创新驱动发展背景下我国区域知识有效供给能力评价研究
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摘要
为客观、准确地评价区域知识有效供给能力,探究知识有效供给能力的影响因素,在总结知识供给、创新驱动发展相关指标基础上,构建了区域知识有效供给能力的评价指标体系。基于耦合模型和TOPSIS法建立区域知识有效供给能力评价模型,对我国区域知识有效供给能力进行评价。研究表明:我国区域知识有效供给能力总体水平处于中等,在地理空间上是不均衡的,呈现一定的东—中—西梯度递减的分布模式,相邻区域的知识有效供给能力基本相近,具有明显的空间集聚特征;互联网资源丰度对我国区域知识有效供给能力的提高起着重要的作用,人均消费水平对其有一定的正向影响,而城市化水平对其产生了负向影响;东部地区应以自主创新为主,中部地区应在以自主创新为主同时,兼顾模仿创新,西部地区以模仿创新为主。评价和实证结果有助于为区域知识有效供给能力提升及区域创新模式选择提供实践借鉴。
In order to objectively and accurately evaluate the effective supply capacity of regional knowledge and explore the influencing factors of the ability of knowledge effective supply,the evaluation index system of effective supply capacity of regional knowledge is constructed on the basis of knowledge supply and innovation driven development related indicators. Based on the coupling model and TOPSIS method,a regional knowledge effective supply capability evaluation model is established to evaluate the effective supply capacity of regional knowledge in China. The research shows that the overall level of effective supply capacity of regional knowledge is in the middle,and it is uneven in geographical space,and presents a certain distribution pattern of East to Middle West gradient. The ability of effective supply of knowledge in adjacent areas is almost similar,and has obvious spatial agglomeration characteristics. The improvement of the ability of effective supply of domain knowledge plays an important role,and the level of per capita consumption has a positive impact on it,and the level of urbanization has a negative impact on it; the eastern region should be based on independent innovation,and the central region should be based on independent innovation at the same time,as well as model imitation,and the western region imitates innovation. The evaluation and empirical results will help to provide a practical reference for the enhancement of regional knowledge effective supply capability and the choice of regional innovation mode.
In order to objectively and accurately evaluate the effective supply capacity of regional knowledge and explore the influencing factors of the ability of knowledge effective supply,the evaluation index system of effective supply capacity of regional knowledge is constructed on the basis of knowledge supply and innovation driven development related indicators. Based on the coupling model and TOPSIS method,a regional knowledge effective supply capability evaluation model is established to evaluate the effective supply capacity of regional knowledge in China. The research shows that the overall level of effective supply capacity of regional knowledge is in the middle,and it is uneven in geographical space,and presents a certain distribution pattern of East to Middle West gradient. The ability of effective supply of knowledge in adjacent areas is almost similar,and has obvious spatial agglomeration characteristics. The improvement of the ability of effective supply of domain knowledge plays an important role,and the level of per capita consumption has a positive impact on it,and the level of urbanization has a negative impact on it; the eastern region should be based on independent innovation,and the central region should be based on independent innovation at the same time,as well as model imitation,and the western region imitates innovation. The evaluation and empirical results will help to provide a practical reference for the enhancement of regional knowledge effective supply capability and the choice of regional innovation mode.
引文
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[26]Anguelov R,Stoltz S M. Stationary and oscillatory patterns in a coupled Brusselator model[J]. Mathematics&Computers in Simulation,2017(133):39-46.
[27]Liu Q,Wang S,Zhang W,et al. China's Municipal Public Infrastructure:Estimating Construction Levels and Investment Efficiency Using the Entropy Method and a DEA Model[J]. Habitat International,2017(64):59-70.
[28]朱建新,祝佳伟,朱祎宏.基于Entropy-Topsis的中国制造业企业创新环境评价[J].哈尔滨工程大学学报,2017(5):808-814.
[29]吕先志,王瑞丹.科技基础条件资源丰度指数研究[J].中国科技论坛,2013(8):15-19.
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[2]Becheikh N,Landry R,Amara N. Lessons from Innovation Empirical Studies in the Manufacturing Sector:A Systematic Review of the Literature From 1993-2003[J]. Technovation,2006(5-6):644-664.
[3]Ramzi T,Salah A B. The Determinants of Innovation Capacity in the Less Innovative Countries in the Euro-Mediterranean Region[J]. Journal of the Knowledge Economy,2015(23):1-18.
