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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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:1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;2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;3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。
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.
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.
引文
[1]吕拉昌,黄茹,廖倩.创新地理学研究的几个理论问题[J].地理科学,2016,36(5):653-661.[Lyu Lachang,Huang Ru,Liao Qian.Several theoretical issues on innovation geography.Scientia Geographica Sinica,2016,36(5):653-661.]
[2]蔡跃洲,付一夫.全要素生产率增长中的技术效应与结构效应--基于中国宏观和产业数据的测算及分解[J].经济研究,2017,52(1):72-88.[Cai Yuezhou,Fu Yifu.The technical and structural effects of TFP growth:measurement and decomposition based on China’s macro and sector data.Economic Research,2017,52(1):72-88.]
[3]李静,楠玉,刘霞辉.中国研发投入的“索洛悖论”--解释及人力资本匹配含义[J].经济学家,2017(1):31-38.[Li Jing,Nan Yu,Liu Xiahui.The“Solow Paradox”of China's R&D--Explanation and implication of human capital matching.Economist,2017(1):31-38.]
[4]周程,张杰军.跨越创新过程中的“死亡之谷”--科技成果产业化问题刍议[J].科学学与科学技术管理,2010(3):50-55.[Zhou Cheng,Zhang Jiejun.To span the″valley of death″in the innovation process:About industrialization of scientific and technical achievements.Science of Science and Management of Science and Technology,2010(3):50-55.]
[5]Bush V.Science,the endless frontier:A report to the President[M].Washington:US Governmen Print Office,1945.
[6]孙早,许薛璐.前沿技术差距与科学研究的创新效应--基础研究与应用研究谁扮演了更重要的角色[J].中国工业经济,2017(3):5-23.[Sun Zao,Xu Xuelu.Technology distance to frontier and the innovative effect of scientific research--Which one plays more important role,basic research or applied research.Chinese Industrial Economy,2017(3):5-23.]
[7]肖文,林高榜.政府支持、研发管理与技术创新效率--基于中国工业行业的实证分析[J].管理世界,2014(4):71-80.[Xiao Wen,Lin Gaobang.Government support,R&D management and technological innovation efficiency:An empirical analysis based on China's industrial sector.Management World,2014(4):71-80.]
[8]Sampat B N.Patenting and US academic research in the 20th century:The world before and after Bayh-Dole[J].Research Policy,2006,35(6):772-789.
[9]Dushnitsky G,Lenox M J.When do incumbents learn from entrepreneurial ventures?:Corporate venture capital and investing firm innovation rates[J].Research Policy,2005,34(5):615-639.
[10]张学勇,张叶青.风险投资、创新能力与公司IPO的市场表现[J].经济研究,2016,51(10):112-125.[Zhang Xueyong,Zhang Yeqing.Venture capital capability and post-IPO performance.Economic Research,2016,51(10):112-125.]
[11]Drucker P.Innovation and entrepreneurship[M].London:Routledge,2014.
[12]Schumpeter J A.Socialism,capitalism and democracy[M].New York:Harper and Brothers,1942.
[13]Arrow K.Economic welfare and the allocation of resources for invention[M]//The rate and direction of inventive activity:Economic and social factors.Princeton:Princeton University Press,1962:609-626.
[14]Guan J C,Yam R C M.Effects of government financial incentives on firms’innovation performance in China:Evidences from Beijing in the 1990s[J].Research Policy,2015,44(1):273-282.
[15]杜志威,吕拉昌,黄茹.中国地级以上城市工业创新效率空间格局研究[J].地理科学,2016,36(3):321-327.[Du Zhiwei,Lyu Lachang,Huang Ru.Spatial pattern of industrial innovation efficiency for Chinese cities at prefecture level and above.Scientia Geographica Sinica,2016,36(3):321-327.]
[16]谭俊涛,张平宇,李静.中国区域创新绩效时空演变特征及其影响因素研究[J].地理科学,2016,36(1):39-46.[Tan Juntao,Zhang Pingyu,Li Jing.Spatio-temporal characteristics of regional innovation performance and its influencing factors in China.Scientia Geographica Sinica,2016,36(1):39-46.]
[17]覃雄合,杜德斌,刘树峰,等.中国省际高校科研成果转化效率时空格局与影响因素--基于网络SBM模型的评价[J].地理研究,2017,36(9):1641-1652.[Qin Xionghe,Du Debin,Liu Shufeng et al.Spatial-temporal pattern and influencing factors in transforming efficiency of scientific research achievements of universities on a provincial scale in China based on the network SBM method.Geographical Research,2017,36(9):1641-1652.]
