| 基于创新价值链视角下中国创新效率时空格局与影响因素分析 |
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| 引用本文： | 刘树峰,杜德斌,覃雄合,侯纯光.基于创新价值链视角下中国创新效率时空格局与影响因素分析[J].地理科学,2019,39(2):173-182. |
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| 作者姓名： | 刘树峰 杜德斌 覃雄合 侯纯光 |
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| 作者单位： | 华东师范大学全球创新与发展研究院/华东师范大学城市与区域科学学院,上海 200062 |
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| 基金项目： | 国家自然科学基金项目（41471108）资助 |
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| 摘 要： | 基于创新价值链视角,将创新过程分为知识凝结阶段和市场转化阶段,运用网络DEA-SBM模型、核密度分析、自然断裂点和空间面板计量模型等方法分析了2008~2015年中国省际创新总效率及两阶段效率演化动态及其成因,得出以下结论： 中国创新总效率、知识凝结效率和市场转化效率整体处在低位水平,呈波动上升趋势,近年来增速放缓; 创新效率存在明显的阶段性和区际差异,创新知识凝结、市场转化、总过程的效率值分别呈现低值集聚、离散发展和多峰分异格局,在空间上自东向西大体呈阶梯式递减分布,存在空间相关性,空间溢出效应显著; 科研队伍水平、政府政策支持力度与创新效率有显著的正相关关系,研发经费投入强度的持续增加对创新效率起到一定抑制作用,市场化发育程度和对外开放程度对创新效率的影响不显著。现阶段亟需解决企业自身研发能力不足,高校、研究机构科研评价体系不健全与成果转化收益分配不合理,基础研究投入不足和区际间知识生产能力与市场吸纳能力不匹配等问题。
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| 关 键 词： | 创新效率 创新价值链 网络SBM 空间面板计量模型 |
| 收稿时间： | 2017-10-31 |
| 修稿时间： | 2018-01-24 |
Spatial-temporal Pattern and Influencing Factors of China's Innovation Efficiency Based on Innovation Value Chain |
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| Shufeng Liu,Debin Du,Xionghe Qin,Chunguang Hou.Spatial-temporal Pattern and Influencing Factors of China's Innovation Efficiency Based on Innovation Value Chain[J].Scientia Geographica Sinica,2019,39(2):173-182. |
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| Authors: | Shufeng Liu Debin Du Xionghe Qin Chunguang Hou |
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| Institution: | Institute for Innovation and Strategic Studies/School of Urban and Regional Science, East China Normal University, Shanghai 200062, China |
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| Abstract: | From the perspective of the innovation value chain, the innovative process was divided into two stages in this article: knowledge condensation and market transformation. This article analyzes on the overall innovation efficiency, dynamic efficiency evolution and cause in the knowledge condensation stage and market transformation stage on a provincial scale in China from 2008 to 2015 with the methods of network DEA-SBM model, kernel density analysis, natural breaking point and Spatial Panel Econometric Model. We can draw the following conclusions: 1) The overall innovation efficiency, knowledge condensation and market transformation efficiency in China were in the low level with the slower fluctuating rise in the recent years; 2) There were obvious differences between different stages and inter regions. The innovative knowledge condensation efficiency presented a low value cluster, the market transformation efficiency presented a discrete development, and the overall efficiency showed us a double-peak pattern. From east to west, it was generally decreasing step by step in space. Spatial correlation can be seen and spatial spillover effect was remarkable; 3) The level of scientific research team and the support of government policy had a significant positive correlation with innovation efficiency. The continuously increased R&D expenditure depressed the innovation efficiency to a certain extent. While the impacts of degree of marketization development and opening up were not significant. The enterprises lacked of R&D ability; scientific research evaluation system of colleges, universities and research institutes is imperfect and the income distribution of achievement transformation is unreasonable; the investment on basic research is insufficient; the knowledge productivity does not match the market absorption capacity properly. All the above problems are urgently to be solved. |
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| Keywords: | innovation efficiency innovation value chain Network-SBM Spatial Panel Econometric Model |
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