长三角城市群知识创新网络结构韧性时空分异与驱动因素分析  

Analysis of Spatiotemporal Differentiation and Driving Factors of Knowledge Innovation Network Structure Resilience in the Yangtze River Delta Urban Agglomeration

作　　者：王玉珊 刘道强[2,3] 王光辉 孙澍 WANG Yushan;LIU Daoqiang;WANG Guanghui;SUN Shu(The Institute for Sustainable Development,Macao University of Science and Technology,Macao 999087,China;Zhaoqing College,Zhaoqing 526061,China;School of Education,City University of Macao,999087,Macao,China;Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;School of Financial Mathematics and Statistics,Guangdong University of Finance,Guangzhou 510520,China)

机构地区：[1]澳门科技大学可持续发展研究所,中国澳门999087 [2]肇庆学院,肇庆526061 [3]澳门城市大学教育学院,中国澳门999087 [4]中国科学院地理科学与资源研究所,北京100101 [5]广东金融学院金融数学与统计学院,广州510520

出　　处：《地球信息科学学报》2024年第4期1093-1109,共17页Journal of Geo-information Science

基　　金：国家自然科学基金面上项目(71974182,72374191);国家自然科学基金地区项目(72163010);中国科学院青年创新促进会项目(2022152)。

摘　　要：提升城市群知识创新网络结构韧性,有助于建设安全的区域创新体系,保障城市知识创造职能。基于2011—2021年长三角41个城市间合作发表WOS论文数据构建城市群知识创新网络,基于演进韧性理论与复杂网络理论,构建网络结构韧性的“脆弱性-抗毁性-恢复性-演进性”四维评价指标体系,采用社会网络分析和GIS空间分析技术刻画网络结构韧性的时序演化与空间格局,运用GTWR和MRQAP模型识别其驱动因素。结果表明:(1)2011—2021年长三角城市群知识创新网络结构韧性呈上升趋势,立体化特征减弱,传输环境优化,异质性联系减弱,一体化属性增强,且呈现“中部高南北低,东高西低”的差异化空间布局;(2)韧性主导节点为上海、南京、杭州、合肥、苏州等核心城市,确保主导节点的稳定性是保障网络结构韧性的关键;(3)科教支持和产业结构对城市节点韧性具有显著正向驱动力,经济发展、对外开放、人力资本与知识基础的解释力具有鲜明的空间异质性,发挥双因子交互作用可有效推动网络结构韧性演化;(4)网络聚合效应、匹配效应、虹吸效应以及邻近性均驱动网络结构韧性演化,网络拓扑结构、产业相似和人资相似、良好的教育环境,以及制度、社会和组织邻近性均有助于城市间形成强韧的知识合作关系。Improving the structural resilience of the knowledge innovation network of urban agglomerations is conducive to building a safe regional innovation system and ensuring the knowledge creation function of cities.The knowledge innovation network of urban agglomeration is constructed based on the data of papers published on WOS website for 41 cities in the Yangtze River Delta from 2011 to 2021.Based on evolutionary toughness theory and complex network theory,a four-dimensional evaluation index system of network structure toughness is constructed,which is"vulnerability-invulnerability-resilience-evolution".Social network analysis and GIS spatial analysis are used to describe the temporal evolution and spatial pattern of network structure toughness.GTWR and MRQAP models are used to identify the driving factors.The results show that:(1)From 2011 to 2021,the structural resilience of the knowledge innovation network of the Yangtze River Delta urban agglomeration shows an upward trend,with weakened three-dimensional characteristics,optimized transmission environment,weakened heterogeneous connections,and enhanced integration attributes.There are obvious regional differences in the resilience of the network structure,showing a layout trend of"high in the middle and low in the north,high in the east and low in the west";(2)The leading nodes of resilience are core cities such as Shanghai,Nanjing,Hangzhou,Hefei,and Suzhou.Ensuring the stability of the dominant node is the key to ensuring the structural resilience of the network.The vulnerable nodes are mostly concentrated in the northwest and southwest of the Yangtze River Delta.Although they can avoid large-scale network collapse through the regional"lock-in"effect,there may also be connection instability caused by poor network linkage and poor resource transmission;(3)Science and education support and industrial structure have significant positive driving forces on the resilience of urban nodes.The explanatory power of economic development,opening up,human capital,and knowle

关 键 词：知识创新 创新网络 长三角城市群 网络结构韧性 演进韧性 时空分异 GTWR MRQAP 

分 类 号：F124.3[经济管理—世界经济]