The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the...The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit （DMU） might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.展开更多
The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new research...The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.展开更多
The paper studies the non-zero slacks in data envelopment analysis. A procedure is developed for the treatment of non-zero slacks. DEA projections can be done just in one step.
规模化农业机械化生产单位在促进土地流转、提高农业机械化水平等方面发挥了巨大作用,农机合作社是规模化生产单位的代表,评价农机合作社总体经营效果对促进农机合作社和其他新型农业生产经营主体的健康发展具有重要意义。以黑龙江省13...规模化农业机械化生产单位在促进土地流转、提高农业机械化水平等方面发挥了巨大作用,农机合作社是规模化生产单位的代表,评价农机合作社总体经营效果对促进农机合作社和其他新型农业生产经营主体的健康发展具有重要意义。以黑龙江省13个地市农机合作社为研究对象,采用Spearman样本正态性(p=0.01)双侧检验方法确定投入和产出评价指标;建立CCR模型(Charnes Cooper Rhodes,CCR)和超效率DEA模型(Super efficiency-DEA)评价黑龙江省13个地市农机合作社的总体效率;引入Malmquist指数评价分析了黑龙江省农机合作社效率动态变化情况。研究结果表明,黑龙江省各地市农机合作社总体效率较高,但不同地市农机合作社超效率和综合效率差异较大,同地市农机合作社不同分析期的总体效率变动也较大;分析期内黑龙江省各地市农机合作社全要素生产率呈先快后缓的增加趋势,平均全要素生产率呈正增长的地市有5个,占比38.46%。研究结果可为农机合作社等新型农业生产经营主体高质量发展提供理论与技术支撑。展开更多
文摘The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit （DMU） might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.
基金supported by the National Natural Science Foundation of China(71471087)
文摘The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.
文摘The paper studies the non-zero slacks in data envelopment analysis. A procedure is developed for the treatment of non-zero slacks. DEA projections can be done just in one step.
文摘规模化农业机械化生产单位在促进土地流转、提高农业机械化水平等方面发挥了巨大作用,农机合作社是规模化生产单位的代表,评价农机合作社总体经营效果对促进农机合作社和其他新型农业生产经营主体的健康发展具有重要意义。以黑龙江省13个地市农机合作社为研究对象,采用Spearman样本正态性(p=0.01)双侧检验方法确定投入和产出评价指标;建立CCR模型(Charnes Cooper Rhodes,CCR)和超效率DEA模型(Super efficiency-DEA)评价黑龙江省13个地市农机合作社的总体效率;引入Malmquist指数评价分析了黑龙江省农机合作社效率动态变化情况。研究结果表明,黑龙江省各地市农机合作社总体效率较高,但不同地市农机合作社超效率和综合效率差异较大,同地市农机合作社不同分析期的总体效率变动也较大;分析期内黑龙江省各地市农机合作社全要素生产率呈先快后缓的增加趋势,平均全要素生产率呈正增长的地市有5个,占比38.46%。研究结果可为农机合作社等新型农业生产经营主体高质量发展提供理论与技术支撑。
