“丝路”海运网络的脆弱性及风险控制研究
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摘要
为研究海上丝绸之路集装箱海运网络的脆弱性,对沿线集装箱港口及挂靠航线进行了统计,构建了海上丝绸之路集装箱海运网络,以随机攻击和蓄意攻击两种方式分别对网络的平均度、孤立节点比例、聚类系数、平均路径长度、网络效率和最大连通子图相对大小等反映网络连通性特征值的变化进行了研究。结果表明"丝路"海运网络在受到随机攻击时较为"强壮",在受到蓄意攻击时相对脆弱。经进一步挖掘,揭示了蓄意攻击下网络开始崩溃和完全崩溃的临界点,并据此指出了需重点保护的枢纽干线港;结合地理特征,分析了"丝路"中主要海上通道通航受阻时网络连通性的变化,发现马六甲海峡、台湾海峡、曼德海峡及苏伊士运河对网络的脆弱性影响最为显著。为进行风险评价,分析了"丝路"网络脆弱性形成因素和抗毁性机制,并提出了相应的抗毁性评价方法,经计算得出南亚为"丝路"网络中抗毁性最薄弱的区域。最后,结合地缘风险分析,提出了相应的对策和建议。本研究对于认清"丝路"海运网络的脆弱性及风险控制方法,保障其互联互通,具有重要的理论意义和应用价值。
The Maritime Silk Road is representative of China's global strategy of this century.The road runs through the western Pacific Ocean, the southern Indian Ocean, the Mediterranean Sea, and the eastern Atlantic Ocean, connecting most of the ports in Eurasia and northeastern Africa from east to west. As world economy dependence on container shipping has been constantly increasing and terrorism has quickly spread, research on the vulnerability and geopolitical risk of the Maritime Silk Road container shipping network is crucial in establishing and improving the security mechanism in the global economy operation, as well as in guaranteeing unobstructed container shipping. Our study specifically addresses this issue through a statistical analysis of all ports and shipping lines in the Maritime Silk Road operated by global container shipping companies in 2015, covering 93% of the global container shipping capacity. The results highlight the presence of 2429 shipping lines and 440 ports in the Maritime Silk Road container shipping network. Based on these statistics, we calculated the rates of change of network average degree, isolated-node proportion, clustering coefficient,network average shortest-path length, network efficiency, and relative size of the largest connected subgraph when the network is under either random or intentional attack. Results indicate that the network is robust under random attack, but vulnerable under an intentional one. We find that the top 53 ports with the largest node strength are hub/mainline ports which require more careful protection, as the network begins to collapse when the intentional attack rate reaches 12%, with a complete collapse when such a rate is 30%. Moreover, by combining geographical features and calculating the rates of change of the network metrics when the main channels in the Maritime Silk Road are interrupted, we find that the straits of Malacca, Taiwan,and Mandeb, as well as the Suez Canal are the most influential channels, thus requiring more attention in terms of protection. In the risk evaluation, the factors determining network vulnerability and survivability are analysed. As for the latter, we find that South Asia is the weakest area in the network. Then, by combining geopolitical and economic factors, we considered the geopolitical risk of the Maritime Silk Road container shipping network. Finally,we formulated corresponding policy recommendations from the perspective of maritime security. Overall, this paper is of great theoretical significance and practical value in the study of vulnerability and risk management of the Maritime Silk Road container shipping network.
