A novel multilevel network slacks-based measure with an application in electric utility companies

Mahmoudabadi, Mohammad Zarei; Azar, Adel; Emrouznejad, Ali

doi:10.1016/j.energy.2018.05.161

Cited by 25 publications

(9 citation statements)

References 27 publications

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“…In many applications, the computational scheme for efficiency measurement must be addressed as multi-stages such as network structures [23]. Conventional DEA models generally treat the DMUs without considering their internal structure [23].…”

Section: Network Deamentioning

confidence: 99%

A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

Amini

Azar

Eskandari

2021

Applied Soft Computing

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Section: Network Deamentioning

confidence: 99%

A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

Amini

Azar

Eskandari

2021

Applied Soft Computing

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“…As a non-parametric method, data envelopment analysis (DEA) has been widely applied to efficiency assessment in the fields of insurance industry [20], bank [21], transportation industry [22], high-tech industry [23] and so on due to its advantages. For example, DEA does not need to consider explicit relationships between inputs and outputs [24], and it can handle multiple inputs and outputs at the same time. Air quality evaluation based on DEA has also attracted much attention of scholars, such as [3,4,10,11].…”

Section: Introductionmentioning

confidence: 99%

The Unified Efficiency Evaluation of China’s Industrial Waste Gas Considering Pollution Prevention and End-Of-Pipe Treatment

Tang

Chen

Yang

et al. 2020

IJERPH

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With the deepening of industrialization and urbanization in China, air pollution has become the most serious environmental issue due to huge energy consumption, which threatens the health of residents and the sustainable development of the country. Increasing attention has been paid to the efficiency evaluation of industrial system due to its fast development and severe air pollution emissions, but the efficiency evaluation on China’s industrial waste gas still has scope for improvement. This paper proposes a global non-radial Network Data Envelopment Analysis (NDEA) model from the perspective of pollution prevention (PP) and end-of-pipe treatment (ET), to explore the potential reduction of generation and emission of air pollutants in China’s industrial system. Given the differences of different air pollution treatment capacities, the ET stage is further subdivided into three parallel sub-stages, corresponding to SO2, NOX, and soot and dust (SD), respectively. Then, grey relation analysis (GRA) is adopted to figure out the key factor affecting the unified efficiency. The main findings are summarized as follows: firstly, the unified efficiency of China’s industrial waste gas underperformed nationwide, and most provinces had the potential to reduce the generation and emission of industrial waste gas. Secondly, the PP efficiency outperformed the ET efficiency in many provinces and the efficiency gap between two stages increasingly narrowed except in 2014. Thirdly, the unified efficiency in the eastern area performed well, while the area disparities increased significantly after 2012. Fourthly, significant differences were found in three ET efficiencies and the ET efficiency of NOX was higher than that of SO2 and SD in the sample period. Finally, the results of GRA indicated that different air pollutants had distinct influence on the improvement of the unified efficiency in three areas. To promote the unified efficiency of industrial waste gas, some pertinent policy suggestions are put forward from the perspectives of sub-stages, air pollutants and areas.

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“…Mahmoudabadi et al (2018) developed an alternative network slacks-based DEA measure (NSBM) to determinate overall efficiency in 16 Iranian electric power companies. The main advantage of NSBM is that they express the efficiency of weakly efficient decision-making units (DMUs) more appropriately than the traditional radial model.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of the electricity sector in Mexico 2008-2015

Navarro-Chávez

Ortega

Díaz-Pulido

2020

IJESM

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Purpose The purpose of this paper is to determine the level of efficiency in the Mexico electricity industry during the 2008-2015 period. Design/methodology/approach A data envelopment analysis (DEA) network model is proposed, where technical efficiency is calculated. A factorial analysis using the principal components method was carried out first. Later, latent dimensions were calculated through the variance criterion and sedimentation graph, where four components were presented. After performing factor rotation, the nodes were grouped: generation, transmission, distribution and sales. It proceeded later to structure a DEA network model. Findings From the calculations made, the most efficient node was the transmission, while the North Gulf and East Center divisions were the only efficient. Research limitations/implications The limitations presented in this study were data collection. Practical implications The implications that were observed were that through the results obtained, proposals can be made to the Mexican electricity sector to improve each of the nodes, and have a better operation and reduce energy losses. Social implications The social impact of this type of study is that based on the results obtained, they present the basis for improving energy policy and users can have a better service that has better quality and coverage. Originality/value The originality of this study consists in the use of two methodologies, factor analysis methodology and DEA network model.

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A novel multilevel network slacks-based measure with an application in electric utility companies

Cited by 25 publications

References 27 publications

A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

The Unified Efficiency Evaluation of China’s Industrial Waste Gas Considering Pollution Prevention and End-Of-Pipe Treatment

Efficiency of the electricity sector in Mexico 2008-2015

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