scholarly journals China’s Input-Output Efficiency of Water-Energy-Food Nexus Based on the Data Envelopment Analysis (DEA) Model

2016 ◽  
Vol 8 (9) ◽  
pp. 927 ◽  
Author(s):  
Guijun Li ◽  
Daohan Huang ◽  
Yulong Li
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Input Output ◽  
Dea Model ◽  
Output Efficiency

The Comprehensive Efficiency Evaluation of Electrical Power System of China Based on Data Envelopment Analysis

2013 ◽  
Vol 860-863 ◽  
pp. 1881-1885 ◽  
Author(s):  
Wang Cheng Long ◽  
Xiao Wang ◽  
Dong Peng ◽  
Qiao Wang
Keyword(s):  
Data Envelopment Analysis ◽  
Power System ◽  
Electrical Power ◽  
Scientific Development ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Input Output ◽  
Analysis Model ◽  
Electrical Power System ◽  
Output Efficiency

With the power system of China continuous expanding recently, the electric power generation, transmission and supply capacity increased dramatically. In order to improve economic operational efficiency and realize scientific development, the Input-Output efficiency between the input of the power system facilities and the output of the power supply becomes a critical issue that government, business and academia have to face up to. In this paper, we used the DEA (Data Envelopment Analysis) model and tested the Input-Output efficiency of power system development and study the trend of important development segment. The relative efficiency of power system is closely related to the electricity management system and economic situation, the elements of reduce the efficiency were been found out by analyzing the DEA results. And a series of suggestions were proposed to increase the comprehensive efficiency.

Generalized Fuzzy Sample DEA Model and its Application in the Evaluation of Projects

2011 ◽  
Vol 63-64 ◽  
pp. 407-411
Author(s):  
Ren Mu ◽  
Zhan Xin Ma ◽  
Wei Cui ◽  
Yun Morigen Wu
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Input Output ◽  
Output Data ◽  
Dea Model ◽  
Decision Making Unit ◽  
Fuzzy Input ◽  
Fuzzy Dea

Evaluating the performance of activities or organizations by traditional data envelopment analysis model requires crisp input/output data. However, in real-world problems inputs and outputs are often with some fuzziness. To evaluate DMU with fuzzy input/output data, researchers provided fuzzy data envelopment analysis (FDEA) model and proposed related evaluating method. But up to now, we still cannot evaluate a fuzzy sample decision making unit (SDMU) for FDEA model. So this paper proposes a generalized fuzzy DEA model which can evaluate a sample decision making unit and a numerical experiment is used to illustrate this model.

The Differences Analysis of Input-Output Efficiency of Regional R&D Activities Based on DEA

2014 ◽  
Vol 599-601 ◽  
pp. 1764-1767
Author(s):  
Yu Han Liu ◽  
Yong Bo Lv ◽  
Yuan Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Technological Innovation ◽  
Technology Development ◽  
Science And Technology ◽  
Data Envelopment ◽  
Input Output ◽  
Regional Investment ◽  
Output Efficiency ◽  
Dea Method ◽  
Using Data

Research and development activities plays an important role in regional science and technology development and technological innovation. Regional R&D input-output efficiency is a measure of the effectiveness of regional investment in science and technology activities. This paper selects four indicators to make evaluation of the input-output efficiency of R&D activities and analysis of differences between regions by using data envelopment analysis (DEA method).

scholarly journals Evaluation of Input-Output Efficiency of Sports Industry Based on SWOT-PEST Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huan Dong ◽  
Zhiguo Liu ◽  
Kai Kong ◽  
Tong Li ◽  
Qianli Ma
Keyword(s):  
Data Envelopment Analysis ◽  
Index System ◽  
Indicator System ◽  
High Tech ◽  
Data Envelopment ◽  
Analysis Method ◽  
Input Output ◽  
Sports Industry ◽  
Industry Environment ◽  
Output Efficiency

This article takes the macro-environmental sports industry as the research object. Firstly, based on the development and characteristics of the sports industry, the article uses the principle of data envelopment analysis to analyze its input and output efficiency and finds out its current problems. In addition, the SWOT analysis method is used to conduct a comprehensive analysis of the external and internal environment influencing the efficiency of the sports industry and propose corresponding development countermeasures. Through the comparison of efficiency evaluation methods, the data envelopment analysis method is proposed to evaluate SWOT efficiency. Secondly, on the basis of pointing out the guiding ideology and basic principles of the evaluation system, four input indicators and four output indicators are specifically selected to form the SWOT input-output indicator system. Thirdly, we introduce the PEST model, focusing on its extended BCC model and use it to make empirical analysis of the SWOT efficiency of regions and provinces. The analysis results show that the efficiency of regional SWOT is not optimal and that there are problems such as input redundancy and insufficient output. Through further analysis, it is concluded that the main reason for the inefficiency of regional SWOT is the unreasonable SWOT input structure and insufficient output value of high-tech industries. We use the analytical framework of this method to clarify the current macro-competitive environment of the sports industry, and use the constructed index system to determine whether the sports industry environment in a region is good or bad. In the selection of indicators, we must carefully analyze their connotations, so that the evaluation index system can accurately evaluate the region’s sports industry environment.

Input–Output Efficiency of Urban Agglomerations in China: An Application of Data Envelopment Analysis (DEA)

Urban Studies ◽  
2013 ◽  
Vol 50 (13) ◽  
pp. 2766-2790 ◽  
Author(s):  
ChuangLin Fang ◽  
XingLiang Guan ◽  
ShaSha Lu ◽  
Min Zhou ◽  
Yu Deng
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Input Output ◽  
Urban Agglomerations ◽  
Output Efficiency

scholarly journals Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model

2018 ◽  
Vol 10 (9) ◽  
pp. 3168 ◽  
Author(s):  
Haoran Zhao ◽  
Huiru Zhao ◽  
Sen Guo
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Variables ◽  
Market Competition ◽  
Environmental Values ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Electricity Grid ◽  
Frontier Analysis ◽  
Dea Model ◽  
Statistical Noise

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.

Sign in / Sign up

Export Citation Format

Share Document