The Maritime Silk Road is representative of China's global strategy of this century.The road runs through the western Pacific Ocean, the southern Indian Ocean, the Mediterranean Sea, and the eastern Atlantic Ocean, connecting most of the ports in Eurasia and northeastern Africa from east to west. As world economy dependence on container shipping has been constantly increasing and terrorism has quickly spread, research on the vulnerability and geopolitical risk of the Maritime Silk Road container shipping network is crucial in establishing and improving the security mechanism in the global economy operation, as well as in guaranteeing unobstructed container shipping. Our study specifically addresses this issue through a statistical analysis of all ports and shipping lines in the Maritime Silk Road operated by global container shipping companies in 2015, covering 93% of the global container shipping capacity. The results highlight the presence of 2429 shipping lines and 440 ports in the Maritime Silk Road container shipping network. Based on these statistics, we calculated the rates of change of network average degree, isolated-node proportion, clustering coefficient,network average shortest-path length, network efficiency, and relative size of the largest connected subgraph when the network is under either random or intentional attack. Results indicate that the network is robust under random attack, but vulnerable under an intentional one. We find that the top 53 ports with the largest node strength are hub/mainline ports which require more careful protection, as the network begins to collapse when the intentional attack rate reaches 12%, with a complete collapse when such a rate is 30%. Moreover, by combining geographical features and calculating the rates of change of the network metrics when the main channels in the Maritime Silk Road are interrupted, we find that the straits of Malacca, Taiwan,and Mandeb, as well as the Suez Canal are the most influential channels, thus requiring more attention in terms of protection. In the risk evaluation, the factors determining network vulnerability and survivability are analysed. As for the latter, we find that South Asia is the weakest area in the network. Then, by combining geopolitical and economic factors, we considered the geopolitical risk of the Maritime Silk Road container shipping network. Finally,we formulated corresponding policy recommendations from the perspective of maritime security. Overall, this paper is of great theoretical significance and practical value in the study of vulnerability and risk management of the Maritime Silk Road container shipping network.
引文
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[2]Tian Yaping,Chang Hao.Bibliometric analysis of research progress on ecological vulnerability in China.Acta Geographica Sinica,2012,67(11):1515-1525.[田亚平,常昊.中国生态脆弱性研究进展的文献计量分析.地理学报,2012,67(11):1515-1525.]
[3]Zhao Dongsheng,Wu Shaohong.Responses of vulnerability for natural ecosystem to climate change in China.Acta Geographica Sinica,2013,68(5):602-610.[赵东升,吴绍洪.气候变化情景下中国自然生态系统脆弱性研究.地理学报,2013,68(5):602-610.]
[4]Yuan Quanzhi,Wu Shaohong,Dai Erfu,et al.NPP vulnerability of China's potential vegetation to climate change in the past 50 years.Acta Geographica Sinica,2016,71(5):797-806.[苑全治,吴绍洪,戴尔阜,等.过去50年气候变化下中国潜在植被NPP的脆弱性评价.地理学报,2016,71(5):797-806.]
[5]Liu Yi,Huang Jianyi,Ma Li.The assessment of regional vulnerability to natural disasters in China based on DEA model.Geographical Research,2010,29(7):1153-1162.[刘毅,黄建毅,马丽.基于DEA模型的我国自然灾害区域脆弱性评价.地理研究,2010,29(7):1153-1162.]
[6]Li Zequan,Zhang Ruixin,Yang Zhao,et al.Influence complex network centrality on disaster spreading.Acta Physica Sinica,2012,61(23):1-7.[李泽荃,张瑞新,杨曌,等.复杂网络中心性对灾害蔓延的影响.物理学报,2012,61(23):1-7.]
[7]Tian Yaping,Xiang Qingcheng,Wang Peng.Regional coupled human-natural systems vulnerability and its evaluation indexes.Geographical Research,2013,32(1):55-63.[田亚平,向清成,王鹏.区域人地耦合系统脆弱性及其评价指标体系.地理研究,2013,32(1):55-63.]
[8]Su Fei,Zhang Pingyu,Li He.Vulnerability assessment of coal-mining cities'economic systems in China.Geographical Research,2008,27(4):907-916.[苏飞,张平宇,李鹤.中国煤矿城市经济系统脆弱性评价.地理研究,2008,27(4):907-916.]
[9]Fang Chuanglin,Wang Yan.A comprehensive assessment of urban vulnerability and its spatial differentiation in China.Acta Geographica Sinica,2015,70(2):234-247.[方创琳,王岩.中国城市脆弱性的综合测度与空间分异特征.地理学报,2015,70(2):234-247.]
