| 城市间技术邻近的类型及其知识溢出的差异——基于知识复杂度的视角 |
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| 引用本文： | 吕爽,孙铁山,孙瑜康.城市间技术邻近的类型及其知识溢出的差异——基于知识复杂度的视角[J].地理研究,2022,41(11):3036-3050. |
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| 作者姓名： | 吕爽 孙铁山 孙瑜康 |
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| 作者单位： | 1.北京大学政府管理学院，北京 1008712.首都经济贸易大学城市经济与公共管理学院，北京 100070 |
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| 基金项目： | 国家自然科学基金项目(41971156);研究阐释党的十九届四中全会精神国家社会科学基金重大项目(20ZDA040);国家自然科学基金青年项目(41901147) |
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| 摘 要： | 随着全球城市创新网络的日益密切，区域创新研究开始由城市本地创新转向网络视角下城市间的知识溢出。本文使用专利数据测度了中国278个地级及以上城市间技术邻近水平，在此基础上引入知识复杂度分析框架讨论城市间技术邻近的不同类型，并利用2007—2019年的城市面板数据实证检验了基于不同类型技术邻近的知识溢出的差异。研究发现：① 城市间的技术邻近与城市知识多样性和遍在性有关，多样化和专业且遍在化的知识结构更容易在城市间产生技术邻近；② 城市间技术邻近与知识存量不存在显著的相关关系，但受到知识结构的影响而呈现出不同类型，具有多样化知识结构特征的城市间技术邻近平均程度最高且内部差异最小；③ 基于不同类型技术邻近的知识溢出有较大差异，与知识遍在性相比，知识多样性所带来的技术邻近更有利于城市间的知识溢出，在知识多样性的基础上，知识遍在性会强化这种效应。
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| 关 键 词： | 城市间技术邻近 知识溢出 知识复杂度 专利数据 |
| 收稿时间： | 2021-12-09 |
Types of inter-city technological proximity and differences in the knowledge spillovers: From the perspective of knowledge complexity |
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| LYU Shuang,SUN Tieshan,SUN Yukang.Types of inter-city technological proximity and differences in the knowledge spillovers: From the perspective of knowledge complexity[J].Geographical Research,2022,41(11):3036-3050. |
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| Authors: | LYU Shuang SUN Tieshan SUN Yukang |
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| Institution: | 1. School of Government, Peking University, Beijing 100871, China2. School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing 100070, China |
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| Abstract: | It is the key issue of current regional studies to understand how to promote regional knowledge exchange and innovation growth. With the development of the global urban innovation network, the focus of regional innovation research has begun to shift from the intra-city innovation to the inter-city technological proximity and knowledge spillovers from the network perspective. The acquisition of knowledge in a region does not only originate from local creation, but the exchange of knowledge between cities is also an important factor driving the growth of regional knowledge. This paper measures the inter-city technological proximity by using the patent data of 278 prefecture-level and above cities in China. The knowledge complexity is introduced to understand different types of inter-city technological proximity, and their differences in promoting knowledge spillovers using the city level panel data from 2007 to 2019. We divide the knowledge complexity into two dimensions, namely diversity and ubiquity, as a basis for discussing the different types of inter-city technological proximity. Our results show that (1) inter-city technological proximity is related to the diversity and ubiquity of urban knowledge structure, and the diversified, or the specialized and ubiquitous knowledge structures are easier to generate high inter-city technological proximity; (2) the types of inter-city technological proximity are influenced by the knowledge structures of cities, instead of the knowledge stock of cities. The average technological proximity between cities with diversified knowledge structures is the highest with the least internal variation; (3) knowledge spillovers based on the different types of inter-city technological proximity vary greatly, and compared to the knowledge ubiquity, the technological proximity brought by the knowledge diversity is more favorable to the inter-city knowledge spillover; and on the basis of knowledge diversity, the knowledge ubiquity will strengthen this effect. Our contributions are twofold. Firstly, we distinguish different types of inter-city technological proximity according to the city′s knowledge structure. Secondly, we construct a spatial weight matrix based on the inter-city technological proximity and reveal that different types of inter-city technological proximity can generate differentiated knowledge spillovers through the spatial econometric model. Our findings help to understand how the inter-city technological proximity is determined by the city′s knowledge structure and its differential effect on knowledge spillovers, which provide implications for the choice of innovation policies in different cities. |
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| Keywords: | inter-city technological proximity knowledge spillovers knowledge complexity patents data |
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