数据包络分析的新方法——奥地利一般方案的案例

Drinko Kurevija
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引用次数: 0

摘要

本文采用一种新颖的数据包络分析(DEA)方法,即调整后的DEA (a -DEA),分析了奥地利研究促进局(ARPA)一般计划的绩效。考虑到Sowlati和Paradi(2004)通过定义一个新的“实践前沿”和利用管理投入的先前发现,采用了改进的线性规划模型和方法来提高经验效率单位的效率。其目的是找到新颖的“不同”单元的输出,以便确定既具有经验效率又考虑到ARPA一般程序性能的这些“新”dmu的替代边界。
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Novel approach to data envelopment analysis - the case of the Austrian general program
This article analyses the performances of the Austrian Research Promotion Agency's (ARPA) general program by applying a novel approach to data envelopment analysis (DEA) namely the adjusted DEA (A-DEA). Considering the previous findings of Sowlati and Paradi (2004) by defining a new 'practical frontier' and utilising management input, a modified linear programming model and a methodology for improving the efficiency of empirically efficient units was applied. The aim was to find the output for the novel 'different' units in order to identify an alternative frontier of both already empirically efficient and these 'new' DMUs considering the performances of ARPA's general program.
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来源期刊
International Journal of Operational Research
International Journal of Operational Research Decision Sciences-Management Science and Operations Research
CiteScore
1.50
自引率
0.00%
发文量
57
期刊介绍: IJOR is a fully refereed journal generally covering new theory and application of operations research (OR) techniques and models that include inventory, queuing, transportation, game theory, scheduling, project management, mathematical programming, decision-support systems, multi-criteria decision making, artificial intelligence, neural network, fuzzy logic, expert systems, and simulation. New theories and applications of operations research models are welcome to IJOR. Modelling and optimisation have become an essential function of researchers and practitioners in a networked global economy. New theory development in operations research and their applications in new economy and society have been limited.
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