中国高技术产业创新绩效空间分布特征研究——基于两阶段创新视角的分析
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摘要
基于两阶段价值链视角,运用数据包络分析模型和探索性空间数据分析方法对中国31个省区市高技术产业的技术研发绩效与成果转化绩效状况及其空间分布特征进行量化研究。研究发现:中国高技术产业研发阶段绩效整体低于成果转化阶段绩效。原创性产出不足,核心技术缺乏,部分地区仍存在研发人员和研发资金配置不合理,创新效率偏低;而成果转化阶段则存在科研成果不能有效地转化为实际生产力,导致竞争性产出不足。其次,31个省区市高技术产业两阶段创新绩效空间分布特征不同。在研发阶段仅有北京、上海和广东三个地区的创新绩效达到或接近生产前沿面,其他地区绩效偏低,两级分化严重,在空间上呈随机分布模式;而成果转化阶段则有11个地区达到或接近生产前沿面,根据全局空间相关性分析显示,存在空间集聚模式。局部空间相关性及热点分析揭示,东中部地区绩效高值集聚显著,而西部地区和东北地区局部低值集聚显著,且南部地区的创新绩效高于北部地区。
Based on the two-stage value chain perspective,the model of date envelope analysis and the exploratory spatial data analysis method are taken to study the performances of the technology R&D and the achievement transformation,and the spatial distribution characteristics of high-tech industry in 31 regions of China are quantifiably studied as well. The findings show that the performance of R&D stage is lower than that of the achievements transformation stage. The improper distribution of the R&D personnel and the R&D funds are major causes of the insufficiency of the original output and the core technology in some areas,thus the innovation efficiency is comparatively at a low level; and the insufficiency of the competitive output is due to the inadequacy of efficiency in scientific research achievement transformation. Moreover,the spatial distribution characteristics of the two-stage innovation efficiency of China's 31 regions are different. At the R&D stage,only Beijing,Shanghai and Guangdong,the three regions' innovation performance has reached or closed to the production frontiers,and the other regions' performance is low in efficiency. In addition,the polarization of the R&D efficiency is serious,and there is a random distribution pattern in the space; while there are 11 regions which have reached or closed to the production frontiers at the stage of achievement transformation. According to the global spatial correlation analysis,the efficiency of achievement transformation presents space agglomeration distribution characteristics. The local spatial correlation and the hot spot analysis reveals that the concentration of high efficiency is significant in the eastern and central regions,while the low efficiency shows significantly agglomeration characteristics in part of western and northeastern regions,and the innovation efficiency of southern region is higher than that of the northern region.
Based on the two-stage value chain perspective,the model of date envelope analysis and the exploratory spatial data analysis method are taken to study the performances of the technology R&D and the achievement transformation,and the spatial distribution characteristics of high-tech industry in 31 regions of China are quantifiably studied as well. The findings show that the performance of R&D stage is lower than that of the achievements transformation stage. The improper distribution of the R&D personnel and the R&D funds are major causes of the insufficiency of the original output and the core technology in some areas,thus the innovation efficiency is comparatively at a low level; and the insufficiency of the competitive output is due to the inadequacy of efficiency in scientific research achievement transformation. Moreover,the spatial distribution characteristics of the two-stage innovation efficiency of China's 31 regions are different. At the R&D stage,only Beijing,Shanghai and Guangdong,the three regions' innovation performance has reached or closed to the production frontiers,and the other regions' performance is low in efficiency. In addition,the polarization of the R&D efficiency is serious,and there is a random distribution pattern in the space; while there are 11 regions which have reached or closed to the production frontiers at the stage of achievement transformation. According to the global spatial correlation analysis,the efficiency of achievement transformation presents space agglomeration distribution characteristics. The local spatial correlation and the hot spot analysis reveals that the concentration of high efficiency is significant in the eastern and central regions,while the low efficiency shows significantly agglomeration characteristics in part of western and northeastern regions,and the innovation efficiency of southern region is higher than that of the northern region.
引文
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[2]董艳梅,朱英明.中国高技术产业创新效率评价——基于两阶段动态网络DEA模型[J].科技进步与对策,2015,9(24):106-113.
[3]郑坚,丁云龙.高技术产业技术创新效率评价指标体系的构建[J].哈尔滨工业大学学报,2007,9(6):105-108.
[4] Feng F,Wang B,Zou Y,et al. A New Internet DEA Structure:Measurement of Chinese R&D Innovation Efficiency in High Technology Industry[J]. International Journal of Business&Management,2013,8(21):32-40.
[5]国家统计局社科文司"中国创新指数研究"课题组,贾楠,李胤.中国创新指数研究[J].统计研究,2014,31(11):24-28.
[6]许霞.高技术产业创新效率省际差异与空间收敛检验——基于两阶段DEA的实证分析[J].北京邮电大学学报(社会科学版),2016,18(1):78-86.
[7] Fare R,Grosskopf S. Productivity and intermediate products:a frontier approach[J]. Economics Letters,2006,12(50):65-70.
[8] Kao C,Wang S N. Efficiency decomposition in two-stage data envelopment analysis:application on-life insurance companies in Taiwan[J]. European Journal of Operation Researches,2008,10(6):418-429.
[9] Tone K,Tsutsui M. Dynamic DEA:A slacks-based measure approach[J]. Omega,2010,38(3-4):145-156.
[10]王远飞,何洪林.空间数据分析方法[M].北京:科学出版社,2007.
[11] Moran P A P. Notes on Continuous Stochastic Phenomena[J]. Biometrika,1950,37(1/2):17-23.
[12] Geary R C. The Contiguity Ratio and Statistical Mapping[J]. The Incorporated Statistician,1954,5(3):115-146.
[13]王守坤.空间计量模型中权重矩阵的类型与选择[J].经济数学,2013,30(3):57-63.
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