scholarly journals Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

2020 ◽  
Vol 10 (5) ◽  
pp. 1760 ◽  
Author(s):  
Chia-Nan Wang ◽  
Hsien-Pin Hsu ◽  
Yen-Hui Wang ◽  
Tri-Tung Nguyen
Keyword(s):  
Data Envelopment Analysis ◽  
Poor Performance ◽  
European Countries ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Measure Data ◽  
Productivity Change ◽  
Data Envelopment ◽  
Efficiency Assessment ◽  
Energy Inputs

One problem raised by the lack of energy efficiency is the generation of more greenhouse gases (GHGs) that can cause air pollution and climate change. Ecological efficiency (eco-efficiency) means the efficiency of resources used. A poor performance from this efficiency can then be detected for further improvement. In this research, we conduct an assessment on the eco-efficiency for some European countries as they consume a large part of global energy annually. A total of 17 European countries were selected as decision making units (DMUs) and assessed by the Slacks-based measure (SBM) Data Envelopment Analysis (DEA) model. Indices including Catch-Up, Frontier-Shift, and Malmquist Productivity Index (MPI) have been used to evaluate eco-efficiency, as well as efficiency change, technological change, and productivity change, over 2013–2017. In the model, energy consumption and share of renewable energy are used as energy inputs, and labor productivity and gross capital formation are used as economy inputs. On the other hand, GDP is used as a desired output, and CO2 emissions is used as one undesired output. The experimental results show that the 17 countries as a whole lacked eco-efficiency in 2013–2017, implying more efforts are required to improve their eco-efficiency.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

scholarly journals ANALISIS TINGKAT EFISIENSI SEKTOR PARIWISATA DI JAWA TENGAH TAHUN 2017 DAN 2019

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change

Sektor pariwisata sebagai salah satu sektor yang diandalkan bagi penerimaan daerah maka pemerintah Provinsi Jawa Tengah dituntut untuk dapat menggali dan mengelola potensi wisata yang dimiliki. Penelitian ini bertujuan untuk menganilisis tingkat efisiensi dan produktivitas pada sektor pariwisata di Jawa Tengah antara tahun 2017 dan 2019 dengan sampel 35 Kabupaten/Kota. Analisis dilakukan dengan menggunakan konsep efisiensi yang didasarkan pada teori produksi, pengukuran nilai efisiensi dan produktivitas diperoleh menggunakan metode analisis Data Envelopment Analysis (DEA) dan Malmquist Productivity Index (MPI). Asumsi yang digunakan adalah variable return to scale (VRTS) dan model orientasi output (output oriented). Dengan variable input objek wisata, restoran dan rumah makan, biro perjalanan wisata dan jumlah hotel bintang serta melati. Variabel output dalam penelitian ini adalah wisatawan dan pendapatan sektor pariwisata. Hasil akhir penelitian menunjukkan bahwa terdapat 16 Kabupaten/Kota (45,8%) di tahun 2017, 18 Kabupaten/Kota (51,4%) di tahun 2019 yang mencapai efisiensi teknis penuh. Total Factor productivity change mengindikasikan bahwa 22 Kabupaten/Kota (62,8%) mendekati frontier baik pada frontier produksi maupun frontier efisiensi dan dari scale efficiency change mengindikasikan bahwa terdapat 17 Kabupaten/Kota (48,57%) mengalami perbaikan efisiensi teknis selama periode 2017 ke 2019.

scholarly journals Malmquist Data Envelopment Analysis as a tool to evaluate the Productivity levels of Container Ports in Developing Countries located in East and Southern Africa.

2018 ◽  
Vol 2 (3) ◽  
pp. 79
Author(s):  
Adeola Oluwatoyin OSUNDIRAN ◽  
Felix OKONTA
Keyword(s):  
Data Envelopment Analysis ◽  
Design Research ◽  
Developing Nations ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Port Authorities ◽  
Port Efficiency ◽  
Container Ports

Aim:  The purpose of this paper is to examine the productivity of 12 container ports located in East and Southern African developing nations for the period of 2014-2016. Furthermore, to investigate the sources of productivity change over the time period. Design / Research methods: This research collects data on the 12 container ports. The productivity of these ports is analyzed using the Data Envelopment Analysis based Malmquist productivity index.  This is decomposed into technological changes and technical efficiency. The sources of productivity change are identified.Conclusions /findings: The major finding of this study is the trend in the port efficiency level over the three year period of analysis. Therefore assisting maritime policymakers and port authorities on what aspect of the port production need enhancement. Originality/value of the article: Evaluation of ports in developing nations in Africa is not common. Also, the year under examination is less than five years. Therefore the result is relevant to port authorities as well as to the African nations.Implications of the research: 90% of import and exports into developing African nations are done by sea. The implication of this is that an efficient or inefficient port will have a multiplier effect on the nation’s economy. Great improvement in port productivity will enhance economic growth and development.Limitations of the research: Port efficiency should be evaluated on a yearly basis to serve as a major determinant of port productivity. However, this evaluation is based on availability of data.

