Abstract:

This paper took the number of patent applications and patent authorization as the indicators for evaluation, by using spatial classification, coefficient of variation, exploratory spatial data analysis and other methods to analyze the spatial difference of the innovation output at county scale in China, and then explored the influencing factors. The results were shown as follows. (1) From the perspective of the overall distribution pattern, the experimental results are similar to the existing research, but local special and shattered features are obvious. In addition, the areas with high-level output are mainly distributed in Southeast China, and the overall pattern is characterized by "One Belt" with the core of Fuqing and Changle and "Two Regions" are mainly distributed in Beijing-Tianjin-Hebei region and the Yangtze River Delta. Besides, the areas with low-level output are mainly distributed in northwest and western regions in China by Hu Huanyong Line and formed the agglomeration pattern. (2) From the difference degrees of spatial internal gap, the degree is relatively not large and the areas showed a differentiated development trends with high-quality growth in East China, the degree is small and the areas showed a high-quality and balanced trend in North China and Northeast China, the degree is not small and the areas are in a steady catch -up stage, the degree is relatively not large but the areas are in a low-quality growth trend. (3)From the spatial autocorrelation pattern, the phenomenon of spatial agglomeration of similar regions exists and is obvious in local areas. Specifically, the counties with high-level output in hot spots regions are mainly distributed in the Yangtze River Delta Region, Shandong Peninsula Urban Agglomeration and Beijing-Tianjin-Hebei Region, while cold spots regions are mainly distributed in Southwest China and North China.(4) From the perspective of influencing factors, the strength of each factor is different and shows obvious spatial heterogeneity, but the spatial pattern shows a good trend with the driving force of economic strength and high-level industrialization in China.

Key words: innovation output, spatial differentiation, influencing factors, county, China

摘要：

以专利申请量、专利授权量作为评价指标，运用空间分类、变异系数、探索性空间数据分析等方法探究中国县域创新产出的空间分异规律及其影响因素。结果表明：（1）从总体格局看，创新产出高、较高值区主要分布在东部沿海，且形成了“一带二区”的结构特点，即长三角、京津两个高值集聚片区，以及福清市-长乐市为核心的高值连绵带；低、较低值区主要分布在西北部且集聚态势凸显，形成大区域低值连绵区。（2）从空间内部差异程度看，华东地区整体呈现出高质量差异化发展的特征；华北和华南地区创新产出水平处于高质量均衡化发展阶段；华中地区处于稳步追赶阶段；西南、西北和东北地区产出水平不高，整体呈现出低质量均衡化发展特征。（3）区域创新产出集聚态势凸显，热点区域主要集中于长三角地区、山东半岛以及京津冀地区，冷点区主要集中于西南、华北地区。（4）从影响因素分析看，各因子对县域单元创新产出呈现明显的空间异质性。其中，经济实力及工业化水平引领创新高产出水平的新趋势。

关键词: 创新产出, 空间分异, 影响因素, 县域, 中国