Abstract：The optimal allocation of scientific and technological innovation resources is an important measure to improve the capability for independent innovation,deepen the reform of scientific and technological system,enhance the comprehensive national strength,and promote economic development.It is studied from the perspective of efficient allocation of scientific and technological innovation resources and dynamic evolution of non-homogeneity.First of all,according to the economic development,the thirty-one provinces and cities,which are not including Hong Kong,Macao and Taiwan in China,are divided into three regions.Next,the paper uses six aggregation models of distance measure and cross efficiency to analyze and evaluate the ability of scientific and technological innovation of these 31 provinces and cities in 2014.Then,it applies the improved entropy method to determine the regional optimal weights by which to evaluate interactively between regions.On the basis of the regional optimal weights,comprehensive efficiency evaluation value is obtained as scientific and technological innovation resources allocation.Finally it analyzes the results and makes policy suggestions
范建平,赵园园,吴美琴. 基于改进交叉效率的中国科技创新资源配置研究[J]. 中国科技论坛, 2017(12): 32-40.
Fan Jianping,Zhao Yuanyuan,Wu Meiqin. Chinese Science and Technology Innovation Resources Allocation Based on the Improved Cross-Efficiency Method. , 2017(12): 32-40.
[1]王雪原,王宏起.我国科技创新资源配置效率的DEA分析[J].统计与决策,2008(8):108-110. [2]范斐,杜德斌,李恒.区域科技资源配置效率及比较优势分析[J].科学学研究,2012,30(8):1198-1205. [3]KLINGEBIEL R,RAMMER C.Resource allocation strategy for innovation portfolio management[J].Strategic management journal,2014,35(2):246-268. [4]SCHLAPP J,ORAIOPOULOS N,MAK V.Resource allocation decisions under imperfect evaluation and organizational dynamics[J].Management science,2015,61(9):2139-2159. [5]CHOU Y C,SUN C C,YEN H Y.Evaluating the criteria for human resource for science for science and technology(HRST)based on an integrated fuzzy AHP and fuzzy DEMATEL approach[J].Applied soft computing,2012,12(1):64-71. [6]WANG X Y,WANG H Q.Comparison research of science and technology(S&T)innovation resources allocation level of each district in China[C].International Conference on Management Science and Engineering-Annual Conference Proceedings,2008:1537-1542. [7]CHARNES A,COOPER W W,RHODES E L.Measuring the efficiency of decision making units[J].European journal of operational research,1978,2(6):429-444. [8]ZHONG W,YUAN W,LI S X,et al.The performance evaluation of regional R&D investments in China:an application of DEA based on the first official China economic census data[J].Omega,2011,39(4):447-455. [9]LEE H,PARK Y,CHOI H.Comparative evaluation of performance of national R&D programs with heterogeneous objectives:a DEA approach[J].European journal of operational research,2009,196(3):847-855. [10]SEXTON T R,SILKMAN R H,HOGAN A J.Data envelopment analysis:critique and extensions[J].New directions for program evaluation,1986(32):73-105. [11]DU J,COOK W D,LIANG L,et al.Fixed cost and resource allocation based on DEA cross-efficiency[J].European journal of operational research,2014,235(1):206-214. [12]LOTFI F H,HATAMI-Marbini A,AGRELL P J,et al.Allocating fixed resources and setting targets using a common-weights DEA approach[J].Computers&industrial engineering,2013,64(2):631-640. [13]DOYLE J,GREEN R.Efficiency and cross efficiency in DEA:derivations,meanings and the uses[J].Journal of the operational research society,1994,45:67-578. [14]WANG Y M,CHIN K S.A neutral DEA model for cross-efficiency evaluation and its extension[J].Expert systems with applications,2010,37(5):3666-3675. [15]WANG Y M,CHIN K S,LUO Y.Cross-efficiency evaluation based on ideal and anti-ideal decision making units[J].Expert systems with applications,2011,38(8):10312-10319. [16]马占新.广义参考集DEA模型及其相关性质[J].系统工程与电子技术,2012,34(4):709-714.
2017, 
