scholarly journals Environmental Efficiency Evaluation in the Top Asian Economies: An Application of DEA

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 889
Author(s):  
Chia-Nan Wang ◽  
Hoang-Phu Nguyen ◽  
Cheng-Wen Chang
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Undesirable Output ◽  
Dea Model ◽  
Asian Economies ◽  
Dea Method ◽  
Bad Outputs

Sustainable development has become a global catchphrase in the recent development age. This leads to the growth of various methodologies in evaluating environmental efficiency, such as the Data Envelopment Analysis (DEA) method. The purpose of this study is to propose an extended DEA model, i.e., the undesirable output model, in measuring the relative eco-efficiency scores across nations. The study collected the data of inputs, namely bad outputs and good outputs of the top 20 Asian economies in the period of 2005–2019, and then estimated the environmental efficiency of each country and classified them. The results have shown that there are four nations having higher average environmental efficiency than others. Japan is a good example of sustainable development that simultaneously balances economic development and environmental protection. The study has also discussed possible solutions for improvement to the group of nations with low environmental efficiency. Contributing to applying a novelty extended DEA model, this work recommends a more precise model, taking the weight of outputs into account for further studies.

Location Optimization of Rapeseed and Soybean Cultivation Areas Considering Economic, Climatic and Social Criteria

2018 ◽  
Vol 9 (3) ◽  
pp. 53-65
Author(s):  
Reza Babazadeh ◽  
Mohammad Voria Yavarirad ◽  
Ehsan Momeni Bashusqeh
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Present Article ◽  
Principle Component Analysis ◽  
Data Envelopment ◽  
Dea Model ◽  
Location Optimization ◽  
Principle Component ◽  
Pca Method ◽  
Dea Method

This article describes how among different oilseeds, rapeseed and soybean contain considerable amounts of protein and oil and have a specific role in agriculture and supplying food. Optimizing the cultivation areas of rapeseed and soybean based on sustainability factors will improve their productivity, economic, environmental, and social objectives. The goal of the present article is to investigate the background for cultivation of these two types of seeds using a data envelopment analysis (DEA) method. Sustainable development criteria including economic, climatic and social criteria are considered in assessing the candidate locations for cultivating soybean and rapeseed by DEA model. The proposed method is applied in Iran. The Principle Component Analysis (PCA) method is used to verify and validate the results of DEA model. Results show that the DEA model can be used as a powerful tool to optimize the cultivation areas of soybean and rapeseed.

scholarly journals Measurement of Environmental Efficiency in the Countries of the European Union with the Enhanced Data Envelopment Analysis Method (DEA) during the Period 2005–2012

Proceedings ◽  
2020 ◽  
Vol 38 (1) ◽  
pp. 20
Author(s):  
Manuel Jesús Hermoso-Orzáez ◽  
Miriam García-Alguacil ◽  
Julio Terrados-Cepeda ◽  
Paulo Brito
Keyword(s):  
European Union ◽  
Data Envelopment Analysis ◽  
Geographical Area ◽  
Environmental Policies ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
The European Union ◽  
Analysis Method ◽  
New Variant ◽  
Dea Method

In recent years there has been growing interest in measuring the environmental efficiency of the different territories, countries and/or nations. This has led to the development of different methods applied to the evaluation of environmental efficiency such as the Data Envelopment Analysis (DEA) method. This method, supported by different studies, allows measuring relative environmental efficiency and is consolidated as a very reliable method to measure the effectiveness of environmental policies in a specific geographical area. The objective of our study is the calculation of the environmental efficiency of the 28 member countries of the European Union (EU) through the DEA method. We will collect the data regarding the last years in which there are reliable comparative data in all. We will study in reference to them, the results of the environmental policies applied in the different countries, in order to make comparisons between countries and classify them according to their environmental efficiency. Using this, two variants of calculation within the DEA method to compare in a contrasted way the results of environmental efficiency for the 28 countries of the European Union (EU) analyzed and propose possible solutions for improvement. Contributing in this work as main novelty the application of a new variant of the DEA Method, which we will call Improved Analysis Method (MAN) and that aims to agglutinate and assess more objectively, the results of the two DEA methods applied. The results show that there are 14 of the 28 countries that have a high relative environmental efficiency. However, we also find countries with very low environmental efficiency that should improve in the coming years. Coinciding precisely in this last group with countries recently admitted to the EU and where environmental policies have not yet been applied effectively and with positive results.

Mengukur Tingkat Efisiensi Bank Umum Syariah dengan Metode DEA dan Perbandingan dengan Rasio Keuangan (Studi Kasus: PT Bank Muamalat Indonesia dan PT Bank Mega Syariah)

2020 ◽  
Vol 1 (1) ◽  
pp. 25-48
Author(s):  
Joni Agusah Putra ◽  
Muhammad Doddy
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Financial Ratio ◽  
Dea Model ◽  
Constant Return ◽  
Dea Method ◽  
Measurement Efficiency ◽  
Production Approach

