Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (12): 251-257.DOI: 10.3778/j.issn.1002-8331.1701-0112

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Weighted dynamic network SBM-DEA model based on group decision making

FAN Jianping, ZHANG Xiaojie, WU Meiqin   

  1. School of Economics and Management, Shanxi University, Taiyuan 030006, China
  • Online:2018-06-15 Published:2018-07-03



  1. 山西大学 经济与管理学院,太原 030006

Abstract: There are three main problems in the application of the traditional DEA models. The first one is how to reflect the subjective attitude of the evaluator. The second one is how to improve the resolution of the dynamic network DEA models when the number of decision making units is small. The third one is how to reasonably determine the weight of each period. In order to solve the above problems, this paper puts forward the concept of “transition period” firstly and predicts input and output data in transition period. And the exponential decay method is proposed to determine the weight of each period. Then this paper constructs a weighted dynamic network SBM-DEA model based on group decision making. Finally, the proposed model is applied to evaluate the efficiency of 16 listed banks of China. The results show that the improved model not only solves the existing problems effectively, but also makes the evaluation results more objective.

Key words: dynamic network DEA, group decision making, slacks

摘要: 传统的DEA模型在实际应用时主要存在三个问题:一是如何体现评价者的主观态度;二是评价有限个决策单元的动态网络效率时如何提高模型的分辨力;三是如何合理地确定子时期的权重。对此,提出了“过渡期”这一概念,首先在已有数据的基础上对过渡期的投入产出数据进行主观预测,接着提出指数衰减法来确定子时期的权重,然后构建了一个基于群决策的加权动态网络SBM-DEA模型,最后应用此模型评价了我国16家上市银行的相对效率。结果表明,改进后的模型不仅有效解决了现有问题,而且得到的评价结果更加客观。

关键词: 动态网络DEA, 多准则群决策, 松弛变量