Using the data envelopment analysis (DEA) model to evaluate the operational efficiency

2012 ◽  
Vol 6 (37) ◽  
Author(s):  
Horng-Jinh Chang
2018 ◽  
Vol 10 (9) ◽  
pp. 3168 ◽  
Author(s):  
Haoran Zhao ◽  
Huiru Zhao ◽  
Sen Guo

With the implementation of new round electricity system reform in China, the provincial electricity grid enterprises (EGEs) of China should focus on improving their operational efficiency to adapt to the increasingly fierce market competition and satisfy the requirements of the electricity industry reform. Therefore, it is essential to conduct operational efficiency evaluation on provincial EGEs. While considering the influences of exterior environmental variables on the operational efficiency of provincial EGEs, a three-stage data envelopment analysis (DEA) methodology is first utilized to accurately assess the real operational efficiency of provincial EGEs excluding the exterior environmental values and statistical noise. The three-stage DEA model takes the amount of employees, the fixed assets investment, the 110 kV and below distribution line length, and the 110 kV and below transformer capacity as input variables and the electricity sales amount, the amount of consumers, and the line loss rate as output variables. The regression results of the stochastic frontier analysis model indicate that the operational efficiencies of provincial EGEs are significantly affected by exterior environmental variables. Results of the three-stage DEA model imply that the exterior environmental values and statistical noise result in the overestimation of operational efficiency of provincial EGEs, and the exclusion of exterior environmental values and statistical noise has provincial-EGE-specific influences. Furthermore, 26 provincial EGEs are divided into four categories to better understand the differences of operational efficiencies before and after the exclusion of exterior environmental values and statistical noise.


2020 ◽  
Vol 15 (2) ◽  
pp. 165
Author(s):  
Asmina Akter

In this study an Output-oriented DEA (Data Envelopment Analysis) model is used to measure operational efficiency of foreign branches of Bangladeshi banks as financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit. Among 58 Bangladeshi banks there are only three Bangladeshi banks which have in total seven foreign branches in different foreign locations. A branch of bank can’t be separated legally from its parent company and supervised by its home authorities as part of supervision of the banking group as a whole. By employing DEA model and using “Financial Intermediary Approach” this study found that as a financial intermediary organization between savers and borrowers these foreign branches of Bangladeshi banks are performing efficiently over the years. Among three banks Janata Bank Limited and AB Bank limited are performing most efficiently and Sonali Bank Limited is performing less efficiently relative to two other banks in operating their foreign branches as a financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit.


2020 ◽  
Vol 13 (1) ◽  
pp. 115-125
Author(s):  
Mariusz Pyra

SummarySubject and purpose of work: This paper aims to assess the operational efficiency of public higher vocational schools in the Lublin Region.Materials and methods: The assessment was based on the non-parametric method of data envelopment analysis (DEA) using the standard CCR-O model.Results: In most of the analysed models (E, N, O series), the public higher vocational schools in the Lublin Region were found to have improved their efficiency in 2019 relative to 2017.Conclusions: E-series models are very susceptible to changes, both in terms of inputs and effects. This gives the possibility of a significant impact on the increase in the assessment of the effectiveness of investigated units DMUs. N-series models demonstrate the importance of aggregation and quality of source data for the results of performance assessment. Class O models justify the need to look for and compare the use of other DEA model variants in the study of the effectiveness of public higher vocational schools.


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.


2019 ◽  
Vol 9 (2) ◽  
pp. 246 ◽  
Author(s):  
Yong Xie ◽  
Yafang Gao ◽  
Shihao Zhang ◽  
Hailong Bai ◽  
Zhenghao Liu

This study presents a method that is based on the three-stage network Data Envelopment Analysis (DEA) to evaluate the sustainability of packaging systems for a product. This method facilitates the selection of better product packaging alternatives from an environmentally friendly point of view and it comprises the following four steps: (i) the definition of packaging sustainability indicator (PSI) based on environmental efficiency and impact indicator of three-stage in packaging life cycle, (ii) modeling a three-stage Network DEA model for a packaging system, (iii) computing PSI based on the DEA model, and (iv) result analysis. An empirical test has been progressed to prove the feasibility of the proposed method by selecting the three types of milk packaging systems. The results indicated that the PSI value of PrePack is the maximum and the Tetra Pak minimum. According to these results, the study provides an environmentally friendly evaluation method for product packaging systems, which is more intuitive than Life Cycle Assessment (LCA).


2019 ◽  
Vol 11 (8) ◽  
pp. 2330 ◽  
Author(s):  
Patricija Bajec ◽  
Danijela Tuljak-Suban

Sustainable concerns are reputed to be of the utmost priority among governments. Consequently, they have become more and more of a concern among supply chain partners. Logistics service providers (LPs), as significant contributors to supply chain success but also one of the greatest generator of emissions, play a significant role in reducing the negative environmental impact. Thus, the performance evaluations of LPs should necessarily involve such a measure which, firstly, represents a balance between all three pillars of sustainability and, secondly, consider the desirable and undesirable performance criteria. This paper proposes an integrated analytic hierarchy process (AHP) and slack-based measure (SBM) data envelopment analysis (DEA) model, based on the assumption of a variable return to scale (VRS). An AHP pairwise comparison enables selecting the most influential input/output variables. Output-oriented SBM DEA provides simultaneously evaluation of both the undesirable and desirable outputs. The proposed model was tested on a numerical example of 18 LPs. The comparison of output Charnes, Cooper and Rhodes (CCR) and SBM DEA models resulted in a higher number of inefficient LPs when the SBM DEA model was applied. Moreover, efficiency scores of inefficient LPs were lower in SBM DEA model. The proposed model is fair to those LPs that are environmentally friendly.


2020 ◽  
Vol 39 (5) ◽  
pp. 7705-7722
Author(s):  
Mohammad Kachouei ◽  
Ali Ebrahimnejad ◽  
Hadi Bagherzadeh-Valami

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.


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