Dynamic super-efficiency interval data envelopment analysis

Author(s):  
Ling Li ◽  
Xuliang Lv ◽  
Weidong Xu ◽  
Zhixin Zhang ◽  
Xianhui Rong
Kybernetes ◽  
2016 ◽  
Vol 45 (4) ◽  
pp. 666-679 ◽  
Author(s):  
Qian Yu ◽  
Fujun Hou

Purpose – The traditional data envelopment analysis (DEA) model as a non-parametric technique can measure the relative efficiencies of a decision-making units (DMUs) set with exact values of inputs and outputs, but it cannot handle the imprecise data. The purpose of this paper is to establish a super efficiency interval data envelopment analysis (IDEA) model, an IDEA model based on cross-evaluation and a cross evaluation-based measure of super efficiency IDEA model. And the authors apply the proposed approach to data on the 29 public secondary schools in Greece, and further demonstrate the feasibility of the proposed approach. Design/methodology/approach – In this paper, based on the IDEA model, the authors propose an improved version of establishing a super efficiency IDEA model, an IDEA model based on cross-evaluation, and then present a cross evaluation-based measure of super efficiency IDEA model by combining the super efficiency method with cross-evaluation. The proposed model cannot only discriminate the performance of efficient DMUs from inefficient ones, but also can distinguish between the efficient DMUs. By using the proposed approach, the overall performance of all DMUs with interval data can be fully ranked. Findings – A numerical example is presented to illustrate the application of the proposed methodology. The result shows that the proposed approach is an effective and practical method to measure the efficiency of the DMUs with imprecise data. Practical implications – The proposed model can avoid the fact that the original DEA model can only distinguish the performance of efficient DMUs from inefficient ones, but cannot discriminate between the efficient DMUs. Originality/value – This paper introduces the effective method to obtain the complete rank of all DMUs with interval data.


2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.


Author(s):  
Margareta Gardijan Kedžo

The chapter investigates chosen hedging strategies with options as useful risk hedging instruments. Assuming that average investor prefers greater return, is risk-averse, and prefers greater positive skewness, the performance of different hedged and unhedged portfolios is evaluated using stochastic dominance (SD) criteria and data envelopment analysis (DEA). The SD is examined up to the third degree (TSD) using Davidson-Duclos (DD) test. In the DEA, a super efficiency BCC model is used. It is investigated how these two methodologies can be combined and how the TSD criteria can be integrated into DEA in order to simplify the analysis of determining efficient hedging strategies with options.


Omega ◽  
2013 ◽  
Vol 41 (4) ◽  
pp. 731-734 ◽  
Author(s):  
Hsin-Hsiung Fang ◽  
Hsuan-Shih Lee ◽  
Shiuh-Nan Hwang ◽  
Cheng-Chi Chung

2013 ◽  
Vol 275-277 ◽  
pp. 2788-2792
Author(s):  
You Min Gao ◽  
Xiao Wen Wang

Construction industry is a main industry in national economy, Chinese construction industry has made huge achievement, but the developments between different provinces in China are imbalanced. To compare the different efficiencies between them, data envelopment analysis and an important extended means of DEA were introduced, compared and applied in empirical analysis of Chinese construction industry efficiency between different provinces based on statistical data. Then some conclusions and advices were reached in the end.


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