The impact of main channel interruption on vulnerability of container shipping network and China container shipping
Received date: 2016-11-29
Request revised date: 2017-02-19
Online published: 2017-04-20
Copyright
The Malacca Strait, the Suez Canal and the Panama Canal are the main channels in the global container shipping network. As the dependence of the world economy on container shipping constantly increases and terrorism wantonly spread, research of the impact of main channel interruption on the global container shipping network and China container shipping is of great significance in analyzing the vulnerability of the global container shipping network, establishing and improving the security mechanism of the global economy operation and guaranteeing unobstructed container shipping between China and other regions. To study the impact, we performed a statistical analysis of all ports and shipping lines that are operated by the top 100 container shipping companies in 2015, which occupy 93% of the global container shipping capacity. The results indicate that there are 2827 shipping lines and 734 ports in the global container shipping network. Based on the statistics, we calculated the change rates of network average degree, isolated-node proportion, clustering coefficient, network average shortest-path length and network efficiency of the network when the main channels are attacked respectively. The average of the change rates of the network's metrics are 5.61%, 3.50% and 1.89% when the Malacca Strait, the Suez Canal and the Panama Canal are attacked respectively. So the network is sensitive to the three main channels, and the Malacca Strait is the most influential channel, followed by the Suez Canal and the Panama Canal. At the same time, we analyzed the impact on China container shipping by combining the characteristics of global marine geography. The node degrees of 12, 6 and 6 ports in China decrease when the main channels are attacked respectively, and the network shortest-path lengths between the affected ports in China and other ports in the world increase in varying degrees, so the transport efficiency decreases obviously. Finally, to guarantee unobstructed container shipping between China and other regions, we present the alternative shipping lines by detour transportation or sea-land multimodal transportation according to different main channels, and make corresponding policies from the maritime security perspective.
Key words: Malacca Strait; Suez Canal; Panama Canal; container; network
WU Di , WANG Nuo , WU Nuan , LIN Wanni . The impact of main channel interruption on vulnerability of container shipping network and China container shipping[J]. GEOGRAPHICAL RESEARCH, 2017 , 36(4) : 719 -730 . DOI: 10.11821/dlyj201704010
Fig. 1 Location of container shipping lines via main channels图1 集装箱海运主航道航线分布图 |
Tab. 1 Statistics of channels in the global shipping network表1 全球海运网络航道统计 |
| 编号 | 航道 | 编号 | 航道 | 编号 | 航道 |
|---|---|---|---|---|---|
| 1 | 马六甲海峡 | 9 | 龙目海峡 | 17 | 白令海峡 |
| 2 | 苏伊士运河 | 10 | 望加锡海峡 | 18 | 土耳其海峡 |
| 3 | 巴拿马运河 | 11 | 民都洛海峡 | 19 | 德雷克海峡 |
| 4 | 英吉利海峡 | 12 | 台湾海峡 | 20 | 麦哲伦海峡 |
| 5 | 直布罗陀海峡 | 13 | 大隅海峡 | 21 | 多佛尔海峡 |
| 6 | 曼德海峡 | 14 | 朝鲜海峡 | 22 | 莫桑比克海峡 |
| 7 | 霍尔木兹海峡 | 15 | 宗谷海峡 | 23 | 基尔运河 |
| 8 | 巽它海峡 | 16 | 佛罗里达海峡 |
Tab. 2 Change in the network average degree after themain channels are attacked表2 三大主航道遭受攻击时网络节点度变化 |
| 攻击对象 | 无 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|---|
| 平均节点度 | 9.19 | 8.28 | 8.58 | 8.92 |
| 变化率(%) | - | -9.90 | -6.67 | -2.87 |
Tab. 3 Top five ports with the largest decrease in node degree when the main channels are attacked表3 三大主航道遭受攻击时节点度减少最多的前5个港口 |
| 受攻击航道 | 排名 | 港口 | 攻击前节点度 | 攻击时节点度 | 节点度减少值 | 变化率(%) |
|---|---|---|---|---|---|---|
| 马六甲海峡 | 1 | 巴生港(马来西亚) | 91 | 21 | 70 | 76.92 |
| 2 | 新加坡港(新加坡) | 123 | 68 | 55 | 44.72 | |
