中国区际价值链协作的网络特征与空间格局及其演变——基于增加值分解和复杂网络的分析

利用增加值分解和复杂网络分析方法，基于2007年、2010年和2012年的省际投入产出表，构建中国区际价值链协作网络，考察区际价值链协作的网络特点与空间格局及其演变。结果表明，中国区际价值链协作存在显著的网络特点，显示出小世界网络特征；各地区的网络中心性有明显的地区差异，且该差异在不断缩小，而工业化水平等是引起节点网络中心性地区差异的重要因素。节点聚类和社区划分的结果发现，中国区际价值链协作网络存在3~4个网络社区，地区间的局部网络互动显著；且各网络社区内部的节点地区表现出显著的空间毗邻与地理成片，特别是上海等8个地区在网络中的局部互动最为稳定。

The Network Characteristics and Spatial Patterns of Inter-region Value Chain Coordination in China and Their Evolution: Based on the Analysis of Value Added Decomposition and Complex Network

In order to investigate the network characteristics and spatial pattern of inter-region value chain coordination in China, this article uses inter-province across industries input-output tables in 2007, 2010 and 2012, calculates the value chain coordination indexes across 30 provincial level regions and constructs networks of inter-region value chain coordination, based on the method of value added decomposition and the prospective of complex network. It turns out that the inter-region value chain coordination in China demonstrates remarkable small-world network feature, according to the higher value of average clustering coefficients and lower value of average shortest length of paths across 30 nodal regions. With the help of PageRank nodal centralities, it is also found that there are remarkable regional differences among the 30 provincial level regions and Jiangsu Province has the highest nodal centralities and the most significant influences in the network of inter-region value chain coordination in China. Henan Province and Guangdong Province also have the higher nodal centralities while Qinhai, Hainan and Ningxia have the lowest nodal centralities in the network. The result from Dagum Gini coefficients of regional nodal centralities demonstrates that spatial differences among regions and spatial disparities among eastern-middle-western areas narrow down. Moreover, according to the Moran’ I index which is the highest in 2012, there is significantly positive spatial association among the network centralities of regional nodes in the network. The econometrical analysis verifies the theoretic hypothesis that the levels of industrialization, the involvements in international trade and the sizes of economy in the regions positively affect the nodal centralities in the network of inter-region value chain coordination. In other words, ceteris paribus, the higher level of industrialization, the deeper involvement in international trade and the larger size of economy, the stronger the nodal centrality of a region. This research also examines the node clustering and community classification of the 30 nodal regions in the network of inter-region value chain coordination, according to the approach of optimal community clustering based on modularity. The results of node clustering and community classification show that there are several network communities in the network of inter-region value chain coordination and local network interactions among regions are also remarkable. There are notable spatial adjacencies and geographical continuities among the nodal regions in the same network community. Especially, 8 provincial level regions with relatively higher economic development levels including Shanghai, Zhejiang, Anhui, Fujian, Shandong, Hunan, Guangdong and Hainan, belong to the same network community from 2007 to 2012 and have the most stable local interactions with each other in the network of inter-region value chain coordination. The conclusions above can benefit public policy making. Since there are significant network characteristics in the inter-region value chain coordination in China, the government really needs to take network effect into consideration when putting forward the regional development policies. The government also should take advantage of leading role of some developed regions to promote the development of regions which belong to the same network community in the network of inter-region value chain coordination.