地理科学进展 ›› 2016, Vol. 35 ›› Issue (9): 1119-1128.doi: 10.18306/dlkxjz.2016.09.007

• 研究论文 • 上一篇    下一篇

长江经济带创新产出的空间特征和时空演化

张建伟1,2, 石江江1, 王艳华2, 赵建吉2,*()   

  1. 1. 安阳师范学院资源环境与旅游学院,河南 安阳 455000
    2. 河南大学黄河文明与可持续发展研究中心暨黄河文明传承与现代文明建设河南省协同创新中心,河南 开封 475001
  • 收稿日期:2016-04-01 修回日期:2016-07-01 出版日期:2016-09-20 发布日期:2016-09-20
  • 通讯作者: 赵建吉 E-mail:zhaojianji@126.com
  • 作者简介:

    作者简介:张建伟(1984-),男,河南周口人,博士后,讲师,主要从事城市和区域创新研究,E-mail: jwzhang12@163.com

  • 基金资助:
    国家自然科学基金项目(41501136,41301115,41430637,41501141); 中国博士后科学基金项目(2015M582180,2014T70673); 河南省高等学校哲学社会科学研究“三重”重大项目(2014-SZZD-20)

Spatial characteristics and dynamic change of innovation outputs in the Yangtze River Economic Belt

Jianwei ZHANG1,2, Jiangjiang SHI1, Yanhua WANG2, Jianji ZHAO2,*()   

  1. 1. School of Resources Environment and Tourism, Anyang Normal University, Anyang 455000, Henan, China
    2. Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng 475001, Henan, China
  • Received:2016-04-01 Revised:2016-07-01 Online:2016-09-20 Published:2016-09-20
  • Contact: Jianji ZHAO E-mail:zhaojianji@126.com
  • Supported by:
    Foundation: National Natural Science Foundation of China, No.41501136, No.41301115, No.41430637, No.41501141; China Postdoctoral Science Foundation, No.2015M582180, No.2014T70673; Major Program of Philosophy and Social Sciences of Henan Province, No.2014-SZZD-20

摘要:

本文以县(市、区)作为空间分析单元,以专利授权量作为创新产出指标,对1986-2014年长江经济带853个县域创新产出的时空特征进行ESDA分析。结果发现:①长江经济带创新产出的绝对差异在2001年前增长缓慢,其后增长迅猛,2012年后开始降低;相对差异呈现“增加—缩小—缓慢增加—缩小”的态势,其年度空间关联性呈增长趋势;②长江经济带创新产出县域分布呈现出分散、集中、相对集中扩散的态势,创新产出较高的县(市、区)为长三角地区地级市区、经济发达县(市、区)以及中西部地区省会城市市区;③显著空间关联类型总体格局稳定,局部变化明显,县(市、区)显著空间的关联类型以正相关类型为主,显著低低集聚关联类型占主导地位,低低集聚地区主要在西部地区,且有向中部扩展的态势;④长江经济带创新产出空间格局演变过程中,科技创新资源禀赋、教育水平与研发投入、技术溢出与扩散、政策与制度因素的作用较为显著。

关键词: 创新产出, 空间特征, 空间自相关, 时空演化, 长江经济带

Abstract:

This article analyzes the spatial distribution of innovation outputs—measured by the number of patent authorization—in the Yangtze River Economic Belt, using exploratory spatial data analysis (ESDA) method, based on the statistical data of 853 county-level cities from 1986 to 2014.The results are as follow: (1) The absolute difference of innovation output growth of the Yangtze River Economic Belt slowed before 2001, followed by a rapid growth in 2012, then began to decrease again. But the relative difference showed an increase-decrease-increase slowly-decrease trend, with increasing annual spatial correlation; (2) Innovative outputs in the Yangtze River Economic Belt counties showed dispersion, concentration, relative concentration spatial patterns. Counties/districts with higher innovation outputs were the urban districts of prefectural-level cities, economically developed counties, and the urban districts of provincial capital cities in the midwest. (3) The overall pattern of significant spatially correlated type areas was stable, while local changes were significantly. Positive correlation type was dominant at the county level, especially the significant low-low correlation type. Low-low correlation areas were mainly in the western region, but showed a tendency to extend to the central area. (4) Resource endowment, education level and R & D investment, technology spillover and diffusion, and policy and institution played a significant role in the process of change of innovation output spatial pattern in the Yangtze River Economic Belt.

Key words: innovation output, spatial characteristics, spatial autocorrelation, spatial and temporal evolution, Yangtze River Economic Belt