中国城市绿色创新空间关联网络及其影响效应  

Spatial association network of green innovation in Chinese cities and its impact effect

作　　者：王婧[1,2] 杜广杰 WANG Jing;DU Guangie(School of Urban and Regional Sciences,Shanghai University of Finance and Economics,Shanghai 200082,China;Institute of Finance and Economics,Shanghai University of Finance and Economics,Shanghai 200082,China)

机构地区：[1]上海财经大学城市与区域科学学院,上海200082 [2]上海财经大学财经研究所,上海200082

出　　处：《中国人口·资源与环境》2021年第5期21-27,共7页China Population,Resources and Environment

基　　金：国家自然科学基金面上项目“村镇绿色居住能源系统模式探索:基于生命周期评价的视角”(批准号:42071291);上海财经大学研究生创新基金资助项目“空间溢出视角下绿色创新与中国城市绿色发展”(批准号:CXJJ-2020-309)。

摘　　要：绿色创新能够在保证环境质量的前提下,提高生产效率实现社会进步,有助于我国社会经济发展可持续转型。文章从关系型视角拓展绿色创新相关研究,基于中国336个城市相互间的绿色专利联合申请信息构造绿色创新空间关联网络,弥补了现有研究多基于属性数据的缺陷。进而基于网络分析技术考察绿色创新空间关联网络的结构特征,并构造了一种新的嵌套分解方法对网络嵌套结构特征进行分析。最终,揭示绿色创新空间关联网络的整体结构以及个体节点网络位置在城市绿色创新水平提升中所发挥的作用。研究发现:①样本城市间绿色创新合作关系平均数为2.04项,而北京市与样本内其他城市的绿色创新合作关系平均数约为228项。②网络内仅北京、南京、杭州、上海、武汉等少部分城市拥有较强的影响力,而样本内78.9%的城市度数中心度小于1,位于网络边缘位置。③我国城市绿色创新空间关联网络呈现出典型嵌套性结构,通过将绿色创新空间关联网络分解为不同的子网络,进一步识别了不同子网络的网络密度以及各城市在不同子网络内的中心度特征。④通过绿色创新空间关联网络,各类创新主体能够吸收更大空间范围内的资源、知识与技术经验,从而超越自身认知局限而提升其创新能力。根据空间计量模型估计结果,绿色创新空间关联网络密度的提升能够显著提高城市绿色创新水平。⑤创新网络中占据不同位置的创新主体所接收到的信息和知识是不同的,占据核心位置的成员相比非核心成员拥有更强的信息优势,由此可能加剧网络内各成员的非均衡发展趋势。Green innovation can improve production efficiency and achieve social progress while ensuring environmental quality, which will contribute to the sustainable transformation of China’s socio-economic development. This paper expanded the research related to green innovation from a relational perspective, and constructed the spatial association network of green innovation based on the information of joint application for green patents among 336 cities, which made up for the defects of existing research based on attribute data. Then the overall structural characteristics and nested structural characteristics of the green innovation spatial association network were analyzed based on network analysis methods. Finally, based on the spatial econometric model, this paper identified the role of network structure and spatial spillover effects in the promotion of urban green innovation. The main research conclusions were as follows:① The average number of green innovation cooperative relationships between cities was 2.04, while the average number of green innovation cooperative relationships between Beijing and other cities in the sample was about 228.② Only a few cities in the network, such as Beijing, Nanjing, Hangzhou, Shanghai, and Wuhan, had strong influence, and 78.9% of the cities in the sample had a degree centrality less than 1, with the cities being located at the edge of the network.③ China’s urban green innovation spatial association network presented a typical nested structure. By decomposing the green innovation spatial association network into different sub-networks, the paper further identified the network density of different sub-networks and the degree of each city in different sub-networks.④ Through the green innovation cooperation network, various innovation entities could absorb resources, knowledge and technical experience in a larger spatial scale, so as to exceed their own cognitive limitations and enhance their innovation capabilities. According to the estimation results of the spatial me

关 键 词：绿色创新 空间关联网络 网络分析 绿色专利 

分 类 号：F124.3[经济管理—世界经济]