Penelitian ini dilakukan untuk mengukur tingkat efisiensi Bank Muamalat Indonesia (BMI) dan Bank Mega Syariah (BMS). Metode yang digunakan adalah data envelopment analysis (DEA) model constant return to scale (CRS) dan model variabel return to scale (VRS) dengan pendekatan aset dan produksi. Hasil DEA model CRS pendekatan aset dibadingkan dengan rasio ROA sedangkan hasil DEA model VRS pendekatan produksi dibandingkan dengan rasio BOPO.Hasil penelitian ini menunjukkan, pada pendekatan aset BMI cenderung tidak efisien baik dengan model CRS, VRS dan secara skala. Sementara pada pendekatan produksi BMI tidak efisien dengan model CRS tetapi efisien berdasarkan model VRS dan secara skala. Sedangkan BMS cenderung dalam kondisi yang efisien pada pendekatan aset dan produksi baik dengan model CRS, VRSmaupun secara skala selama periode penelitian. Penelitian ini juga menyimpulkan, pengukuran efisiensi dengan DEA menunjukkan hasil yang konsisten dengan rasio keuangan ROA dan BOPO. Sehingga tidak ada perbedaan antara tingkat efisiensi menggunakan metode DEA dengan tingkat efisiensi menggunakan rasio keuangn pada BMI dan BMS selama periode penelitian.Kata Kunci: Efisiensi BUS, DEA, Rasio KeuanganABSTRACTThis research had been done to measure efficiency level Bank Muamalat Indonesia (BMI) and Bank Mega Syariah (BMS). The method tools were analysis envelopment data (DEA) model constant return to scale (CRS) and models variable return to scale (VRS) through asset and production approach. Result DEA model of asset approach CSR was compared to ratio ROA whereas result DEA model of production approach was compared to ratio BOPO. This research indicated that approach asset BMI tended to inefficiency both model CRS, VRS and by scale. Temporary approaching by production BMI in efficiency with model CRS but efficiency based on model VRS and by scale. Whereas BMS tended to be in efficiency to asset and production approach both model CRS, VRS and by scale during period of research. This research was also to conclude measurement efficiency by using DEA showed consistent result with financial ratio ROA and BOPO. So there would not be difference between the level of efficiency by using DEA method with the level of efficiency by using financial ratio at BMI and BMS during period of research.Keywords: BUS Efisiensi, DEA, Financial Ratio

DEA by sequential exclusion of alternatives in heterogeneous samples

2016 ◽  
Vol 15 (01) ◽  
pp. 5-22 ◽  
Author(s):  
Fuad Aleskerov ◽  
Vsevolod Petrushchenko
Keyword(s):  
Data Envelopment Analysis ◽  
New Method ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Dea Model ◽  
Economic Applications ◽  
Heterogeneous Samples ◽  
Efficiency Estimation ◽  
Dea Approach ◽  
Russian Universities

Data Envelopment Analysis (DEA) is a well-known nonparametric technique of efficiency evaluation which is actively used in many economic applications. However, DEA is not very well applicable when a sample consists of firms operating under drastically different conditions. We offer a new method of efficiency estimation in heterogeneous samples based on a sequential exclusion of alternatives and standard DEA approach. We show a connection between efficiency scores obtained via standard DEA model and the ones obtained via our algorithm. We also illustrate our model by evaluating 28 Russian universities and compare the results obtained by two techniques.

scholarly journals Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3436 ◽  
Author(s):  
Xiaoyang Zhou ◽  
Hao Chen ◽  
Hao Wang ◽  
Benjamin Lev ◽  
Lifang Quan
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Environmental Efficiency ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Assessment ◽  
Radial Model ◽  
Better Than

With the acceleration of industrialization, a large amount of energy consumption has brought tremendous pressure to the natural environment. In order to prevent environmental pollution and promote sustainable development, the environmental efficiency assessment as an effective way to provide decision-making basis has been given wide attention. This study measures the environmental efficiency of 30 provinces in China from 2006 to 2015 based on the Data Envelopment Analysis (DEA) environmental assessment radial model both under natural disposability and managerial disposability that considered the constant variable return to scale (RTS) and the damage to scale (DTS). In addition, the scale efficiency under the two kinds of disposability of China’s 30 provinces were also measured. We found that the environmental efficiencies of different provinces in China showed regional disparities. Provinces such as Beijing, Shanghai, and Guangdong had a good performance in unified environmental efficiency and scale efficiency both under natural disposability and managerial disposability. Generally speaking, the eastern regions always performed better than the central and western regions in unified environmental efficiency during the observed years. Therefore, policies should be established to distribute the resources in balance between the east, center, and west to further promote environmental efficiency.

scholarly journals Cross-Efficiency Evaluation Method with Compete-Cooperate Matrix

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Qiang Hou ◽  
Xue Zhou
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Evaluation Method ◽  
Peer Assessment ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Self Assessment ◽  
Dea Method ◽  
Decision Making Units

Cross-efficiency evaluation method is an effective and widespread adopted data envelopment analysis (DEA) method with self-assessment and peer-assessment to evaluate and rank decision making units (DMUs). Extant aggressive, benevolent, and neutral cross-efficiency methods are used to evaluate DMUs with competitive, cooperative, and nontendentious relationships, respectively. In this paper, a symmetric (nonsymmetric) compete-cooperate matrix is introduced into aggressive and benevolent cross-efficiency methods and compete-cooperate cross-efficiency method is proposed to evaluate DMUs with diverse (relative) relationships. Deviation maximization method is applied to determine the final weights of cross-evaluation to enhance the differentiation ability of cross-efficiency evaluation method. Numerical demonstration is provided to illustrate the reasonability and practicability of the proposed method.

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