地理科学进展 ›› 2019, Vol. 38 ›› Issue (3): 370-382.doi: 10.18306/dlkxjz.2019.03.007

• 研究论文 • 上一篇    下一篇

中国城市间技术转移的空间特征与邻近性机理

张翼鸥1,2(), 谷人旭1,2,*(), 马双3   

  1. 1. 华东师范大学城市发展研究院,上海 200062
    2. 华东师范大学城市与区域科学学院,上海 200241
    3. 上海社会科学院信息研究所,上海 200235
  • 收稿日期:2018-05-05 修回日期:2018-12-16 出版日期:2019-03-28 发布日期:2019-03-28
  • 通讯作者: 谷人旭 E-mail:zyo9426@126.com;rxgu@re.ecnu.edu.cn
  • 作者简介:

    第一作者简介:张翼鸥(1994— ),女,辽宁沈阳人,硕士生,主要从事经济地理与区域创新研究。E-mail: zyo9426@126.com

  • 基金资助:
    上海市政府决策咨询项目(2018-GR-18)

Spatial characteristics and proximity mechanism of technology transfer among cities in China

Yiou ZHANG1,2(), Renxu GU1,2,*(), Shuang MA3   

  1. 1. Institute of Urban Development, East China Normal University, Shanghai 200062, China
    2. School of Urban and Regional Science, East China Normal University, Shanghai 200062, China
    3. Institute of Information, Shanghai Academy of Social Sciences, Shanghai 200235, China
  • Received:2018-05-05 Revised:2018-12-16 Online:2019-03-28 Published:2019-03-28
  • Contact: Renxu GU E-mail:zyo9426@126.com;rxgu@re.ecnu.edu.cn
  • Supported by:
    Decision Consulting Project of Shanghai Municipal Government, No. 2018-GR-18.

摘要:

技术转移是区域经济发展的主要方式。城市作为多种要素流动的中心,彼此间的相互作用和联系状况,是城市地理研究的重要内容。因此,在知识经济时代,对技术转移的机理进行探讨尤为重要。在此背景下,论文基于国家知识产权局2000—2015年的专利转移数据,借助Gephi、ArcGIS和Stata等工具,对中国技术转移网络的主体结构、分部类模式及其空间特征进行了探究。结果表明:① 就技术转移网络的主体而言,虽然民营企业和高校的地位不断攀升,但多数联系建立在高校、科研院所与其衍生企业之间,说明网络整体连通性较低,溢出效应微弱;② 从分部类专利转移数据来看,对创新能力要求较高的知识往往在相对较少的地方产生,且其转移的空间尺度主要集中于城市内,说明中国城市间技术转移存在一定的地域阻隔;③ 对多维邻近性及其影响的回归分析表明,多数城市在建立创新联系时,更倾向与同一行政区内或地理、技术规模邻近的城市进行专利转移,即地理邻近、技术邻近、社会邻近对中国产学研合作网络的构架具有正向的促进作用。

关键词: 技术转移, 多维邻近性, 创新网络, 空间特征, 中国

Abstract:

Technology transfer is the main route of regional economic development. Cities are the center of the flow of various elements, and interactions and relationships between them is an important content of urban geography research. Therefore, in the era of knowledge economy, the mechanism of technology transfer is particularly important. Consequently, in the perspective of technology transfer and network capital and based on the patent transfer data from the State Intellectual Property Office for 2000-2015, this study explored the main structure, the sub-category model, and the spatial characteristics of the technology transfer network using Gephi, ArcGIS and Stata. The results show that: 1) Although private enterprises and universities are playing an increasingly important role in the technology transfer network in China, most of the connections are established between universities, research institutions, and their derivative enterprises, indicating that the overall connectivity is low and the network spillover effect is weak. 2) According to the patent transfer data of sub-categories, the knowledge required for innovation ability is often generated in relatively few places, and its transfer is mainly concentrated in cities, suggesting that there are some regional barriers to technology transfer between cities in China. 3) In addition, the vast majority of cities are more likely to carry out patent transfer in the same administrative area or between cities with geographical proximity or similar knowledge scale when establishing innovative ties—geographical proximity, technological proximity, and social proximity play a positive role in promoting the development of China's technology transfer network that comprises of enterprises, universities, and research institutions.

Key words: technology transfer, multi-dimensional proximities, innovation network, spatial characteristics, China