

    Tel: +86-0431-85542219   Email: egeoscien@neigae.ac.cn  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return