Improved interval DEA models with common weight

Sun, Jiasen; Miao, Yajun; Wu, Jie; Cui, Lianbiao; Zhong, Ray Y.

doi:10.14736/kyb-2014-5-0774

Cited by 6 publications

(11 citation statements)

References 15 publications

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“…The aggregating weights of the lower and upper efficiencies are h 1 and h 2 , and h 1 + h 2 = 1. The results obtained by Sun et al [50] are presented in Table 4.…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 93%

“…Based on these relative Euclidean distances, the ranking results of the DMUs are obtained, which are shown in Table 4. In order to compare our approach with other models, the interval DEA model proposed by Sun et al [50] is selected to evaluate these DMUs. Hadad and Hanani [51] provided a survey on the common weight DEA models (Ganley and Cubbin [52]; Friedman and Sinuany-Stern [53] and Adler et al [54]).…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 99%

“…However, these models can only be used to evaluate the efficiencies of DMUs with precise data, and they are incapable of assessing DMUs with interval data. Based on the idea of common weights, Sun et al [50] proposed an interval DEA model. Therefore, to make a fair comparison, we compare our results with the results from Sun et al [50].…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 99%

“…Based on the idea of common weights, Sun et al [50] proposed an interval DEA model. Therefore, to make a fair comparison, we compare our results with the results from Sun et al [50]. Sun et al [50] used a simple weighting method to aggregate the lower and upper efficiencies for obtaining the final efficiency.…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 99%

“…Therefore, to make a fair comparison, we compare our results with the results from Sun et al [50]. Sun et al [50] used a simple weighting method to aggregate the lower and upper efficiencies for obtaining the final efficiency. The aggregating weights of the lower and upper efficiencies are h 1 and h 2 , and h 1 + h 2 = 1.…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 99%

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Entropy Cross-Efficiency Model for Decision Making Units with Interval Data

Wang

Hong

2016

Entropy

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Abstract:The cross-efficiency method, as a Data Envelopment Analysis (DEA) extension, calculates the cross efficiency of each decision making unit (DMU) using the weights of all decision making units (DMUs). The major advantage of the cross-efficiency method is that it can provide a complete ranking for all DMUs. In addition, the cross-efficiency method could eliminate unrealistic weight results. However, the existing cross-efficiency methods only evaluate the relative efficiencies of a set of DMUs with exact values of inputs and outputs. If the input or output data of DMUs are imprecise, such as the interval data, the existing methods fail to assess the efficiencies of these DMUs. To address this issue, we propose the introduction of Shannon entropy into the cross-efficiency method. In the proposed model, intervals of all cross-efficiency values are firstly obtained by the interval cross-efficiency method. Then, a distance entropy model is proposed to obtain the weights of interval efficiency. Finally, all alternatives are ranked by their relative Euclidean distance from the positive solution.

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“…The aggregating weights of the lower and upper efficiencies are h 1 and h 2 , and h 1 + h 2 = 1. The results obtained by Sun et al [50] are presented in Table 4.…”

Section: The Results and Compared With Other Modelsmentioning

confidence: 93%