[4]Solow R M. Technical Change and the Aggregate Production Function[J]. Review of Economics&Statistics,1957(3):554-562.
[5]Porter ME. The Competitive Advantage of Nations[J]. Harvard Business Review,1990(2):73-93.
[6]OECD. New Sources of Growth:Knowledge-Based Capital[M]. Washington,USA:OECD Publishing,2013.
[7]Bergsman J,Greenston P,Healy R. A Classification of Economic Activities Based on Location Patterns[J]. Journal of Urban Economics,1975(1):1-28.
[8]Wang S,Fan J,Zhao D,et al. Regional Innovation Environment and Innovation Efficiency:the Chinese Case[J]. Technology Analysis&Strategic Management,2016(4):396-410.
[9]Furman J L,Hayes R. Catching up or Standing Still:National Innovative Productivity Among‘Follower’Countries,1978-1999[J]. Research Policy,2004(9):1329-1354.
[10]Furman J L, Macgarvie M. Academic Collaboration and Organizational Innovation:The Development of Research Capabilities in the US Pharmaceutical Industry,[J]. Industrial and Corporate Change,2009(5):929-961.
[11]Corrado C A,Haskel J,Jona-Lasinio C,et al. Intangible Capital and Growth in Advanced Economies:Measurement Methods and Comparative Results[J]. Social Science Electronic Publishing,2012(3):225.
[12]Vitola A,Senfelde M. Evaluation of Institutions in Innovation-Driven Economies[J]. Economic Science for Rural Development,2015(8):94-103.
[13]程郁,陈雪.创新驱动的经济增长——高新区全要素生产率增长的分解[J].中国软科学,2013(11):26-39.
[14]万君康,凌丹,邹蔚.论技术有效供给[J].科学学与科学技术管理,2006(12):11-14.
[15]于涛.中国37个工业行业技术供给能力的差异及原因[D].大连:大连理工大学,2008.
[16]张海笔.供需视角下技术选择的动态均衡分析[J].中国科技论坛,2013(11):151-154.
[17]贺正楚等.生物医药产业共性技术服务效率研究[J].中国软科学,2014(2):130-139.
[18]朱建民,金祖晨.国外关键共性技术供给体系发展的做法及启示[J].经济纵横,2016(7):113-117.
[19]尹士,李柏洲.中国区域技术有效供给能力评价及影响因素[J].中国科技论坛,2018(4):128-137.
[20]梁正.从科技政策到科技与创新政策——创新驱动发展战略下的政策范式转型与思考[J].科学学研究,2017(2):170-176.
[21]吴海建,韩嵩,周丽等.创新驱动发展评价指标体系设计及实证研究[J].中国统计,2015(2):53-54.
[22]周柯,唐娟莉.我国省际创新驱动发展能力测度及影响因素分析[J].经济管理,2016(7):24-34.
[23]霍国庆,杨阳,张古鹏.新常态背景下中国区域创新驱动发展理论模型的构建研究[J].科学学与科学技术管理,2017(6):77-93.
[24]Paul Benneworth,Rómulo Pinheiro,James Karlsen. Strategic Agency and Onstitutional Change:Investigating the Role of Universities in Regional Innovation Systems(RISs)[J]. Regional Studies,2017(2):1-14.
[25]卓丽洪,贺俊.产业集群共性技术供给机制的比较分析[J].经济纵横,2017(7):60-68.
[26]Anguelov R,Stoltz S M. Stationary and oscillatory patterns in a coupled Brusselator model[J]. Mathematics&Computers in Simulation,2017(133):39-46.
[27]Liu Q,Wang S,Zhang W,et al. China's Municipal Public Infrastructure:Estimating Construction Levels and Investment Efficiency Using the Entropy Method and a DEA Model[J]. Habitat International,2017(64):59-70.
[28]朱建新,祝佳伟,朱祎宏.基于Entropy-Topsis的中国制造业企业创新环境评价[J].哈尔滨工程大学学报,2017(5):808-814.
[29]吕先志,王瑞丹.科技基础条件资源丰度指数研究[J].中国科技论坛,2013(8):15-19.
[30]余泳泽,张先轸.要素禀赋、适宜性创新模式选择与全要素生产率提升[J].管理世界,2015(9):13-31.