[18]Hansen M T,Birkinshaw J.The innovation value chain[J].Harvard Business Review,2007,85(6):121.
[19]国家统计局,科学技术部.中国科技统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China,The Ministry of Science and Technology.China statistical yearbook on science and technology.Beijing:China Statistics Press,2007-2015.]
[20]国家统计局.中国统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China.China statistical yearbook.Beijing:China Statistics Press,2007-2015.]
[21]国家统计局.中国城市统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China.China Urban Statistical Yearbook.Beijing:China Statistics Press,2007-2015.]
[22]佟连军,宋亚楠,韩瑞玲,等.辽宁沿海经济带工业环境效率分析[J].地理科学,2012,32(3):294-300.[Tong Lianjun,Song Yanan,Han Ruiling et al.Analysis of industrial environmental efficiency of Liaoning coastal economic belt.Scientia Geographica Sinica,2012,32(3):294-300.]
[23]余泳泽,刘大勇.我国区域创新效率的空间外溢效应与价值链外溢效应--创新价值链视角下的多维空间面板模型研究[J].管理世界,2013(7):6-20.[Yu Yongze,Liu Dayong.The effect of the space outflow of China's regional innovation and the effect of the outflow of value chains:A study,from the perspective of the innovative value chain on the model of the panel of multidimensional space.Management World,2013(7):6-20.]
[24]Guan J,Chen K.Measuring the innovation production process:A cross-region empirical study of China’s high-tech innovations[J].Technovation,2010,30(5):348-358.
[25]Tone K,Tsutsui M.Network DEA:A slacks-based measure approach[J].European Journal of Operational Research,2009,197(1):243-252.
[26]孙才志,李欣.基于核密度估计的中国海洋经济发展动态演变[J].经济地理,2015,35(1):96-103.[Sun Caizhi,Li Xin.Dynamic evolution analysis of China's marine economy development based on kernel density estimation.Economic Geography,2015,35(1):96-103.]
[27]程钰,任建兰,陈延斌,等.中国环境规制效率空间格局动态演变及其驱动机制[J].地理研究,2016,35(1):123-136.[Cheng Yu,Ren Jianlan,Chen Yanbin et al.Spatial evolution and driving mechanism of China's environmental regulation efficiency.Geographical Research,2016,35(1):123-136.]
[28]陈耀.新一轮东北振兴战略要思考的几个关键问题[J].经济纵横,2017(1):8-12.[Chen Yao.Several key issues about the strategy of a new round of revitalization.Economic Review,2017(1):8-12.]
[29]金凤君,王姣娥,杨宇,等.东北地区创新发展的突破路径与对策研究[J].地理科学,2016,36(9):1285-1292.[Jin Fengjun,Wang Jiaoe,Yang Yu et al.The paths and solutions of innovation development in Northeast China.Scientia Geographica Sinica,2016,36(9):1285-1292.]
[30]Florida R.The rise of the creative class--Revisited:Revised and expanded[M].New York:Basic Books(AZ),2014.
[31]王小鲁,樊纲,余静文.中国分省份市场化指数报告(2016)[D].北京:社会科学文献出版社,2016.[Wang Xiaolu,Fan Gang,Yu Jingwen.Report on marketization index of provinces in China(2016).Beijing:Social Sciences Academic Press,2016]
[32]郭迎锋,顾炜宇,乌天玥,等.政府资助对企业R&D投入的影响--来自我国大中型工业企业的证据[J].中国软科学,2016(3):162-174.[Guo Yingfeng,Gu Weiyu,Wu Tianyue et al.The impact of government funding on business R&D expenditure.China Soft Science,2016(3):162-174.]
[33]迈克尔D沃德,克里斯蒂安·格里蒂奇.空间回归模型[M].上海:格致出版社,2016.[Michael D Ward,Kristian Skrede Gleditsch.Spatial regression model.Shanghai:Truth&Wisdom Press,2016.]
