地理研究 ›› 2014, Vol. 33 ›› Issue (10): 1825-1836.doi: 10.11821/dlyj201410004

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浙江省区域创新产出空间分异特征及成因

蒋天颖()   

  1. 宁波大红鹰学院, 宁波 315175
  • 收稿日期:2014-01-08 修回日期:2014-07-05 出版日期:2014-10-10 发布日期:2014-10-10
  • 作者简介:

    作者简介:蒋天颖(1976-),男,浙江诸暨人,博士,教授,主要从事区域创新和空间计量等研究。E-mail: jty7608@126.com

  • 基金资助:
    国家自然科学基金项目(71372001);浙江省自然科学基金项目(LY13G030025)

Spatial differentiation and its influencing factors of regional innovation output in Zhejiang province

Tianying JIANG()   

  1. Ningbo Dahongying University, Ningbo 315175, Zhejiang, China
  • Received:2014-01-08 Revised:2014-07-05 Online:2014-10-10 Published:2014-10-10

摘要:

通过构建总体差异测度指数,并结合运用核密度估计等多种空间统计方法,分析浙江省区域创新产出的空间分异特征及其影响因素,结果表明:2006-2012年,浙江省区域创新产出总体存在较大差异,并呈现波动式上升趋势;浙江省区域创新产出分异增强,空间核密度呈现出由相对均匀到极化的演化趋势;浙江省区域创新产出整体上呈现高值和低值集聚分布,且集聚程度逐渐增强;各县域创新产出同样具有空间集聚性,杭州与宁波市辖区成为热点区域;空间指向性明显,整体表现出“东高西低、北高南低”的空间趋势面分布;由回归分析得出该时期浙江省区域创新产出空间分异主要受经济基础、政策制度、技术溢出和空间区位四个主要因素的影响。

关键词: 创新产出, 空间分异, 核密度估计, 成因

Abstract:

By general difference index and multiple spatial data analysis such as kernel density estimate, this paper makes an analysis of spatial distribution of regional innovation output and its influencing factors in Zhejiang province. The results are as follows: from 2006 to 2012, there are great differences of regional innovation output in Zhejiang, featured by a slow fluctuated rising trend, which shows an obvious trend of unbalanced development. It is the main stage for the unbalanced development of regional innovation in Zhejiang from 2006 to 2009. The kernel density estimation shows that there are increasing differences in the regional innovation output in this province. The spatial density tends to change from relative equality to polarization. The spatial hot spots of regional innovation output are mainly concentrated in the northern and eastern parts of Zhejiang, while the spatial cold spots are mainly concentrated in the southwest. And what's more, the regional innovation output presents a concentrational trend with Hangzhou, Ningbo and the surrounding counties as the hotspot regions. The overall regional innovation output has its obvious spatial directivity which shows the spatial distribution of being high in the east, low in the west and high in the north, and low in the south. With time going by, the original trend which is high in the middle but low in both ends is gradually replaced by the increasing trend from west to east. Finally, a conclusion can be drawn from the regression analysis that spatial distribution of regional innovation output in Zhejiang is mainly influenced by four factors: economic growth foundation, innovation policies, technology spillover and spatial proximity. In 2006, economic growth foundation, innovation policies and technology spillover have a positive impact on spatial distribution of regional innovation output in this province. Compared with 2006, in 2012, technology spillover, spatial proximity and innovation policies become main factors. Corresponding suggestions are put forward subsequently: (1) promoting the high-tech industry construction actively. (2) formulating the corresponding policies and regulations to ensure that the development of regional innovation is institutionalized and standardized and has its procedures. (3) establishment of high-tech parks within the provincial range.

Key words: innovation output, spatial differentiation, kernel density estimate, influencing factors