Study on Energy Saving and Emission Reduction Using Data Envelopment Analysis Model

2012 ◽  
Vol 524-527 ◽  
pp. 2437-2441
Author(s):  
Lei Chen ◽  
Hao Qiang Pang ◽  
Tian Yuan Liu ◽  
Guang Mu Zhu ◽  
Wen Quan Tao
Keyword(s):  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Energy Saving ◽  
Emission Reduction ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Weight Method ◽  
Emission Reduction Target ◽  
Using Data

In the paper, on the basis of the comprehensive weight method, the total energy saving and emission reduction target is distributed to every region. Then the DEA model is adopted to evaluate the actual effect of the energy consumption and the emission reduction. Finally, the optimal scheme is put forward. Taking China as example to compare the efficiency of the program A, B and the program C, we get that program B is more suitable for China, and in more developed economical region, the task of energy saving and emission reduction is done better.

Performance Analysis of Hospitals in Kerala Using Data Envelopment Analysis Model

2020 ◽  
Vol 22 (1) ◽  
pp. 25-40
Author(s):  
Saswat Barpanda ◽  
Neena Sreekumar
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Analysis ◽  
Technical Efficiency ◽  
Hospital Performance ◽  
Vital Role ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Input And Output ◽  
Using Data

Performance analysis in any industry plays a vital role in understanding the current scenario and thereby improving the overall efficiency. Using a sample of 20 hospitals randomly selected in Kerala, performance measures of quality were examined as they related to technical efficiency. Efficiency scores for the study hospitals were computed using data envelopment analysis (DEA). The study found that the technically efficient hospitals were performing well as far as quality measures were concerned. DEA can be used to benchmark both dimensions of hospital performance, that is, technical efficiency and quality. The variables selected for the study were divided under input and output measures. Using the DEA model, the factors considered were weighed and analysis was done. The input variables under study are bed number, trained medical staff and services offered. The output variables considered were outpatient rate, mortality rate and number of surgical operations in a month. Through the study, performance of each hospital is measured, and it aims to find out a relation between the input and output variables.

scholarly journals Efficiency of Red Crescent Society Units in Gilan Province and Their Ranking using Data Envelopment Analysis

2020 ◽  
Keyword(s):  
Data Envelopment Analysis ◽  
Organizational Performance ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Super Efficiency ◽  
Using Data ◽  
Gilan Province

INTRODUCTION: Efficiency is one of the basic measures of organizational performance, and in general, refers to the degree or quality of the achievement of the desired goals. This study aimed to investigate the efficiency of Red Crescent population branches in Gilan province and rank them based on the data envelopment analysis model. METHODS: This research was applied in terms of purpose and documentary in terms of implementation. For the purposes of the study, 16 branches of the Red Crescent Society in Gilan province were analyzed with GAMS software (version 24) in 2018. In this research, the input-oriented Banker, Charnes, and Cooper model was used as one of the basic models of data envelopment analysis to measure the relative efficiency of 16 branches of the Red Crescent Society in Gilan province. Afterward, the Anderson-Peterson super-efficiency model was used to rank the efficient units. FINDINGS: Based on the findings, six branches, namely Astara, Rasht, Bandar Anzali, Tallish, Lahijan, and Sowme’eh Sara, had an efficiency score of one. In other words, they were recognized as efficient branches and could provide solutions and models as reference branches for inefficient branches to help them reach the efficiency limit. Afterward, the Anderson-Peterson super-efficiency model was used to rank the efficient units. According to this model, the efficiency scores of the studied units were more than one and the Rasht branch had the highest efficiency. CONCLUSION: The results provide researchers as well as branch managers and staff with suggestions that can help them make better decisions. An important point to keep in mind is that in order to increase the efficiency of a branch, it is necessary to reduce input costs and increase outputs based on reference branches. Due to the fact that this research uses an input-oriented approach, its purpose is to increase the indicators that enhance the efficiency of branches.

scholarly journals REDUCTION OF NON-PERFORMING LOANS IN THE BANKING INDUSTRY: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS

2017 ◽  
Vol 18 (5) ◽  
pp. 833-851 ◽  
Author(s):  
Chih-Ching YANG
Keyword(s):  
Data Envelopment Analysis ◽  
Finite Number ◽  
Relative Efficiency ◽  
Banking Industry ◽  
Negative Impact ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
The World ◽  
Using Data

The increase in non-performing loans around the world has had quite a negative impact on many nations’ banking systems. To address these problems, many creative regulatory solutions and well-designed risk techniques have been utilized in the hope of reducing non-performing loans to an acceptable level. The purpose of this study is to apply a newly developed data envelopment analysis model to suggest the most efficient plan (called Plan 4) to reduce non-performing loans that can maximize the efficiency of the entire banking industry’s control over the bad debts. For comparison purpose, three other reduction plans are also represented. The four plans are presented using data from Taiwan’s banking industry. The empirical results show that among the plans presented, Plan 4 shows the most effective allocation of the industry-wide reduction target. The plan focuses on a finite number of banks, helping identify the key units to improve industry-wide efficiency. The findings implicitly suggest that the regulator should devise more incentive measures to encourage target banks to perform the non-performing loan reduction task. Our results also suggest that for the regulator, forcing banks to cut their non-performing loans by the same ratio will not help improve the relative efficiency of the industry.

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