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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 被引量:2

Study of the Technology Collaborative Innovation and Efficiency from Two-stage Chain Perspective——Based On China's 28 provinces and cities in the data of the high-tech industry
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摘要 链式DEA模型研究科技投入产出两阶段效率时,忽视了阶段投入和成果产出之间的关联度,也没有就两阶段段效率对整体效率的促进作用进行检测,易造成投入因子和产出结果关联耦合度不足。在对各阶段的投入要素和成果产出进行灰色关联度分析的基础上,运用链式DEA模型对我国28个省市高技术产业的两阶段科技投入产出数据进行实证分析。然后借助单因子回归模型检验阶段效率对整体效率的作用。最后根据实证结果把各省市分为效率兼优型等四个类型。并针对性地提出政策建议。 When using the chain DEA model to research the input and output of two-stage efficiency, the correlation between the stage input and output results is ignored, and two-stage segment efficiency role in promoting the overall efficiency of detection is not available, which could easily lead to low correlated coupling of factor inputs and outputs. Based on the grey relational analysis of various stages of input factors and output results, an empirical analysis on input-output data of high-tech industry's two-stage technology in China's 28 provinces is made by using the chain DEA model, and then the affection of the phase efficiency on the overall efficiency is verified by using the single-factor regression model testing. Finally, provinces and cities are divided into four types according to the empirical results, and policy suggestions are put forward.
作者 冯锋 燕会雷
出处 《电子科技大学学报(社科版)》 2013年第5期31-36,共6页 Journal of University of Electronic Science and Technology of China(Social Sciences Edition)
基金 国家自然科学基金"产学研共生"项目资助课题(71073151)
关键词 链式网络DEA 两阶段 高技术产业 效率 灰色关联度 单因子检验 chain network DEA two stages high-tech industry efficiency grey correlation degree single-factor test
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  • 1胡谦尊.米尔顿·弗里德曼[J].世界经济,1979,2(6):76-76. 被引量:1
  • 2Glaister K. W,Buckley P. J. Strategic motives for inter-national alliance formation [ J ] . Journal of ManagementStudies, 1996(33) : 301-332. 被引量:1
  • 3Fare R, Grabowski R,Grosskopf S,et al. Efficiency of afixed but allocatable input: A non-parametric approach [ J].Economics Letters, 1997(56) : 187-193. 被引量:1
  • 4Fare R,Grosskopf S. Network DEA [ J] . Socio-EconomicPlanning Sciences, 2000( 34) : 35-49. 被引量:1
  • 5Zhu J,Cook W D. Modeling data irregularities andstructural complexities in DEA[ M]. Springer,2007. 被引量:1
  • 6DouglasA E. Symbiotic interactions[M]. Oxford:OxfordUniversity Press, 1994. 被引量:1
  • 7Ahmadjian V. Symbiosis an introduction to biologicalassociation[ M]. University Press of New England, 1986. 被引量:1
  • 8Andersen P,Petersen N C. A procedure for rankingefficient units in data envelopment analysis [ J] . ManagementScience, 1993, 39(10) : 1261-1264. 被引量:1
  • 9Lang J R,Golden P. Evaluating the efficiency of SBDCSwith data envelopment analysis: A longitudinal approach[ J].Journal of Small Business Management, 1989(27) : 42-49. 被引量:1
  • 10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. 被引量:62

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