长江经济带技术创新网络格局演化及其多维邻近性机制  

Evolution of Technology Innovation Network and Multi-proximity Mechanism in Yangtze River Economic Belt

作　　者：江凯乐 梁双波[1] JIANG Kai-le;LIANG Shuang-bo(Key Laboratory of Watershed Geographic Sciences,Nanjing Institute of Geography and Limnology,Chinese Academy of Sciences,Nanjing 210008,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院南京地理与湖泊研究所中国科学院流域地理学重点实验室,江苏南京210008 [2]中国科学院大学,北京100049

出　　处：《长江流域资源与环境》2023年第9期1796-1805,共10页Resources and Environment in the Yangtze Basin

基　　金：国家自然科学基金项目(42071163);中国科学院南京地理与湖泊研究所自主部署项目(NIGLAS2022GS06)。

摘　　要：区域创新网络是建设创新型国家的重要支撑,也是实现区域高质量发展的重要保障。运用长江经济带城市间专利转移与合作数据,引入K-means聚类、地理探测器等方法,分析了长江经济带技术转移与合作的时空演化特征,探索了不同类型城市在技术创新网络中所扮演角色变化,并分析了专利流向的发展规律、多维邻近性对技术转移与合作的影响。研究发现:(1)长江经济带的技术创新网络呈现明显的异质性特征,表现在网络密度分布和重要节点分布两个方面;(2)长江经济带技术创新网络中的城市节点类型与特征都发生了较大的变化,从单一中心向多中心演变,技术创新网络一级中心城市的辐射带动作用不断加强;(3)专利净流入量与专利申请量、人均GDP呈现倒U形的关系。认知邻近、社会邻近、制度邻近、经济邻近、产业邻近、技术邻近和地理邻近都对技术转移与合作产生影响,但在不同时期其影响的强度和显著性存在差异,并且不同邻近因子之间具有显著的交互增强作用。The construction of regional innovation networks is an important support for building an innovative country and a crucial guarantee for achieving high-quality regional development.Using patent transfer and cooperation data between cities in the Yangtze River Economic Belt,this paper employs methods of K-means clustering and geodetector to analyze the spatiotemporal evolution characteristics of technology transfer and cooperation in the Yangtze River Economic Belt.In particular,this paper explores the role chenges of cities of different types in the technology innovation network,analyzes the development patterns of patent flow,and examines the impact of multi-proximity on technology transfer and cooperation.The following conclusions are drawn:(1)The technology innovation network in the Yangtze River Economic Belt exhibits apparent heterogeneity in terms of network density distribution and important node distribution.(2)The types and features of city nodes in the technology innovation network have undergone significant changes,evolving from one single center to multiple centers,and the radiation-driven effect of first-level central cities has been constantly strengthened.(3)The net inflow of patents exhibits an inverted U-shaped relationship with patent application and per capita GDP.Cognitive proximity,social proximity,institutional proximity,economic proximity,industrial proximity,technological proximity,and geographical proximity all have impacts on technology transfer and cooperation,but their intensity and significance vary at different times,and there is a significant interaction enhancement effect between different proximity factors.

关 键 词：专利 创新网络 多维邻近性 长江经济带 

分 类 号：F49[经济管理—产业经济] F124.3