(1)东部地区:北京、天津、河北、上海、江苏、浙江、福建、山东、广东和海南10省;中部地区:山西、安徽、江西、河南、湖北和湖南6省;西部地区:内蒙古、广西、重庆、四川、贵州、云南、西藏、陕西、甘肃、青海、宁夏和新疆12省(区、市);东北地区:辽宁、吉林、黑龙江3省。
[2]蔡跃洲,付一夫.全要素生产率增长中的技术效应与结构效应--基于中国宏观和产业数据的测算及分解[J].经济研究,2017,52(1):72-88.[Cai Yuezhou,Fu Yifu.The technical and structural effects of TFP growth:measurement and decomposition based on China’s macro and sector data.Economic Research,2017,52(1):72-88.]
[3]李静,楠玉,刘霞辉.中国研发投入的“索洛悖论”--解释及人力资本匹配含义[J].经济学家,2017(1):31-38.[Li Jing,Nan Yu,Liu Xiahui.The“Solow Paradox”of China's R&D--Explanation and implication of human capital matching.Economist,2017(1):31-38.]
[4]周程,张杰军.跨越创新过程中的“死亡之谷”--科技成果产业化问题刍议[J].科学学与科学技术管理,2010(3):50-55.[Zhou Cheng,Zhang Jiejun.To span the″valley of death″in the innovation process:About industrialization of scientific and technical achievements.Science of Science and Management of Science and Technology,2010(3):50-55.]
[5]Bush V.Science,the endless frontier:A report to the President[M].Washington:US Governmen Print Office,1945.
[6]孙早,许薛璐.前沿技术差距与科学研究的创新效应--基础研究与应用研究谁扮演了更重要的角色[J].中国工业经济,2017(3):5-23.[Sun Zao,Xu Xuelu.Technology distance to frontier and the innovative effect of scientific research--Which one plays more important role,basic research or applied research.Chinese Industrial Economy,2017(3):5-23.]
[7]肖文,林高榜.政府支持、研发管理与技术创新效率--基于中国工业行业的实证分析[J].管理世界,2014(4):71-80.[Xiao Wen,Lin Gaobang.Government support,R&D management and technological innovation efficiency:An empirical analysis based on China's industrial sector.Management World,2014(4):71-80.]
[8]Sampat B N.Patenting and US academic research in the 20th century:The world before and after Bayh-Dole[J].Research Policy,2006,35(6):772-789.
[9]Dushnitsky G,Lenox M J.When do incumbents learn from entrepreneurial ventures?:Corporate venture capital and investing firm innovation rates[J].Research Policy,2005,34(5):615-639.
[10]张学勇,张叶青.风险投资、创新能力与公司IPO的市场表现[J].经济研究,2016,51(10):112-125.[Zhang Xueyong,Zhang Yeqing.Venture capital capability and post-IPO performance.Economic Research,2016,51(10):112-125.]
[11]Drucker P.Innovation and entrepreneurship[M].London:Routledge,2014.
[12]Schumpeter J A.Socialism,capitalism and democracy[M].New York:Harper and Brothers,1942.
[13]Arrow K.Economic welfare and the allocation of resources for invention[M]//The rate and direction of inventive activity:Economic and social factors.Princeton:Princeton University Press,1962:609-626.
[14]Guan J C,Yam R C M.Effects of government financial incentives on firms’innovation performance in China:Evidences from Beijing in the 1990s[J].Research Policy,2015,44(1):273-282.
[15]杜志威,吕拉昌,黄茹.中国地级以上城市工业创新效率空间格局研究[J].地理科学,2016,36(3):321-327.[Du Zhiwei,Lyu Lachang,Huang Ru.Spatial pattern of industrial innovation efficiency for Chinese cities at prefecture level and above.Scientia Geographica Sinica,2016,36(3):321-327.]
[16]谭俊涛,张平宇,李静.中国区域创新绩效时空演变特征及其影响因素研究[J].地理科学,2016,36(1):39-46.[Tan Juntao,Zhang Pingyu,Li Jing.Spatio-temporal characteristics of regional innovation performance and its influencing factors in China.Scientia Geographica Sinica,2016,36(1):39-46.]
[17]覃雄合,杜德斌,刘树峰,等.中国省际高校科研成果转化效率时空格局与影响因素--基于网络SBM模型的评价[J].地理研究,2017,36(9):1641-1652.[Qin Xionghe,Du Debin,Liu Shufeng et al.Spatial-temporal pattern and influencing factors in transforming efficiency of scientific research achievements of universities on a provincial scale in China based on the network SBM method.Geographical Research,2017,36(9):1641-1652.]
