资源科学 ›› 2022, Vol. 44 ›› Issue (2): 365-374.doi: 10.18402/resci.2022.02.12

• 资源管理 • 上一篇    下一篇

东北地区城际专利转移的空间—行业路径与影响因素

王姣娥1,2(), 杜方叶1,2, 景悦3, 杜德林1,2   

  1. 1.中国科学院地理科学与资源研究所,中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
    2.中国科学院大学资源与环境学院,北京 100049
    3.佛罗里达大学,盖恩斯维尔 32601,美国
  • 收稿日期:2021-07-01 修回日期:2021-10-27 出版日期:2022-02-25 发布日期:2022-04-13
  • 作者简介:王姣娥,女,湖南涟源人,研究员,主要从事交通地理与区域发展研究。E-mail: wangje@igsnrr.ac.cn
  • 基金资助:
    国家社会科学基金重大项目(20&ZD099)

Spatial-industry paths of technology transfer: An empirical study of Northeast China

WANG Jiaoe1,2(), DU Fangye1,2, JING Yue3, DU Delin1,2   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    3. University of Florida, Gainesville, FL 32601, USA
  • Received:2021-07-01 Revised:2021-10-27 Online:2022-02-25 Published:2022-04-13

摘要:

创新驱动发展是新时期东北实现全面振兴的必经之路。本文使用2016年全国尺度的发明专利转移数据,分析东北地区城际专利转移空间—行业路径的特征,并进一步借助Tobit回归模型,揭示东北地区城际专利转移路径形成的影响因素。结果表明:①东北地区的城际专利转移以跨区域转移为主。跨区域专利转移在空间、行业和路径方面均呈现明显的聚集性,空间上主要集中于北京、常州、深圳、益阳和上海等,行业主要集中于化学原料和化学制品制造业、装备制造业、医药制造业等。②区域内专利转移具有一定的空间和行业聚集性,但路径聚集性不明显。③城市主体的行政等级、创新载体数量、对外开放程度、城市间创新合作、城市间创新能力差异、地理邻近性、行业发展邻近性以及城市创新邻近性均对东北地区专利转移具有显著影响。本文结果可为挖掘东北地区的产业发展潜力、构建技术合作网络以及制定区域合作和创新发展驱动战略提供指导。

关键词: 创新, 技术转移, 产业, 跨区域, Tobit模型, 东北地区

Abstract:

As the Chinese economy entered a “new normal” state, the development of Northeast China suffered keenly. Innovation plays an important role in promoting industrial development. Thus, revealing the industry characteristics and specific paths of innovation resources flow is an important approach for examining industrial development in the region. This study explored the characteristics of flow of innovation resources from the industry and spatial perspectives as well as the mechanism. The results indicate that: (1) Patent transfers in Northeast China have obvious spatial and industry clustering characteristics. The number of patents transferred within the Northeast region is significantly greater than that of cross-regional patent transfer. Patent input and output networks have similar spatial patterns, but the spatial aggregation of the patent input network is significantly higher than that of the patent output network. Patents transferred within the Northeast region are mainly concentrated in equipment manufacturing and heavy chemical industries such as chemical raw materials and chemical product manufacturing, general equipment manufacturing, and the pharmaceutical manufacturing industry. (2) The spatial-industry routes of patent transfer in the Northeast region are mainly concentrated in the equipment manufacturing and heavy chemical industries between the cities of Dalian, Shenyang, Harbin, and Changchun. Cross-regional patent input network shows certain path aggregation characteristics, and 30% of patent transfers are concentrated in the raw materials and chemical product manufacturing from Beijing to Shenyang. In contrast, the number of patents on each patent output path is relatively balanced. (3) The administrative level of the city, the number of innovation carriers, the degree of opening, inter-city innovation cooperation, geographical proximity, industrial development proximity and urban innovation proximity have significant impact on the patent transfer in northeast China. This study can provide some reference for the development of industries in Northeast China.

Key words: innovation, technology transfer, industry, cross-regional, Tobit model, Northeast China