煤炭资源聚集区省际科技协同创新绩效研究——基于中心-腹地模式
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摘要
基于中心-腹地模式观,运用数据包络分析(DEA)法测算由晋陕豫冀蒙组成的煤炭资源聚集区内地区间科技协同创新绩效水平。研究结果表明:晋豫、晋冀、晋蒙科技协同创新绩效相对不理想;晋陕科技协同创新绩效较高、协同投入与产出比相对良好,分别集聚了省内主要科技资源的太原市和西安市在形成中心-腹地模式的科技协同创新关系方面潜力较大。鉴于将来有较大可能形成科技资源以西安市为中心向山西省境内城市辐射的局面,提出山西省应主动承接陕西省科技辐射等对策建议。
Based on the concept of central-hinterland model, this paper uses data envelopment analysis(DEA) method to calculate the performance level of sci-tech collaborative innovation in the coal resource agglomeration area of Shanxi, Shaanxi, Henan, Hebei and Mongolia. The results show that: the performances of sci-tech collaborative innovation between Shanxi-Henan, Shanxi-Hebei, and Shanxi-Mongolia are relatively unsatisfactory; ShanxiShaanxi sci-tech collaborative innovation has a higher performance and a relatively good collaborative input-output ratio,Taiyuan and Xi'an, which have gathered major scientific and technological resources in the province respectively,have great potential in forming a central-hinterland model of scientific and technological collaborative innovation. In view of the situation that science and technology resources are likely to radiate to cities in Shanxi province with Xi'an as the center in the future, the paper puts forward some countermeasures and suggestions, for example, Shanxi should take the initiative to undertake the scientific and technological radiation in Shaanxi.
Based on the concept of central-hinterland model, this paper uses data envelopment analysis(DEA) method to calculate the performance level of sci-tech collaborative innovation in the coal resource agglomeration area of Shanxi, Shaanxi, Henan, Hebei and Mongolia. The results show that: the performances of sci-tech collaborative innovation between Shanxi-Henan, Shanxi-Hebei, and Shanxi-Mongolia are relatively unsatisfactory; ShanxiShaanxi sci-tech collaborative innovation has a higher performance and a relatively good collaborative input-output ratio,Taiyuan and Xi'an, which have gathered major scientific and technological resources in the province respectively,have great potential in forming a central-hinterland model of scientific and technological collaborative innovation. In view of the situation that science and technology resources are likely to radiate to cities in Shanxi province with Xi'an as the center in the future, the paper puts forward some countermeasures and suggestions, for example, Shanxi should take the initiative to undertake the scientific and technological radiation in Shaanxi.
引文
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[23]王仁文,宋伟.省际高校科技创新协同度研究[J].中国高校科技,2013(11):32-35.
[24]曹志鹏,潘启亮.我国高校间科研创新合作现状: 基于2014年合著论文的社会网络分析[J].科技管理研究,2017,37(1):93-98.
[25]毕娟.京津冀科技协同创新影响因素研究[J].科技进步与对策,2016,33(8):49-54.
[26]刘凤朝,马荣康.区域间技术转移的网络结构及空间分布特征研究: 基于我国2006—2010省际技术市场成交合同的分析[J].科学学研究,2013,31(4):529-536.
[27]王聪,朱先奇,刘玎琳,等.京津冀协同发展中科技资源配置效率研究: 基于超效率DEA-面板Tobit两阶段法[J].科技进步与对策,2017,34(19):47-52.
[2]杨凡,杜德斌,林晓.中国省域创新产出的空间格局与空间溢出效应研究[J].软科学,2016,30(10):6-10.
[3]胡谦尊.米尔顿·弗里德曼[J].世界经济,1979(6):76-78.
[4]李小建,李庆春.克鲁德曼的主要经济地理学观点分析[J].地理科学进展,1999,18(2):97-102.
[5]赵渺希,唐子来.基于网络关联的长三角区域腹地划分[J].经济地理, 2010,30(3):371-376.
[6]汪鑫,罗震东,朱查松,等.中心与腹地的辩证:基于企业联系的苏州、宁波区域空间关系比较研究[J].城市规划学刊, 2014(5):79-85.
[7]张同斌,李金凯,周浩.高技术产业区域知识溢出、协同创新与全要素生产率增长[J].财贸研究,2016,27(1):9-18.
[8]ZABALA-ITURRIAGAGOITLA J M, GUTIERREZ-GRACIA V PA,SAEZ F J.Regional innovation systems :how to assess performance[J].Regional Studies, 2007(5):661-672.
[9]FAN D C,TANG X X.Performance evaluation of industry-universityresearch cooperative technological innovation based on fuzzy integral[C]//IEEE.International Conference on Management Science & Engineering.Moscow:Management Science and Engineering,2009:1789-1795.
[10]李林,刘志华,王雨婧.区域科技协同创新绩效评价[J].系统管理学报,2015,24(4):563-568.
[11]SRIDHARAN R,SIMATUPANG T M.The collaboration index: a measure for supply chain collaboration[J].International Journal of Physical Distribution & Logistics Management, 2005,35(1):44-62.
[12]谢思全,鹿媛媛,李叶妍.科技协同创新绩效评价指标体系初探[J].现代管理科学,2014(1):18-20.
[13]郭斌.京津冀科技协同创新绩效体系重构: 基于文献编码的复杂网络分析[J].中央财经大学学报,2016(6):87-96.
[14]BHAGWAT R,SHARMA M K.Performance measurement of supply chain management using the analytical hierarchy process[J].Production Planning & Control,2007,18(8):666-680.
[15]PINTO H,GUERREIRO J.Innovation regional planning and latent dimensions: the case of the Algarve region[J].The Annals of Regional Science, 2010(2):315-329.
[16]冯锋,汪良兵.协同创新视角下的区域科技政策绩效提升研究: 基于泛长三角区域的实证分析[J].科学学与科学技术管理,2011,32(12):109-115.
[17]姜彤彤.省域范围内产学研协同创新效率评价及分析[J].学术论坛,2015,38(3):168-172.
[18]张志新,孙照吉,薛翘.黄河三角洲区域科技创新能力综合分析与评价研究[J].经济问题,2014(4):100-105.
[19]PHILBIN S.Process model for university-industry research collaboration [J].European Journal of Innovation Management, 2008,11(4):488-521.
[20]刘志华,李林,姜郁文.我国区域科技协同创新绩效评价模型及实证研究[J].管理学报,2014,11(6):861-868.
[21]武玉英,魏国丹,何喜军.京津冀高技术制造业与要素协同度测度及实证研究[J].软科学,2016,30(5):21-25.
[22]冯锋,燕会雷.两系统链视角下科技协同创新效率研究: 基于我国28省市高技术产业的数据分析[J].电子科技大学学报(社科版), 2013,15(5):31-36.
[23]王仁文,宋伟.省际高校科技创新协同度研究[J].中国高校科技,2013(11):32-35.
[24]曹志鹏,潘启亮.我国高校间科研创新合作现状: 基于2014年合著论文的社会网络分析[J].科技管理研究,2017,37(1):93-98.
[25]毕娟.京津冀科技协同创新影响因素研究[J].科技进步与对策,2016,33(8):49-54.
[26]刘凤朝,马荣康.区域间技术转移的网络结构及空间分布特征研究: 基于我国2006—2010省际技术市场成交合同的分析[J].科学学研究,2013,31(4):529-536.
[27]王聪,朱先奇,刘玎琳,等.京津冀协同发展中科技资源配置效率研究: 基于超效率DEA-面板Tobit两阶段法[J].科技进步与对策,2017,34(19):47-52.