Statistical Inference of DEA Model of Environmental Efficiency Considering Undesirable Outputs

2014 ◽  
Author(s):  
Yukun Jian ◽  
Lin Dai
Keyword(s):  
Statistical Inference ◽  
Environmental Efficiency ◽  
Undesirable Outputs ◽  
Dea Model

scholarly journals Analysis of Farming Environmental Efficiency Using a DEA Model with Undesirable Outputs

2014 ◽  
Vol 10 ◽  
pp. 154-158 ◽  
Author(s):  
Hsing-Fu Kuo ◽  
Hsiang-Leng Chen ◽  
Ko-Wan Tsou
Keyword(s):  
Environmental Efficiency ◽  
Undesirable Outputs ◽  
Dea Model

scholarly journals Regional Environmental Efficiency Based on a Modified Proportional DEA Model

2018 ◽  
pp. 64-79
Author(s):  
Yuting Xuan ◽  
Wei Woo
Keyword(s):  
Yangtze River ◽  
Risk Attitude ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
The Yangtze River ◽  
Environmental Capacity ◽  
Dea Model ◽  
Conservation Policies ◽  
Ecological Conservation

With the increased attention paid to environmental and ecological issues in China, many methods have been used to evaluate the performance of ecological conservation. Scholars have evaluated environmental efficiency in the production process with undesirable outputs, and used a data envelopment analysis (DEA) model for further examination. However, previous studies do not detail the influence of uncertain factors on undesirable outputs, such as environmental capacity and risk attitude. Therefore, this study proposes and applies a modified proportional DEA model to evaluate the environmental efficiency of various textile and clothing companies located around the main stem and tributaries of the Yangtze River. The empirical results indicate that this model is more suitable to evaluate the environmental efficiency of companies in these acutely polluted regions. Based on these findings, we suggest considering environmental capacity and risk attitude in ecological conservation policies to improve environmental efficiency.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

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.

A common-weights approach for efficiency evaluation in fuzzy data envelopment analysis with undesirable outputs: Application in banking industry

2020 ◽  
Vol 39 (5) ◽  
pp. 7705-7722
Author(s):  
Mohammad Kachouei ◽  
Ali Ebrahimnejad ◽  
Hadi Bagherzadeh-Valami
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Banking Industry ◽  
Evaluation Process ◽  
Fuzzy Arithmetic ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Undesirable Outputs ◽  
Dea Model ◽  
The Impact

Data Envelopment Analysis (DEA) is a non-parametric approach based on linear programming for evaluating the performance of decision making units (DMUs) with multiple inputs and multiple outputs. The lack of the ability to generate the actual weights, not considering the impact of undesirable outputs in the evaluation process and the measuring of efficiencies of DMUs based upon precise observations are three main drawbacks of the conventional DEA models. This paper proposes a novel approach for finding the common set of weights (CSW) to compute efficiencies in DEA model with undesirable outputs when the data are represented by fuzzy numbers. The proposed approach is based on fuzzy arithmetic which formulates the fuzzy additive DEA model as a linear programing problem and gives fuzzy efficiencies of all DMUs based on resulting CSW. We demonstrate the applicability of the proposed model with a simple numerical example. Finally, in the context of performance management, an application of banking industry in Iran is presented for analyzing the influence of fuzzy data and depicting the impact of undesirable outputs over the efficiency results.

scholarly journals A New DEA Model for Evaluation of Supply Chains: A Case of Selection and Evaluation of Environmental Efficiency of Suppliers

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 565 ◽  
Author(s):  
Krmac ◽  
Djordjević
Keyword(s):  
Sensitivity Analysis ◽  
Complex Problem ◽  
Environmental Efficiency ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Chain Management ◽  
Dea Model ◽  
Multi Stage ◽  
Stage System

Supply Chain Management (SCM) represents an example of a complex multi-stage system. The SCM involves and connects different activities, from customer’s orders to received services, all with the aim of satisfying customers. The evaluation of a particular SCM is a complex problem because of the internally linked hierarchical activities and multiple entities. In this paper, the introduction of a non-radial DEA (Data Envelopment Analysis) model for the evaluation of different components of SCM, primarily in terms of sustainability, is the main contribution. However, in order to confirm the novelty and benefits of this new model in the field of SCM, a literature review of past applications of DEA-based models and methods are also presented. The non-radial DEA model was applied for the selection and evaluation of the environmental efficiency of suppliers considering undesirable inputs and outputs resulting in a better ranking of suppliers. Via perturbation of the data used, behavior, as well as the benefits and weaknesses of the introduced model are presented through sensitivity analysis.

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