中国战略性新兴产业企业投入产出效率测度研究——基于2008～2016年环渤海、长三角和珠三角30家上市企业的样本数据
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摘要
随着经济的发展,战略性新兴产业已成为我国经济发展的重要力量,也是世界各国产业竞争的聚焦点。文章基于规模报酬可变的数据包络分析(DEA)方法,对我国环渤海、长三角和珠三角地区30家战略性新兴产业企业投入产出效率进行了测算,并依据美国贸易打击清单的战略性新兴产业企业为例进行剖析。研究结果表明:三大区域企业投入产出效率有显著性差异,环渤海地区效率波动起伏较大,效率值总体低于长三角和珠三角地区;三大区域企业投入产出效率在最优生产前沿面上的企业仅有11家,仅为选取样本企业的1/3,说明大部分样本企业要么是纯技术无效率,要么是规模无效率,即企业规模不经济导致的,但三大区域企业投入产出效率仍有上升的空间。针对实证研究结果,从产业创新驱动、技术联盟和政策扶持等方面提出了相应的政策启示,旨在对中国整体战略性新兴产业企业投入产出效率的提升提供重要的参考。
With the development of economy,strategic emerging industries have become the core competitiveness of China's economic development and the main focus of industrial competition in the world.Based on the sample data of 30 strategic emerging industry companies in Circum-BohaiSea Region,Yangtze River Delta and the Pearl River Delta Region from 2008-2016,this paper calculates the input and output efficiency through Data Envelopment Analysis(DEA).The emerging industry enterprises that are in the U.S.trade hit list are analyzed as well.The results show that:There are significant differences in the input and output efficiency of the three regions.The efficacy of the companies in Circum-Bohai-Sea Region fluctuates obviously and is lower than the companies in the other two regions.There are only 11 enterprises on the forefront of the optimal production of output efficiency in the three regions,which is only one third of the sample enterprises selected.This indicates that most sample en-terprises are either technologically great but inefficient or inefficient with great size.There are great increasing space for enterprises in the three regions.This paper puts forward some policy enlightenments from the aspects of industrial innovation drive,technology alliance,policy support and so on.It aims to supply important reference for the improvement of input-output efficiency of strategic emerging industries in various regions in China.
With the development of economy,strategic emerging industries have become the core competitiveness of China's economic development and the main focus of industrial competition in the world.Based on the sample data of 30 strategic emerging industry companies in Circum-BohaiSea Region,Yangtze River Delta and the Pearl River Delta Region from 2008-2016,this paper calculates the input and output efficiency through Data Envelopment Analysis(DEA).The emerging industry enterprises that are in the U.S.trade hit list are analyzed as well.The results show that:There are significant differences in the input and output efficiency of the three regions.The efficacy of the companies in Circum-Bohai-Sea Region fluctuates obviously and is lower than the companies in the other two regions.There are only 11 enterprises on the forefront of the optimal production of output efficiency in the three regions,which is only one third of the sample enterprises selected.This indicates that most sample en-terprises are either technologically great but inefficient or inefficient with great size.There are great increasing space for enterprises in the three regions.This paper puts forward some policy enlightenments from the aspects of industrial innovation drive,technology alliance,policy support and so on.It aims to supply important reference for the improvement of input-output efficiency of strategic emerging industries in various regions in China.
引文
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[4]李晓梅,白雪飞.基于超效率CCR-DEA的国有物流企业绩效实证分析---基于16家上市物流企业的样本数据[J].中国流通经济,2016,30(4):26-32.
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[9]邸晓燕.新兴产业形成中的产业技术创新战略联盟标准:概念内涵与现实需求[J].科学管理研究,2017,35(2):54-57.
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[11]刘志迎,张吉坤.高技术产业不同资本类型企业创新效率分析---基于三阶段DEA模型[J].研究与发展管理,2013(3):45-52.
[12]黄海霞,张治河.中国战略性新兴产业的技术创新效率---基于DEA-Malmquist指数模型[J].技术经济,2015,34(1):21-27,68.
[13]邬龙,张永安.基于SFA的区域战略性新兴产业创新效率分析---以北京医药和信息技术产业为例[J].科学学与科学技术管理,2013,34(10):95-102.
[14]熊婵,买忆媛,何晓斌,肖仁桥.基于DEA方法的中国高科技创业企业运营效率研究[J].管理科学,2014(2):26-37.
[15]CHARNES A,COOPER W W,RHODES E.Measuring the efficiency of efficiency of decision making units[J].European Journal of Operational Research,1978,2:429-444.
[16]COELLI,T.A Guide to DEAP Version 2.1:A Data Enveloopment Analysis(Computer)Program[Z].CEPA Working Paper,1996:139-151.
[2]姚潇颖,卫平,李健.产学研合作模式及其影响因素的异质性研究---基于中国战略新兴产业的微观调查数据[J].科研管理,2017,38(8):1-10.
[3]程贵孙,张雍,芮明杰.国有与民营企业发展战略性新兴产业相对效率研究---基于2005-2011年上市公司数据的实证分析[J].当代财经,2013(10):96-105.
[4]李晓梅,白雪飞.基于超效率CCR-DEA的国有物流企业绩效实证分析---基于16家上市物流企业的样本数据[J].中国流通经济,2016,30(4):26-32.
[5]李晓华.我国战略性新兴产业的所有制结构研究[J].当代经济管理,2014,36(1):57-65.
[6]吕岩威,孙慧.中国战略性新兴产业技术效率及其影响因素研究---基于18个大类行业面板数据的分析[J].科学学与科学技术管理,2013,34(11):137-146.
[7]王水莲.战略性新兴产业商业模式创新系统框架[J].中国科技论坛,2017(2):164-170.
[8]刘志阳,孔令丞,梁玲.基于产业生命周期的战略性新兴产业创新获利影响因素分析[J].研究与发展管理,2017,29(1):95-105.
[9]邸晓燕.新兴产业形成中的产业技术创新战略联盟标准:概念内涵与现实需求[J].科学管理研究,2017,35(2):54-57.
[10]张晓涛,贾骏阳.中美制造业振兴战略政策支持体系对比研究[J].科学管理研究,2017,35(1):103-107.
[11]刘志迎,张吉坤.高技术产业不同资本类型企业创新效率分析---基于三阶段DEA模型[J].研究与发展管理,2013(3):45-52.
[12]黄海霞,张治河.中国战略性新兴产业的技术创新效率---基于DEA-Malmquist指数模型[J].技术经济,2015,34(1):21-27,68.
[13]邬龙,张永安.基于SFA的区域战略性新兴产业创新效率分析---以北京医药和信息技术产业为例[J].科学学与科学技术管理,2013,34(10):95-102.
[14]熊婵,买忆媛,何晓斌,肖仁桥.基于DEA方法的中国高科技创业企业运营效率研究[J].管理科学,2014(2):26-37.
[15]CHARNES A,COOPER W W,RHODES E.Measuring the efficiency of efficiency of decision making units[J].European Journal of Operational Research,1978,2:429-444.
[16]COELLI,T.A Guide to DEAP Version 2.1:A Data Enveloopment Analysis(Computer)Program[Z].CEPA Working Paper,1996:139-151.