地理学报 ›› 2014, Vol. 69 ›› Issue (12): 1779-1789.doi: 10.11821/dlxb201412004

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中国区域创新的时空动态分析

程叶青1,2(), 王哲野3, 马靖4   

  1. 1. 海南师范大学地理与旅游学院, 海口 571158
    2. 中国科学院东北地理与农业生态研究所, 长春 130102
    3. Department of Geography, Kent State University, Kent 44242, Ohio, USA
    4. 深圳中学, 深圳 518001
  • 收稿日期:2013-11-14 修回日期:2014-06-19 出版日期:2014-12-25 发布日期:2015-01-24
  • 作者简介:

    作者简介:程叶青 (1976-), 男, 湖南武冈人, 博士, 副研究员, 中国地理学会会员 (S110006162M), 主要从事经济地理与乡村发展研究。E-mail: yqcheng@iga.ac.cn

  • 基金资助:
    中国科学院重点部署项目 (KZZD-EW-06, KSZD-EW-Z-021);教育部人文社会科学重点研究基地重大项目 (13JJD790008)

Analyzing the space-time dynamics of innovation in China

Yeqing CHENG1,2(), Zheye WANG3, Jing MA4   

  1. 1. College of Geography and Tourism, Hainan Normal University, Haikou 571158, China
    2. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China
    3. Department of Geography, Kent State University, Kent, Ohio 44242, USA
    4. Shenzhen Middle School, Shenzhen, Guangdong 518001, China
  • Received:2013-11-14 Revised:2014-06-19 Online:2014-12-25 Published:2015-01-24
  • Supported by:
    Key Research Program of the Chinese Academy of Sciences, No.KZZD-EW-06-03, No.KSZD-EW-Z-021;Key Project of the Ministry of Education of China, No.13JJD790008]

摘要:

基于探索性空间数据分析和验证性空间面板模型,本文探讨了2000年以来中国区域创新的时空动态。结果表明:① 自创新战略实施以来,中国各省区创新产出的年均增长率几乎都经历了一个剧烈的加速过程,说明区域创新能力的总体提升,但是,东部沿海地区仍然在创新产出中居于压倒性地位,导致“沿海—内陆”分化加剧和区域鸿沟的进一步突出,省区创新可能会陷入“强者愈强,弱者愈弱”的“马太效应”;② 中国区域创新产出与创新投入的空间集聚随时间推移不断强化,通过识别不同时期各变量“热点”,表明创新产出“热点”地区与创新投入“热点”具有高度的时空耦合特征;③ 人均GDP、研发投入、研发人员及在校大学生数对省区创新产出有显著的直接影响。省区间创新活动存在明显的空间溢出效应,其知识溢出的地理区域跨越了省区边界。空间依赖性的存在导致省区间创新活动具有反馈效应,相邻省区的知识溢出对该省区的创新活动具有实质性影响。

关键词: 区域创新, ESDA, CSDA, “热点”, 面板空间杜宾模型, 知识溢出, 中国

Abstract:

Through an integration of exploratory spatial data analysis (ESDA) and confirmatory spatial data analysis (CSDA), this study examines the space-time dynamics of regional innovation at the provincial scale in China from 2000 to 2011. The results show that: firstly, since the implementation of national innovation strategy, the annual growth ratio of innovation outputs of the provinces in China has experienced a drastic process of acceleration, which suggests the overall improvement of regional innovation capabilities. However, an overwhelming status in growth rate still belongs to eastern region, leading to the rise of the coastal-interior division and the divergence among regions, and regional innovation in China may fall into the “Matthew Effect” that the strong will become stronger and the weak will be constantly weaker. Secondly, regional innovation outputs and inputs in China experience an increasing change of spatial clustering over time. Various types of hot spots are identified over time, revealing that innovation hot spots overlay well with other variables. Finally, the selected explanatory variables, such as GDP, RDE, RDP and PCH, have significant direct impacts on provincial innovation in China. There exist obvious spatial spillover effects in provincial innovation activities, and the geographic region of which has crossed the provincial border. The spatial dependence of innovation activities gives rise to the feedback among the provinces, and the acknowledge spillover of adjacent province have material influence on a specific province.

Key words: regional innovation, exploratory spatial data analysis, confirmatory spatial data analysis, hot spot, spatial panel Dubin mode, acknowledge spillover, China