| 3 | 丹戎帕拉帕斯港(马来西亚) | 60 | 22 | 38 | 63.33 | |
| 4 | 科伦坡港(斯里兰卡) | 47 | 28 | 19 | 40.43 | |
| 5 | 比雷埃夫斯港(希腊) | 48 | 29 | 19 | 39.58 | |
| 苏伊士运河 | 1 | 吉达港(沙特阿拉伯) | 41 | 18 | 23 | 56.1 |
| 2 | 塞得港(埃及) | 42 | 20 | 22 | 52.38 | |
| 3 | 科伦坡港(斯里兰卡) | 47 | 29 | 18 | 38.3 | |
| 4 | 丹戎帕拉帕斯港(马来西亚) | 60 | 43 | 17 | 28.33 | |
| 5 | 巴生港(马来西亚) | 91 | 74 | 17 | 18.68 | |
| 巴拿马运河 | 1 | 曼萨尼略港(巴拿马) | 48 | 31 | 17 | 35.42 |
| 2 | 科隆港(巴拿马) | 27 | 16 | 11 | 40.74 | |
| 3 | 釜山港(韩国) | 103 | 94 | 9 | 8.74 | |
| 4 | 纽约港(美国) | 38 | 29 | 9 | 23.68 | |
| 5 | 卡塔赫纳港(哥伦比亚) | 43 | 35 | 8 | 18.6 |
Tab. 4 Proportion of network isolated-nodes after themain channels are attacked表4 三大主航道遭受攻击时网络孤立节点比例 |
| 攻击对象 | 无 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|---|
| 孤立节点数 | 0 | 16 | 7 | 7 |
| 孤立节点比例(%) | - | 2.18 | 0.95 | 0.95 |
Tab. 5 The ports that become isolated nodes after themain channels are attacked表5 三大主航道遭受攻击时产生的孤立节点 |
| 受攻击航道 | 港口 | 原节点度 |
|---|---|---|
| 马六甲海峡 | 伊利切夫斯特港(乌克兰) | 7 |
| 阿巴斯港(伊朗) | 5 | |
| 塔兰托港(意大利) | 4 | |
| 威廉港(德国) | 4 | |
| 山打根港(马来西亚) | 4 | |
| 纳闽岛港(马来西亚) | 4 | |
| 斗湖港(马来西亚) | 3 | |
| 盖梅港(越南) | 3 | |
| 佩尼谢港(葡萄牙) | 2 | |
| 埃因苏赫纳港(埃及) | 2 | |
| 苏科纳港(埃及) | 2 | |
| 印诺尔港(印度) | 2 | |
| 蒙格拉港(孟加拉) | 2 | |
| 米里港(马来西亚) | 2 | |
| 西港港(马来西亚) | 2 | |
| 诗巫港(马来西亚) | 2 | |
| 苏伊士运河 | 塔兰托港(意大利) | 4 |
| 威廉港(德国) | 4 | |
| 延布港(沙特阿拉伯) | 3 | |
| 盖梅港(越南) | 3 | |
| 勒波尔港(法国) | 2 | |
| 贾瓦哈拉尔港(印度) | 2 | |
| 贝岛港(马达加斯加) | 1 | |
| 巴拿马运河 | 斯拉维亚卡港(俄罗斯) | 4 |
| 科鲁尼亚港(西班牙) | 2 | |
| 尤日内港(乌克兰) | 2 | |
| 罗摩港(斯里兰卡) | 2 | |
| 布拉夫港(新西兰) | 2 | |
| 科罗内尔港(智利) | 2 | |
| 圣安德烈斯港(哥伦比亚) | 2 |
Tab. 6 Change in the clustering coefficient after the main channels are attacked表6 三大主航道遭受攻击时网络聚类系数变化 |
| 参数 | 未攻击前 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|---|
| 聚类系数 | 0.4973 | 0.4788 | 0.4892 | 0.4934 |
| 变化率(%) | - | -3.72 | -1.63 | -0.78 |
Tab. 7 Change in the network average shortest-path lengthafter the main channels are attacked表7 三大主航道遭受攻击时网络平均距离变化 |
| 参数 | 未攻击前 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|---|
| 平均距离 | 3.4514 | 3.6824 | 3.5984 | 3.5452 |
| 变化率(%) | - | 6.69 | 4.26 | 2.72 |
Tab. 8 Change in the network efficiency after the mainchannels are attacked表8 三大主航道遭受攻击时网络效率变化 |
| 参数 | 未攻击前 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|---|
| 网络效率 | 0.3175 | 0.2991 | 0.3056 | 0.3107 |
| 变化率(%) | - | -5.79 | -3.75 | -2.14 |
Tab. 9 Statistics of the ports in China for which node degree changes when the three main channels are attacked表9 三大主航道遭受攻击时中国港口节点度变化统计 |
| 受攻击航道 | 港口 | 攻击前节点度 | 攻击后节点度 | 节点度减少值 | 变化率(%) |
|---|---|---|---|---|---|
| 马六甲海峡 | 上海港 | 74 | 66 | 8 | -10.81 |
| 香港港 | 68 | 61 | 7 | -10.29 | |
| 深圳港 | 59 | 49 | 10 | -16.95 | |
| 宁波港 | 54 | 48 | 6 | -11.11 | |
| 青岛港 | 44 | 43 | 1 | -2.27 | |
| 厦门港 | 40 | 34 | 6 | -15 | |
| 天津港 | 32 | 30 | 2 | -6.25 | |
| 大连港 | 28 | 24 | 4 | -14.29 | |
| 广州港 | 25 | 22 | 3 | -12 | |
| 福清港 | 15 | 13 | 2 | -13.33 | |
| 福州港 | 13 | 10 | 3 | -23.08 | |
| 汕头港 | 11 | 9 | 2 | -18.18 | |
| 苏伊士运河 | 上海港 | 74 | 72 | 2 | -2.7 |
| 香港港 | 68 | 64 | 4 | -5.88 | |
| 深圳港 | 59 | 51 | 8 | -13.56 | |
| 宁波港 | 54 | 51 | 3 | -5.56 | |
| 厦门港 | 40 | 37 | 3 | -7.5 | |
| 大连港 | 28 | 26 | 2 | -7.14 | |
| 巴拿马运河 | 上海港 | 74 | 72 | 2 | -2.7 |
| 香港港 | 68 | 65 | 3 | -4.41 | |
| 深圳港 | 59 | 55 | 4 | -6.78 | |
| 宁波港 | 54 | 53 | 1 | -1.85 | |
| 青岛港 | 40 | 40 | 4 | -9.09 | |
| 厦门港 | 28 | 38 | 2 | -5 |
Tab. 10 Statistics of the change of Chinese ports' network shortest-path lengths after the main channels are attacked表10 三大主航道遭受攻击时中国港口网络距离变化统计 |
| 攻击对象 | 马六甲海峡 | 苏伊士运河 | 巴拿马运河 |
|---|---|---|---|
| 网络距离增加的港口数(个) | 485 | 257 | 133 |
| 网络距离增加的 始终港数(对) | 7258 | 4123 | 2842 |
Fig. 2 Alternative shipping lines when the main channels are attacked图2 三大主航道遭受攻击时的替代航线 |
The authors have declared that no competing interests exist.
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