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首页> 外文期刊>Central European journal of operations research: CEJOR >Relationship between DEA models without explicit inputs and DEA-R models
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Relationship between DEA models without explicit inputs and DEA-R models

机译:没有显式输入的DEA模型与DEA-R模型之间的关系

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摘要

Data envelopment analysis (DEA) is one of often used modeling tools for efficiency and performance evaluation of decision making units. Ratio DEA (DEA-R) is a group of novel mathematical models that combines standard DEA methodology and ratio analysis. The efficiency score given by standard DEA CCR model is less than or equal to that given by DEA-R model. In case of single input or single output the efficiency scores in CCR and DEA-R models are identical. The paper deals with DEA-R models without explicit inputs, i.e. models where only pure outputs or index data are taken into account. A basic DEA-R model without explicit inputs is formulated and a relation between output-oriented DEA models without explicit inputs and output-oriented DEA-R models is analyzed. Central resource allocation and slack-based measure models within DEA-R framework are examined. Finally they are used for projections of decision making units on the efficient frontier. The results of the proposed models are applied for efficiency evaluation of 15 units (Chinese research institutes) and they are discussed.
机译:数据包络分析(DEA)是用于决策单元效率和绩效评估的常用建模工具之一。比率DEA(DEA-R)是一组结合标准DEA方法和比率分析的新颖数学模型。标准DEA CCR模型给出的效率得分小于或等于DEA-R模型给出的效率得分。在单输入或单输出的情况下,CCR和DEA-R模型的效率得分相同。本文涉及没有显式输入的DEA-R模型,即仅考虑纯输出或索引数据的模型。建立了没有显式输入的基本DEA-R模型,并分析了无显式输入的面向输出的DEA模型与面向输出的DEA-R模型之间的关系。检查了DEA-R框架中的中央资源分配和基于松弛的度量模型。最后,它们被用于高效边界上决策单位的预测。所提出的模型的结果可用于15个单位(中国研究机构)的效率评估并进行讨论。

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