长江经济创新驱动带的空间关联网络结构及效应分析——以国家高新区为例
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摘要
本文以国家高新区为创新发展依托,利用熵值法测度了2011—2015年长江经济创新驱动带29个高新区的综合创新能力,并将其作为创新"质量"应用于引力模型构建出空间关联矩阵。在此基础上,分别运用社会网络分析法和固定效应模型对创新网络结构及效应进行了考察。研究发现:①高新区样本的创新能力普遍较低,且呈现出"东高西低"的空间分布格局和稳步提升的时间演变趋势。②高新区之间创新动能的溢出效应明显,网络的稳定性缓慢减弱,创新关联程度具有较大提升空间。③长江经济创新驱动带呈现出显著的"核心-边缘"分布,长江下游地区的高新区成员处于网络的核心位置。④长江经济创新驱动带可划分为长三角、长三角附近、长江中游和长江上游四个创新板块,且第二板块向第一板块的溢出效应最为显著。⑤高新区成员在网络中地位的提升对自身综合创新能力的发展具有显著正向影响。
This paper took the national high-tech zone as the base of the innovation development,and used the entropy method to measure the comprehensive innovation ability of 29 high-tech zones in Yangtze River economic innovation drive belt in the year of 2011—2015,and then applied it as the innovation"quality" to gravitational model to construct the spatial correlation matrix. On this basis,the paper studied the structure and effect of innovation network by using social network analysis method and fixed effect model respectively. The results show that: ①The innovation capability of the high-tech zones is generally low,and presents a spatial distribution pattern of "high east and low west"with a steady temporal evolution trend. ②The spillover effect of innovation kinetic energy between high-tech zones is obvious; the stability of the network is slowly weakening,and the degree of innovation correlation has more room for improvement. ③The Yangtze River economic innovation drive belt presents a significant"core-periphery" distribution,and the hightech zone members in the lower reaches of the Yangtze River are at the core of the network. ④The Yangtze River economic innovation drive belt can be divided into four innovative blocks: Yangtze River Delta,the vicinity of the Yangtze River Delta,the middle reaches of the Yangtze River and the upper reaches of the Yangtze River. The spillover effect of the second block to the first block is most significant. ⑤The improvement of the status of high-tech zone members in the network has a significant positive impact on the development of their own comprehensive innovation capabilities.
This paper took the national high-tech zone as the base of the innovation development,and used the entropy method to measure the comprehensive innovation ability of 29 high-tech zones in Yangtze River economic innovation drive belt in the year of 2011—2015,and then applied it as the innovation"quality" to gravitational model to construct the spatial correlation matrix. On this basis,the paper studied the structure and effect of innovation network by using social network analysis method and fixed effect model respectively. The results show that: ①The innovation capability of the high-tech zones is generally low,and presents a spatial distribution pattern of "high east and low west"with a steady temporal evolution trend. ②The spillover effect of innovation kinetic energy between high-tech zones is obvious; the stability of the network is slowly weakening,and the degree of innovation correlation has more room for improvement. ③The Yangtze River economic innovation drive belt presents a significant"core-periphery" distribution,and the hightech zone members in the lower reaches of the Yangtze River are at the core of the network. ④The Yangtze River economic innovation drive belt can be divided into four innovative blocks: Yangtze River Delta,the vicinity of the Yangtze River Delta,the middle reaches of the Yangtze River and the upper reaches of the Yangtze River. The spillover effect of the second block to the first block is most significant. ⑤The improvement of the status of high-tech zone members in the network has a significant positive impact on the development of their own comprehensive innovation capabilities.
引文
[1]胡艳,时浩楠.长三角城市群城市创新的空间关联分析——基于社会网络分析方法[J].上海经济研究,2017(4):87-97.
[2]宓泽锋,曾刚.创新松散型产业的创新网络特征及其对创新绩效的影响研究——以长江经济带物流产业为例[J].地理研究,2017,36(9):1653-1666.
[3]段德忠,杜德斌,刘承良.上海和北京城市创新空间结构的时空演化模式[J].地理学报,2015,70(12):1911-1925.
[4]KRUGMAN P. Increasing returns and economic geography[J].Journal of political economy,1990,99(3):483-499.
[5]KELLER W. Geographic localization of international technology diffusion[J].American economic review,2002,92(1):120-142.
[6]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.
[7]白俊红,蒋伏心.协同创新、空间关联与区域创新绩效[J].经济研究,2015(7):174-187.
[8]李晓娣,陈家婷. FDI对区域创新系统演化的驱动路径研究——基于结构方程模型的分析[J].科学学与科学技术管理,2014(8):39-48.
[9]周灿,曾刚,曹贤忠.中国城市创新网络结构与创新能力研究[J].地理研究,2017,36(7):1297-1308.