[18]Hansen M T,Birkinshaw J.The innovation value chain[J].Harvard Business Review,2007,85(6):121.
[19]国家统计局,科学技术部.中国科技统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China,The Ministry of Science and Technology.China statistical yearbook on science and technology.Beijing:China Statistics Press,2007-2015.]
[20]国家统计局.中国统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China.China statistical yearbook.Beijing:China Statistics Press,2007-2015.]
[21]国家统计局.中国城市统计年鉴[M].北京:中国统计出版社,2007-2015.[National Bureau of Statistics of China.China Urban Statistical Yearbook.Beijing:China Statistics Press,2007-2015.]
[22]佟连军,宋亚楠,韩瑞玲,等.辽宁沿海经济带工业环境效率分析[J].地理科学,2012,32(3):294-300.[Tong Lianjun,Song Yanan,Han Ruiling et al.Analysis of industrial environmental efficiency of Liaoning coastal economic belt.Scientia Geographica Sinica,2012,32(3):294-300.]
[23]余泳泽,刘大勇.我国区域创新效率的空间外溢效应与价值链外溢效应--创新价值链视角下的多维空间面板模型研究[J].管理世界,2013(7):6-20.[Yu Yongze,Liu Dayong.The effect of the space outflow of China's regional innovation and the effect of the outflow of value chains:A study,from the perspective of the innovative value chain on the model of the panel of multidimensional space.Management World,2013(7):6-20.]
[24]Guan J,Chen K.Measuring the innovation production process:A cross-region empirical study of China’s high-tech innovations[J].Technovation,2010,30(5):348-358.
[25]Tone K,Tsutsui M.Network DEA:A slacks-based measure approach[J].European Journal of Operational Research,2009,197(1):243-252.
[26]孙才志,李欣.基于核密度估计的中国海洋经济发展动态演变[J].经济地理,2015,35(1):96-103.[Sun Caizhi,Li Xin.Dynamic evolution analysis of China's marine economy development based on kernel density estimation.Economic Geography,2015,35(1):96-103.]
[27]程钰,任建兰,陈延斌,等.中国环境规制效率空间格局动态演变及其驱动机制[J].地理研究,2016,35(1):123-136.[Cheng Yu,Ren Jianlan,Chen Yanbin et al.Spatial evolution and driving mechanism of China's environmental regulation efficiency.Geographical Research,2016,35(1):123-136.]
[28]陈耀.新一轮东北振兴战略要思考的几个关键问题[J].经济纵横,2017(1):8-12.[Chen Yao.Several key issues about the strategy of a new round of revitalization.Economic Review,2017(1):8-12.]
[29]金凤君,王姣娥,杨宇,等.东北地区创新发展的突破路径与对策研究[J].地理科学,2016,36(9):1285-1292.[Jin Fengjun,Wang Jiaoe,Yang Yu et al.The paths and solutions of innovation development in Northeast China.Scientia Geographica Sinica,2016,36(9):1285-1292.]
[30]Florida R.The rise of the creative class--Revisited:Revised and expanded[M].New York:Basic Books(AZ),2014.
[31]王小鲁,樊纲,余静文.中国分省份市场化指数报告(2016)[D].北京:社会科学文献出版社,2016.[Wang Xiaolu,Fan Gang,Yu Jingwen.Report on marketization index of provinces in China(2016).Beijing:Social Sciences Academic Press,2016]
[32]郭迎锋,顾炜宇,乌天玥,等.政府资助对企业R&D投入的影响--来自我国大中型工业企业的证据[J].中国软科学,2016(3):162-174.[Guo Yingfeng,Gu Weiyu,Wu Tianyue et al.The impact of government funding on business R&D expenditure.China Soft Science,2016(3):162-174.]
[33]迈克尔D沃德,克里斯蒂安·格里蒂奇.空间回归模型[M].上海:格致出版社,2016.[Michael D Ward,Kristian Skrede Gleditsch.Spatial regression model.Shanghai:Truth&Wisdom Press,2016.]
(1)东部地区:北京、天津、河北、上海、江苏、浙江、福建、山东、广东和海南10省;中部地区:山西、安徽、江西、河南、湖北和湖南6省;西部地区:内蒙古、广西、重庆、四川、贵州、云南、西藏、陕西、甘肃、青海、宁夏和新疆12省(区、市);东北地区:辽宁、吉林、黑龙江3省。