摘要
学术界对国际贸易网络的研究,大都采用宏观的国家层面的数据建立网络模型,并用图论的指标静态分析国际贸易模式、贸易流以及经济全球化等问题。企业作为国际贸易活动的主体,其市场国际化行为影响某国或某地区国际贸易网络的产生和演化。因此,有必要采用微观的企业层面的数据对国际贸易网络进行研究。本文正是在这个研究方向上,提出一个跨学科方法研究国际贸易网络,将国际贸易网络的研究引入到微观层面。
国际贸易微观层面涉及到企业、技术、产品、出口市场等多种要素及要素之间的多丛复杂关系;且表现出要素数目较大的复杂系统特征。对此,首先将Carley的元网络模型扩充为复杂元网络模型,并应用于国际贸易网络微观建模,提出国际贸易复杂元网络模型;然后结合整体网络时间动态性和网络要素动态性提出国际贸易复杂动态元网络模型框架。
由于国际贸易复杂动态元网络模型应用面临处理多数据来源和大规模复杂类型数据流的挑战,提出创新的建模技术方案:建立集成网络建模和分析的商务智能系统。综合运用商务智能平台提供的数据库、数据仓库、OLAP和数据挖掘等技术优势支持复杂动态元网络的智能建模和数据分析。
最后以1995年至2004年广东高新技术产品出口贸易年度统计数据为来源,建立由10个复杂元网络组成的复杂动态元网络;综合采用时序网络分析、多元统计分析和数据挖掘等方法:(1)对复杂元网络整体网络拓扑特征时序变化、子元网络和子网结构的演化进行深入和细致的分析;(2)采用统计过程控制原理诊断网络拓扑特征或网络结构的改变;(3)挖掘企业节点行为模式的演化;(4)基于网络测度指标对企业节点进行定量评价和细分;(5)识别隐含在企业市场关系数据中的市场关联结构及关联二分社团的局域特征。
本文的创新主要体现四个方面。第一,从微观企业角度提出了国际贸易网络的复杂动态元网络模型框架,为国际贸易网络的研究提供了新模型。第二,提出了采用商务智能系统支持的多数据源集成与复杂元网络智能建模方法,为大规模复杂动态元网络模型的具体实现提供了技术支持,为同类研究提供较好的方法论借鉴和参考。第三,针对复杂动态元网络模型中的基元模型:2模式网络:(1)提出采用时间标签定义网络边属性的动态2模式网络表达方法;(2)采用数据挖掘技术识别2模式网络中隐含的节点关联模式和完全二分子图;归纳频繁发生的节点行为模式和事件序列模式。第四,在上述模型与具体建模技术创新工作的基础上,研究广东高新技术产品出口贸易问题。基于复杂元网络方法的研究提供了广东高新技术出口贸易系统结构特征方面和要素关系及企业行为方面的丰富信息,这是目前管理部门采用传统经济统计方法不能提供和解释的。
In the academic research field of International Trade Network, most researchers use macro-level data to establish network model, i.e., the country as a node, trade relations of import or export between countries as arcs; and then used the static graph-based measures to explained the patters of trade flows among countries, as well as the issue on economic globalization. In the process of international trade, the internationalization behavior of enterprises will affect the international trade network of a country or a region, such as, the emergence of networks, network changes over time, and so on. Therefore, it is necessary to use micro-enterprise level data to study the international trade network. This paper proposed an interdisciplinary approach to study international trade networks, by using enterprise-level data modeling and analysis.
However, in the micro-level of international trade activities, because of involving a variety of elements and complex relations among different elements, for example, enterprises, technology, products, markets and trade organizations, etc.. Moreover, the system of international trade exhibited characteristics of complex systems which is large-scale, multiple-elements, and multiple-mode and multiple-plex relation. Traditional one mode or two mode network model cannot support complex mode network modeling. Therefore, to meet the needs of micro-level international trade network modeling, this paper first proposed a international trade complex metanetwork model by extending Charley’s metanetwork model to the complex metanetwork model, and then proposed a dynamic network framework, named the International Trade Complex Dynamic Metanetwork Model, to describe the dynamic nature of the overall metanetwork and the factors caused nodes and links change.
As the application of international trade complex dynamic metanetwork model need to handle multiple data sources and massive data streams, and facing challenges of complex data types, this paper proposed an innovative modeling solution: establish an Business Intelligent system which composites with database, data warehousing, OLAP and data mining, in order to support complex metanetwork modeling and analysis.
Finally, based on high-tech export trade data of Guangdong province during the period of 1995-2004, this paper established the complex dynamic network composing of ten metanetworks, and then used time-series network analysis, multiple variables statistical analysis and data mining: (I) analyze temporal changes of the whole metanetwork topology properties, the structure evolution of sub-metanetwork or subnetwork; (ii) detect the changes of the network topology prosperities or the network structure; (iii) mining the enterprise node’s behavior patterns; (iv) evaluate and classify enterprise nodes based on graph measures; (v) indentify market association structure hidden in the relation data between enterprise and export markets.
The innovation of the present paper is chiefly embodied in the following aspects: (i) it proposed a complex metanetwork model for international trade network modeling by using micro-level data coming from enterprise, which offers a new model for the research of international trade network. (ii) It proposed a methodology to support the large-scale complex dynamic metanetwork modeling by using powerful techniques provided by Business Intelligent platform, which will provide a methodological reference for the similar research. (iii) It proposed a dynamic bipartite network representation schema by enhancing edge definition with timestamp, considering the bipartite network is the“gene”network in complex dynamic metanetwork. And then it applied data mining techniques to discover the bipartite subgraph, the linkage pattern and the nodes behaviors. (iv) It studied systematically the high-tech export trade of Guangdong based on the above works. The empirical results provided large information on the structure prosperities of export trade system. These rich information cannot be provided and explained by the traditional economic statistical methods.
引文
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