[10]LIEFNER I,HENNEMANN S. Structural holes and new dimensions of distance:the spatial configuration of the scientific knowledge network of China's Optical Technology Sector[J].Environment&planning A,2011,43(4):810-829.
[11]WANZENB Ck I,SCHERNGELL T,BRENNER T. What determines the position of regions in European knowledge networks? A comparative perspective on R&D collaboration,co-patent and co-publication networks[J]. Annals of regional science,2013,53(2):337-368.
[12]吕国庆,曾刚,顾娜娜.基于地理邻近与社会邻近的创新网络动态演化分析——以我国装备制造业为例[J].中国软科学,2014(5):97-106.
[13]李敬,陈澍,万广华,等.中国区域经济增长的空间关联及其解释——基于网络分析方法[J].经济研究,2014(11):4-16.
[14]于洪雁,李秋雨,梅林,等.社会网络视角下黑龙江省城市旅游经济联系的空间结构和空间发展模式研究[J].地理科学,2015,35(11):1429-1436.
[15]WHITE H C,BOORMAN S A,BREIGER R L. Social structure from multiple networks I blockmodels of roles and positions[J].American journal of sociology,1976,81(4):730-780.
[16]刘华军,刘传明,孙亚男.中国能源消费的空间关联网络结构特征及其效应研究[J].中国工业经济,2015(5):83-95.
[17]WASSERMAN S,FAUST K. Social network analysis:methods and applications.[J]. Contemporary sociology,1995,91(435):219-220.
[18]白俊红,卞元超.政府支持是否促进了产学研协同创新[J].统计研究,2015,32(11):43-50.
[19]姬广林.中国金融发展对技术创新影响的实证分析[D].长春:吉林大学,2017.
[20]钱晓烨,迟巍,黎波.人力资本对我国区域创新及经济增长的影响——基于空间计量的实证研究[J].数量经济技术经济研究,2010(4):107-121.
[2]宓泽锋,曾刚.创新松散型产业的创新网络特征及其对创新绩效的影响研究——以长江经济带物流产业为例[J].地理研究,2017,36(9):1653-1666.
[3]段德忠,杜德斌,刘承良.上海和北京城市创新空间结构的时空演化模式[J].地理学报,2015,70(12):1911-1925.
[4]KRUGMAN P. Increasing returns and economic geography[J].Journal of political economy,1990,99(3):483-499.
[5]KELLER W. Geographic localization of international technology diffusion[J].American economic review,2002,92(1):120-142.
[6]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.
[7]白俊红,蒋伏心.协同创新、空间关联与区域创新绩效[J].经济研究,2015(7):174-187.
[8]李晓娣,陈家婷. FDI对区域创新系统演化的驱动路径研究——基于结构方程模型的分析[J].科学学与科学技术管理,2014(8):39-48.
[9]周灿,曾刚,曹贤忠.中国城市创新网络结构与创新能力研究[J].地理研究,2017,36(7):1297-1308.
[10]LIEFNER I,HENNEMANN S. Structural holes and new dimensions of distance:the spatial configuration of the scientific knowledge network of China's Optical Technology Sector[J].Environment&planning A,2011,43(4):810-829.
[11]WANZENB Ck I,SCHERNGELL T,BRENNER T. What determines the position of regions in European knowledge networks? A comparative perspective on R&D collaboration,co-patent and co-publication networks[J]. Annals of regional science,2013,53(2):337-368.
[12]吕国庆,曾刚,顾娜娜.基于地理邻近与社会邻近的创新网络动态演化分析——以我国装备制造业为例[J].中国软科学,2014(5):97-106.
[13]李敬,陈澍,万广华,等.中国区域经济增长的空间关联及其解释——基于网络分析方法[J].经济研究,2014(11):4-16.
[14]于洪雁,李秋雨,梅林,等.社会网络视角下黑龙江省城市旅游经济联系的空间结构和空间发展模式研究[J].地理科学,2015,35(11):1429-1436.
[15]WHITE H C,BOORMAN S A,BREIGER R L. Social structure from multiple networks I blockmodels of roles and positions[J].American journal of sociology,1976,81(4):730-780.
[16]刘华军,刘传明,孙亚男.中国能源消费的空间关联网络结构特征及其效应研究[J].中国工业经济,2015(5):83-95.
[17]WASSERMAN S,FAUST K. Social network analysis:methods and applications.[J]. Contemporary sociology,1995,91(435):219-220.
[18]白俊红,卞元超.政府支持是否促进了产学研协同创新[J].统计研究,2015,32(11):43-50.
[19]姬广林.中国金融发展对技术创新影响的实证分析[D].长春:吉林大学,2017.
[20]钱晓烨,迟巍,黎波.人力资本对我国区域创新及经济增长的影响——基于空间计量的实证研究[J].数量经济技术经济研究,2010(4):107-121.