中国海洋科研合作网络的空间联系

doi:10.13284/j.cnki.rddl.003342

Abstract

Abstract:

Marine science and technology are the means to develop healthy maritime productivity. In recent years, the marine economy arrived at the point of developing from high speed to high quality. China is paying more attention to how to use the sea scientifically. The development of marine science research has received more policy support. The outline of the 14th Five-Year Plan proposes to "make breakthroughs in a number of key core technologies in the fields of marine engineering, marine resources, and marine ecology." At the same time, urban network theory based on flow space is a mature and convenient way to measure inter-city scientific research cooperation. An analysis of the structure of this network will help clarify its structural characteristics and spatial differentiation, discover the technical opportunities of marine scientific research, and promote the coordinated development of academic research and the applied technology fields. With the help of the complex network analysis method, UCINET, ArcGIS, and string chart visualization software, this paper analyzes the overall structural characteristics and spatial differences of the marine research cooperation network in 2007 and 2017, respectively, to provide empirical support and a theoretical reference for the development and construction of the network. The results show that first, the marine scientific research cooperation network has obvious characteristics of a "small world" and "scale-free" network, with strong accessibility and agglomeration, and an improved openness; at the same time, it presents discrete trends and unbalanced characteristics. Second, different from the "diamond" structure of the information and innovation cooperation network, the marine scientific research cooperation network in China has formed a special "trapezoidal" structure with Beijing-Tsingtao—Shanghai-Guangzhou as the apex; the focal cooperation ties in the network have increased and gradually broadened. At the same time, three marine scientific research cooperation clusters with different functions, characteristics, and research fields have been formed in the Bohai Rim, the Yangtze River Delta, and the Pan-Pearl River Delta. Finally, the leading pattern of core cities has been consolidated, among which Qingdao plays a strong role as a "throat" and is a national marine scientific research center with a strong ability to control marine scientific resources. Some of the core nodes (such as Beijing and Wuhan) are inland, but they have a strong independent capability in marine scientific research, and an enthusiasm for engaging in scientific research cooperation; in other words, marine scientific research cooperation is characterized by significant complexity. Formation based on marine research papers in the network embodies the link between the cities. On the one hand, this reflects the influence of the research subject emphasis of the cooperation network, such as a core city taking a leading role, or being the backbone of key research institutes, etc.; on the other hand, it also reflects the network between cities that cooperate in research and the contacts that result. Exploring the marine scientific research cooperation network through marine scientific research institutions will have a positive impact on the reconstruction and network progress of national and regional marine scientific research cooperation.

Key words: maritime scientific, collaboration network, urban network, complex network

CLC Number:

K901

Jianke Guo, Yidan Ding, Yafeng Qin. Spatial Links of the Maritime Scientific Research Cooperation Network in China[J].Tropical Geography, 2021, 41(3): 584-595.

Figures/Tables 8

Table 1

Indicators of scientific research cooperation in urban networks and their implications

指标

测算方式

物理意义

实际含义

度中心性

C D i = ∑ j = 1 N a i j

式中：N表示节点个数；节点a_ij表示海洋科研合作邻接矩阵。

度数中心度越高，说明该城市海洋科研合作的重要性越突出，越居于网络的中心位置，从而衡量一个城市与其他城市海洋科研联系的能力。

介数

中心性

C B i = ∑ j = 1; k = 1; j ≠ k ≠ i N N j k i N j k

式中：N_jk（i）是节点v_j和v_k之间的最短路径条数，N_jk（i）表示节点v_j和v_k之间的最短路径经过节点v_i的条数。

如果一个城市处于通往其他城市的捷径（最短途径）上，该城市就具有较高的中间中心度，即在海洋科研合作中具有沟通其他城市的桥梁作用。

接近度

中心性

C c i = N - 1 ∑ j = 1 N d i j

式中：d_ij表示节点i与j之间的最短路径数；N表示节点个数。

城市i的接近中心度越大，科研知识流动越便捷。

Table 1

Fig.1

Table 2

Fig.2

Table 3

Fig.3

Fig.4

Fig.5

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合作网络类型	节点数/个	网络密度	平均度	平均加权度	平均路径长度	平均聚类系数	空间分布情况
中国海洋科研合作网络（2007）	127	0.21	7.452	25.2	1.536	0.768	“发散型”
中国海洋科研合作网络（2017）	134	0.26	10.358	35.2	1.035	0.739	“梯形”
中国CNKI合作网络（2016）（赵星，2017）	32	—	—	—	1.001	0.738	—
中国创新网络（2015）（周灿等，2017）	287	—	7.512	—	2.091	0.688	“菱形”
中国创新网络（2015）（段德忠等，2018）	338	0.10	—	—	0.606	1.968	“四边形”
中国专利合作网络（电子信息类）（高曼等，2018）	278	0.02	8.057	20.5	—	0.519	—
中小企业专利合作网络（王黎萤，2018）	48	0.01	—	—	1.061	0.662	—
中国集装箱运输网络（郭建科等，2018）	—	—	—	—	1.724	0.708	“轴—辐”
中国总部—分支城市网络（吴康等，2015）	330	—	5	—	1.901	0.618	“菱形”

层级	2007年（点度数）	2017年（点度数）
国家级核心	青岛（648.99）、北京（454.01）	青岛（757.49）、上海（593.16）、北京（545.83）、广州（415.34）、大连（272.17）
区域性中心	上海（287）、广州（230.01）、大连（152）	天津（165.99）、南京（148.33）、武汉（138）、烟台（121.01）、杭州（121）、厦门（113.17）、宁波（105.17）、舟山（104.01）、湛江（71.17）
一般城市	厦门（122.01、）武汉（95）、杭州（93）、南京（88.99）、天津（85.99）、湛江（63）、哈尔滨（59）、无锡（53）、烟台（39）	哈尔滨（62）、深圳（51）、威海（39.99）、镇江（37）、无锡（36）、成都（35.16）、南通（33.17）、福州（32）、南宁（32）、海口（31.17）、三亚（27.17）、北海（25）、西安（24.17）、连云港（24）、东营（24）、郑州（24）、沈阳（22）、济南（21）、锦州（20）、秦皇岛（16）、温州（16）、长沙（16）
边缘城市	西安、东营、深圳、舟山、连云港、宁波、济南、沈阳、海口等共110个地级市	长春、潍坊、湖州、盘锦、珠海、宁德、贵阳、钦州、南昌、日照等共98个地级市

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Spatial Links of the Maritime Scientific Research Cooperation Network in China

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