地理研究 ›› 2019, Vol. 38 ›› Issue (2): 259-272.doi: 10.11821/dlyj020170366

• 研究论文 • 上一篇    下一篇

中国重点产业创新产出时空分异及影响因素

王彬燕1(), 王士君1(), 田俊峰2, 浩飞龙1   

  1. 1. 东北师范大学地理科学学院,长春130024
    2. 吉林大学地球科学学院,长春130061
  • 收稿日期:2017-04-25 修回日期:2018-08-11 出版日期:2019-02-20 发布日期:2019-03-08
  • 作者简介:

    作者简介:王彬燕(1991- ),女,四川三台人,博士研究生,主要从事经济地理、城市与区域创新研究。E-mail: wangby956@nenu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41630749,41471142,41571150)

Spatial-temporal characteristics of innovation output and its influencing factors of the key industries in China

Binyan WANG1(), Shijun WANG1(), Junfeng TIAN2, Feilong HAO1   

  1. 1. School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
    2. College of Earth Sciences, Jilin University, Changchun 130061, China
  • Received:2017-04-25 Revised:2018-08-11 Online:2019-02-20 Published:2019-03-08

摘要:

采用Mann-Kendall、Theil指数、空间马尔科夫链等方法,对1994-2014年中国十大重点产业创新产出时空演化进行分析,并对创新发展空间分异成因进行了探讨。研究表明:① 研究期内,中国重点产业创新产出分为两个时段,成果呈指数型增长;② 创新产出差异先增后减,东、中、西、东北板块间差异小于板块内部,创新产出发展呈现出传染扩散与等级扩散的双重特征;③ 邻域环境影响创新发展,创新产出水平发生类型转移的单元集中在东、中部地区,且活跃度不断提升;④ 经济社会与政策条件、高等教育基础条件对重点产业创新发展有明显的正向驱动作用,而工业化程度影响微弱,未来加强对高等教育基础与智力资本的投入可进一步增强重点产业创新发展竞争力。

关键词: 重点产业, 创新产出, 时空分异, 邻域环境, 影响因素, 中国

Abstract:

The innovation, development and technological progress of the ten key industries (iron and steel, automobiles, ships, petrochemicals, textiles, light industry, nonferrous metals, equipment manufacturing, electronic information and logistics) in China are highly concerned by the state and expected by the public. So the research on it is of great significance. Firstly, the Mann-Kendall method is used to divide the development stages of the ten key industries of China from 1994 to 2014, and to understand the evolution of the key industries. Secondly, this paper analyzes the innovation output difference, spatial pattern and spatial-temporal transfer characteristics of key industries in the prefecture-level cities by using the Theil index, Markov and spatial Markov chains method respectively. Finally, based on factor analysis and multiple regression model, this paper discusses the factors that influence the spatial differentiation of the innovation development of the ten key industries in China. The conclusions are drawn as follows: (1) The development of the innovation outputs of the ten key industries can be divided into two stages (the first stage is from 1995 to 2006, the second stage is from 2007 to 2014), and the result of innovation outputs of the ten key industries is in exponential growth. (2) The difference of the innovation outputs of the ten key industries increased at first and then decreased, and the inter-regional difference among the four regions (Eastern, Central, Western and Northeastern China) is less than the intra-regional difference. The development of innovation outputs of the ten key industries presents the dual characteristics of contagious and hierarchical diffusion. (3) The neighborhood environment plays an important role in the development of the ten key industries. Under different environmental constraints, the transition probability of different types of unit is different, and the higher the neighborhood environment level is, the stronger the driving force to low level units is. In the two periods, the transferred units of the innovation outputs of the ten key industries are mainly concentrated in the eastern and central regions of China. The activity of the transfer is increasing, and the transferred units are concentrated in spatial distribution. (4) The social economic and policy factors and the basic condition of higher education have obvious positive driving effect on the innovation and development of the ten key industries, while the effect of industrialization is weak. In the next period of time, the innovation and development competitiveness of the ten key industries can be improved by strengthening the investment in the foundation of higher education and intellectual capital.

Key words: key industries, innovation outputs, spatial-temporal differentiation, neighborhood environment, influencing factor, China