地理科学进展 ›› 2021, Vol. 40 ›› Issue (6): 897-910.doi: 10.18306/dlkxjz.2021.06.001

• 研究论文 •    下一篇

基于关联度和复杂度的中国城市技术引入模式及其演化机制

金泽润(), 朱晟君*()   

  1. 北京大学城市与环境学院,北京 100871
  • 收稿日期:2020-08-19 修回日期:2020-12-19 出版日期:2021-06-28 发布日期:2021-08-28
  • 通讯作者: *朱晟君(1984— ),男,安徽淮北人,研究员,博士生导师,博士,主要研究方向为产业升级、全球化与区域发展。E-mail:zhus@pku.edu.cn
  • 作者简介:金泽润(1998— ),男,辽宁沈阳人,硕士生,研究方向为经济地理。E-mail:jinzerun@pku.edu.cn
  • 基金资助:
    国家自然科学基金项目(41971154);国家自然科学基金项目(41701115);国家自然科学基金项目(41731278)

Technology-introduction pattern of cities in China and its mechanism of change based on technology relatedness and complexity

JIN Zerun(), ZHU Shengjun*()   

  1. Department of Urban and Regional Planning, Peking University, Beijing 100871, China
  • Received:2020-08-19 Revised:2020-12-19 Online:2021-06-28 Published:2021-08-28
  • Supported by:
    National Natural Science Foundation of China(41971154);National Natural Science Foundation of China(41701115);National Natural Science Foundation of China(41731278)

摘要:

“创新驱动发展”是中国的重要发展战略,论文利用中国知识产权局记录的城际技术转移专利条目数据,从关联度和复杂度入手,借助Gephi、ArcGIS、Stata等工具,探索中国城市的专利技术引入模式。论文以城市引入技术的平均关联度、平均复杂度为标尺,划分出“高关联度—高复杂度”“低关联度—高复杂度”“低关联度—低复杂度”“高关联度—低复杂度”4种模式。进一步地,不同的技术引入模式之间隐含着演化机制,论文根据城市发展水平将其划分为3个阶段:以低关联度为主导的开拓学习阶段、关联度逐渐提升的强化学习阶段、多元化引进陌生领域技术的跳跃学习阶段。实证研究结果表明,总体上关联度的提升和复杂度的降低,都有利于城市引入该种专利技术,且关联度的提升将促进城市对复杂技术的吸收,并通过分组回归验证了城市技术引入模式的演化机制。

关键词: 技术转移, 关联度, 复杂度, 演化机制, 中国

Abstract:

"Development driven by innovation" is an important strategy of the Chinese government. This study used data including inter-city patent transfer from China Intellectual Property Office for 2017 and 2018 to explore the technology-introduction pattern of cities in China from the perspective of technology relatedness and complexity, using Gephi, ArcGIS, and Stata. This study hypothesized that: 1) cities tend to introduce technologies highly related to local knowledge structure; 2) the more complex a technology is, the less opportunity that cities will introduce it; and 3) the relatedness of a technology will mitigate the effect of its complexity on technology transfer. Based on the average relatedness and average complexity of technologies introduced in each city, this study identified four technology-introduction patterns, which are "high relatedness and high complexity", "low relatedness and high complexity", "low relatedness and low complexity", and "high relatedness and low complexity". Furthermore, unique mechanisms of change exist for different technology-introduction patterns. This study found that the complexity of introduced technologies increases with the economic development stage of the city, while the relatedness of that displays an inverse U-shaped mode. Hence, we divided technology introduction into three stages according to the level of urban development: 1) the learning stage dominated by low relatedness, 2) the reinforcing stage dominated by the increase in relatedness, and 3) the leaping stage dominated by diversification into unfamiliar technology fields. The empirical results show that in general, the increase in technological relatedness and the decrease in complexity of a technology will promote cities to introduce the technology, and the increase in relatedness will encourage cities to introduce more complex technology in that field. Additionally, the mechanism of change was tested through regression by groups—cities were sorted into four groups by their GDP per capita and population density, then we performed regression on technological relatedness and complexity respectively, which shows that the coefficient of relatedness lost significance in the most developed 25% cities, while it remained robust in the other three groups. The coefficient of complexity similarly lost significance in the most developed 50% cities. These results jointly verify the hypothesis of three technology-introduction stages. This study analyzed the pattern of technology-introduction empirically, stressing on the importance of relatedness and complexity in innovation research, which offers a grounded reference for guiding the innovation development path of cities.

Key words: technology transfer, relatedness, complexity, mechanism of change, China