[10]Wang Nuo,Dong Lingling,Wu Nuan,et al.The change of global container shipping network vulnerability under intentional attack.Acta Geographica Sinica,2016,71(2):293-303.[王诺,董玲玲,吴暖,等.蓄意攻击下全球集装箱海运网络脆弱性变化.地理学报,2016,71(2):293-303.]
[11]Wang Chengjin.Spatial organization networks of world marine container transportation.Geographical Research,2008,27(3):636-648.[王成金.全球集装箱航运的空间组织网络.地理研究,2008,27(3):636-648.]
[12]Wang Chengjin,Cesar Ducruet.Theoretical model of container port system and its empirical research in Yangtze River Delta.Geographical Research,2011,30(3):397-410.[王成金,Cesar Ducruet.现代集装箱港口体系演进理论与实证.地理研究,2011,30(3):397-410.]
[13]Du Chao,Wang Jiao'e,Mo Huihui,Spatial pattern analysis of China container shipping network on complex theory.Resources and Environment in the Yangtze Basin,2016,25(2):190-198.[杜超,王姣娥,莫辉辉.中国集装箱航运网络格局及复杂性研究.长江流域资源与环境,2016,25(2):190-198.]
[14]Mu Xiangwei,Chen Yan,Yang Ming,et al.Topological features of liner shipping network.Journal of Dalian Maritime University,2009,35(2):34-37.[牟向伟,陈燕,杨明,等.班轮航运网络拓扑特性.大连海事大学学报,2009,35(2):34-37.]
[15]Wu Peijian,Deng Guishi,Tian Wei.Research on topology character of container shipping network.Journal of Wuhan University of Technology(Transportation Science&Engineering),2008,32(4):665-668.[武佩剑,邓贵仕,田炜.集装箱航运网络拓扑特性研究.武汉理工大学学报(交通科学与工程版),2008,32(4):665-668.]
[16]Tian Wei,Deng Guishi,Wu Peijian,et al.Analysis of complexity in global shipping network.Journal of Dalian University of Technology,2007,47(4):605-609.[田炜,邓贵仕,武佩剑,等.世界航运网络复杂性分析.大连理工大学学报,2007,47(4):605-609.]
[17]Tian Wei,Deng Guishi,Wu Peijian.Analysis of network effect in port and shipping system characterized by scale-free network.Chinese Journal of Management,2008,5(3):381-384.[田炜,邓贵仕,武佩剑.具有无标度特性的港航系统网络效应分析.管理学报,2008,5(3):381-384.]
[18]Deng Guishi,Wu Peijian,Tian Wei.Research on robustness and vulnerability of global shipping network.Journal of Dalian University of Technology.2008,48(5):765-768.[邓贵仕,武佩剑,田炜.全球航运网络鲁棒性和脆弱性研究.大连理工大学学报,2008,48(5):765-768.]
[19]Jin Fengjun,Wang Jiao'e.Railway network expansion and spatial accessibility analysis in China:1906-2000.Acta Geographica Sinica,2004,59(2):293-302.[金凤君,王姣娥.20世纪中国铁路网扩展及其空间通达性.地理学报,2004,59(2):293-302.]
[20]Kurant M,Thiran P.Extraction and analysis of traffic and topologies of transportation networks.Physical Review E,2006,74(3):036114.
[21]Du Chao,Wang Jiao'e.Spatial pattern of China Southern Airlines'network and its market coverage.Geographical Research,2015,34(7):1319-1330.[杜超,王姣娥.南方航空网络空间格局及市场范围.地理研究,2015,34(7):1319-1330.]
[22]Xu Feng,Zhu Jinfu,Miao Jianjun.The robustness of high-speed railway and civil aviation compound network based on the complex network theory.Complex Systems and Complexity Science,2015,12(1):40-45.[徐凤,朱金福,苗建军.基于复杂网络的空铁复合网络的鲁棒性研究.复杂系统与复杂性科学,2015,12(1):40-45.]
[23]Mo Huihui,Wang Jiao'e,Jin Fengjun.Complexity perspectives on transportation network.Progress in Geography,2008,27(6):112-120.[莫辉辉,王姣娥,金凤君.交通运输网络的复杂性研究.地理科学进展,2008,27(6):112-120.]
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