地理科学进展 ›› 2013, Vol. 32 ›› Issue (11): 1577-1591.doi: 10.11820/dlkxjz.2013.11.001

• 产业经济与区域发展 •    下一篇

基于个体网交易约束的北京市产业网络结构规模绩效分析

王茂军, 包琪   

  1. 首都师范大学资源环境与旅游学院, 北京 100048
  • 收稿日期:2013-03-01 修回日期:2013-10-01 出版日期:2013-11-25 发布日期:2013-11-25
  • 作者简介:王茂军(1973- ),男,山东费县人,博士,教授,主要从事城市地理研究。E-mail: maojunw@yeah.net
  • 基金资助:
    教育部人文社会科学研究规划基金项目(09YJAZH057);国家自然科学基金项目(41071112)。

Achievement analysis of Beijing’s industrial network structure based on individual network’s trading constraint

WANG Maojun, BAO Qi   

  1. Resources, Environment and Tourism College, Capital Normal University, Beijing 100048, China
  • Received:2013-03-01 Revised:2013-10-01 Online:2013-11-25 Published:2013-11-25

摘要: 区域产业间规模差异性是各产业间竞争与合作的表征性结果。这种竞争、合作建立在产业间的供给—需求交易关系之上。产业间的多向供给—需求联系构成了复杂的交易关系网络。本文利用2002 年北京市投入产出表数据,构建了42×42 产业的(0,1)两值对称的链接交易网络,分析了该网络的结构特征及其外部绩效。研究结果发现:① 北京市不同产业的交易产业数量差异悬殊,各产业的交易链接网络规模为线性分布,网络有效规模表现为指数分布;② 北京市废品废料、服装皮革羽绒及其制品业、金属矿采选业、非金属矿采选业等10 个产业受到的网络约束最大,各产业约束量随产业交易网络规模的扩大而趋于减少,表现为非线性变动;③ 北京市各产业的网络竞争结构可以分为强约束—非均衡—小网络型、中约束—中均衡—中规模网络型、微约束—高均衡—大规模网络型,分别有13 个、18 个和8 个产业;④ 网络约束量、约束层级系数、制造业虚拟哑变量均对产业规模均产生了负向影响。交易约束量、制造业虚拟哑变量对产业规模的影响最大,且产业规模变动中的前者相对贡献要大于后者。网络交易约束量对制造业的绝对影响要小于非制造业。

关键词: 北京, 产业网络, 网络绩效, 网络结构, 网络约束

Abstract: Differences among regional industries in scales are the results and manifests of competition and cooperation among the industries, and the competition-and-cooperation relationships are based on the commercial activities governed by the basic supply-and-demand theory. Multi-directional supply-and-demand relationships among the various industries constitute complex networks of commercial activities. There are two common themes in the previous researches on industrial networks. First, they focus on the characteristics of entire network involving all industries and the general statistical characteristics of multi-dimensional network topology. Second, although there are several studies on statuses and roles of different industries (nodes) in the entire network, there is no study on the intrinsic relationships between the status and properties, or the role and properties, of each industry (node) in the network. In other words, it is important to study the intrinsic relationship between the structure of an individual industry's network and its effects on the scale of the industry (node). By using the data of supply-and-demand chart in 2002, we constructed a 42×42 two value (0, 1) symmetric industrial linkage/ transaction network, and analyzed the network's structure characteristics and its external effects. The results are shown as follows. (1) There are eight major suppliers or demanders (industries) of each industry in the network, and they are significantly different from one another. For example, electric heat product and supply industry, chemical industry, construction, transportation, leasing and business services, get the maximum numbers of trading linkages in the market. These industries are the foundation of the regional economy. On the contrary, waste product, garment, leather, down and their manufacturing industry, metal and non-metal mining and selecting, wood processing and furniture manufacturing, gas product and supply industry, petroleum and natural gas industry, each have only one industry as a trading partner. These industries are mostly local industries. In addition, each industry's linkage/trading network is in linear distribution, and the scale of the network is in exponential distribution. (2) Eight industries, for example, waste product and garment, leather, down and their manufactured goods, mining and selecting of metal ore product and nonmetal ore product, are under the highest degree of constraint by the network. Chemical industry, construction, electric heat production and supply industry, transportation, leasing and business services, financial insurance industry, are under the lowest degree of constraint by the network. The constraint on each industry reduces as the scale of the network expands. (3) The competition structures of the industrial networks can be divided into three groups: with strong constraint, imbalance and small scale network; with medium constraint, medium balance, medium scale network; and with minimum constraint, balance, and large scale network, each of which has 13, 18, and 8 industries, respectively. The first one's trading partner industries and constraining markets are minimal, and distribution of industrial trading is concentrated. The second one's scale of trading network is relatively large, trading and constraint distribution are relatively balanced, and constraint market is relatively higher. The last one's suppliers or requirements is the highest, constraint value is minimum, and the coefficient of constraint hierarchy is small. (4) Degree of network constraint, constraint hierarchy coefficient and manufacturing virtual dummy variables directly have negative impact on the industry's scale. The trading constraints and manufacturing virtual dummy variables have the most significant effects on the industry, and the former affects more than the later. Network trading constraints have more absolute effect on manufacturing than non-manufacturing industries.

Key words: Beijing, industrial network, network achievement, network constraint, network structure