Super Efficiency DEA Evaluation Method with Anti-Entropy-Delphi Combined Weights Constraints Cone

Na Xu
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Abstract

In order to avoid the situation where the weight assignment value is zero in the data envelopment analysis, the weights of its input and output indexes should be restricted. In this paper, the objective weight determined by the anti-entropy method is combined with the subjective weight determined by the Delphi method, and then the combined weight is obtained according to the principle of minimum variance, which is added to the data envelopment analysis as a constraint condition to construct the super efficiency DEA model with anti-entropy-Delphi combined weights constrains cone. The new evaluation model with the constraint cone can not only reflect the objective impact of data on the index weight, but also integrate the subjective consciousness of experts, and achieve a complete ranking of the evaluation results. Finally, an empirical analysis of the innovation efficiency of basic research in Beijing from 2011 to 2020 is made based on panel data. The result shows that the new model has obvious advantages compared with the super-efficiency DEA model.
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反熵-德尔菲联合权约束锥的超效率DEA评价方法
为了避免在数据包络分析中权重分配值为零的情况,需要对其输入和输出指标的权重进行限制。本文将反熵法确定的客观权值与德尔菲法确定的主观权值相结合,根据最小方差原理得到组合权值,并将其作为约束条件加入到数据包络分析中,构建了具有反熵-德尔菲组合权值约束圆锥的超效率DEA模型。基于约束锥的评价模型既能反映数据对指标权重的客观影响,又能整合专家的主观意识,实现对评价结果的完整排序。最后,基于面板数据对2011 - 2020年北京市基础研究创新效率进行了实证分析。结果表明,与超效率DEA模型相比,新模型具有明显的优势。
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