中国城市群技术知识单中心与多中心探究

城市空间组织的多中心、网络化特征受到区域经济研究关注。但由于发展阶段、空间尺度、研究视角的差异,城市区域多中心格局有待商榷,知识经济时代解读知识流作用下的城市空间组织应成为经济地理学重点破解的命题。基于中国知识产权局2014年申请和联合申请发明专利数据,运用社会网络分析法和基尼系数,从知识生产和知识网络层面,对京津冀、长三角、珠三角、长江中游、成渝五大城市群技术知识形态多中心和多尺度功能多中心进行测度。研究发现：① 城市群技术知识创新呈现网络化模式,但在形态和功能上多呈现单中心格局,与已有研究基于城市间基础设施联系、企业联系、科学知识联系广泛认同城市群呈现多中心格局的观点不同;② 城市群技术知识网络结构具有空间异质性,国家尺度技术知识流强度的空间不均衡性更加显著,强联系由少数核心城市控制;③ 形态和功能多中心程度存在区域差异,同城市群创新基础、经济实力、协同发展水平有关;④ 功能多中心程度具有尺度敏感性,区域尺度功能多中心程度高于国家尺度。研究结论有助于引发对城市空间组织理论的再思考。

Monocentric or polycentric? A study of technological knowledge in five major urban agglomerations of China

Urban spatial pattern has long been recognized as a central issue of regional economic research. Recent studies have become increasingly interested in the concepts of 'polycentricity' and 'network'. However, despite multiple types of intercity linkages being explored in an analysis of polycentricity, scholars have failed to reach a consensus on the argument whether urban regions feature a morphological or functional polycentricity pattern due to the differences of development stage, spatial scale and research perspective. Exploring the urban spatial pattern under the action of knowledge flow can contribute to a better understanding of innovative space formation and collaborative innovation in a globalizing knowledge economy, which should be a key proposition of economic geography. From a technological knowledge perspective, this paper takes Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), the middle reaches of the Yangtze River (MYR) and Chengdu-Chongqing (CC) urban agglomerations as the objects. Drawing on social network analysis and Gini coefficient, this paper analyzes morphological and functional polycentricity at regional and national geographical scales based on a unique patents and co-patents dataset issued by the National Intellectual Property Administration of P. R. China (CNIPA) in 2014. The main findings of this study are drawn as follows. (1) China's urban agglomerations reach high levels of Gini coefficients of total patents and external connectivity, implying that the structure of technological knowledge production and collaboration can hardly be considered morphologically and functionally polycentric at present, although the network characteristic of technological knowledge collaboration within and beyond the urban agglomerations is found to be clear. The finding differs somewhat from much of the earlier literature which has relied upon data on intercity transportation linkages, intercity firm linkages and intercity scientific knowledge linkages. (2) The technological knowledge network structure of China's urban agglomerations reveals a significant spatial heterogeneity. Geographical proximity is no longer crucial for the formation of technological knowledge collaboration network. It is obvious that the intensity of technological knowledge flows at the national scale tend to be more imbalanced. Analytically, strong ties occur more easily between a few core cities with the strong network position and innovation capability. (3) Comparing morphological and functional polycentricity among China's urban agglomerations, one can obviously see the significant regional differences. In general, the results demonstrate that regional innovation foundation, economic development strength and synergetic development level may affect the degree of polycentricity. (4) The functional polycentricity of China's urban agglomerations has scale sensitivity, with a higher degree of functional polycentricity at the regional scale than that of functional polycentricity at the national scale. These findings of this study will be conducive to stimulating the re-thinking of urban spatial organization theory.