scholarly journals Machine learning Clustering Algorithms Based on the DEA Optimization Approach for Banking System in Developing Countries

2020 ◽  
Vol 5 (6) ◽  
pp. 651-658 ◽  
Author(s):  
Mirpouya Mirmozaffari ◽  
Azam Boskabadi ◽  
Gohar Azeem ◽  
Reza Massah ◽  
Elahe Boskabadi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Developing Countries ◽  
Data Envelopment Analysis ◽  
Clustering Algorithms ◽  
Banking System ◽  
Additive Models ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Optimization Approach ◽  
Data Envelopment

Machine learning grows quickly, which has made numerous academic discoveries and is extensively evaluated in several areas. Optimization, as a vital part of machine learning, has fascinated much consideration of practitioners. The primary purpose of this paper is to combine optimization and machine learning to extract hidden rules, remove unrelated data, introduce the most productive Decision-Making Units (DMUs) in the optimization part, and to introduce the algorithm with the highest accuracy in Machine learning part. In the optimization part, we evaluate the productivity of 30 banks from eight developing countries over the period 2015-2019 by utilizing Data Envelopment Analysis (DEA). An additive Data Envelopment Analysis (DEA) model for measuring the efficiency of decision processes is used. The additive models are often named Slack Based Measure (SBM). This group of models measures efficiency via slack variables. After applying the proposed model, the Malmquist Productivity Index (MPI) is computed to evaluate the productivity of companies. In the machine learning part, we use a specific two-layer data mining filtering pre-processes for clustering algorithms to increase the efficiency and to find the superior algorithm. This study tackles data and methodology-related issues in measuring the productivity of the banks in developing countries and highlights the significance of DMUs productivity and algorithms accuracy in the banking industry by comparing suggested models.

scholarly journals A comparative evaluation of operational efficiency of wood industry using data envelopment analysis and Malmquist productivity index

2019 ◽  
Vol 70 (3) ◽  
pp. 287-298 ◽  
Author(s):  
Jože Kropivšek ◽  
Matej Jošt ◽  
Petra Grošelj ◽  
Darko Motik ◽  
Andreja Pirc Barčić ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Comparative Evaluation ◽  
Operational Efficiency ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Low Carbon ◽  
Wood Industry ◽  
International Comparative ◽  
Using Data

The wood industry, as a traditional sector, represents a very important part of the economy in terms of ensuring a sustainable development of society and transition to a low-carbon society in both countries studied, Slovenia and Croatia. For its further development, it is crucial to know the current position of the industry. The best way to achieve this is an analysis of financial data and international comparative evaluation of its operational efficiency. The aim of the research is to compare the relative efficiency of the wood industry using Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MI), focusing on the Slovenian and Croatian wood industry sectors (C16 and C31) for a recent five-year period (from 2013-2017). With this purpose, the combined measure DEA/MI was applied. The analysis includes only the highest rated companies with more than fi ve employees, divided into 12 clusters regarding the company size. As a result, it was established that clusters CRO-C31- micro, CRO-C16-micro and SI-C16-larger have the highest operational efficiency, due to the effects of different financial indicators, especially activity and liquidity ratios. In general, within the grouped clusters regarding country and subsector, groups SI-C16 and CRO-C31 achieve the highest values for the average of weighted score of efficiency, while CRO-C16 achieves the lowest values.

scholarly journals A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1140 ◽  
Author(s):  
Chia-Nan Wang ◽  
Minh Nhat Nguyen ◽  
Anh Luyen Le ◽  
Hector Tibo
Keyword(s):  
National Income ◽  
Value Added ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Beverage Industry ◽  
Food And Beverage Industry ◽  
Food And Beverage ◽  
Research Findings

The food and beverage industry plays a significant role in the economic development of developing and emerging countries in Asia through an immense contribution to the national income, employment, value-added inducement, and foreign exchange earnings. Among the developing countries in Asia, Thailand and Vietnam have recently experienced a significant growth in the industry due to their many advantages. However, the nascent stage of this industry was found to be lacking sustainable competitiveness in both countries. Therefore, this study aims to evaluate and forecast the performance efficiency of the food and beverage industry in Thailand and Vietnam to understand how efficient the food and beverage industry to these countries is and formulate suggestions to improve their productivity in accordance with the research findings. To achieve the research objectives, the resampling method in the data envelopment analysis is applied to measure and forecast the efficiency of 20 Vietnamese companies and 20 Thailand firms over the period of 2016 to 2023. The Malmquist productivity index is deployed to calculate the efficiency change over observed periods. The results reveal that Vietnam is found to have a higher efficiency than Thailand due to the outstanding performance of one company but have performed quite poorly due to low scores in technical and productivity change. The findings of this research can give useful information and practical suggestions to improve performance for inefficient companies as well as enhance competitiveness of the efficient companies trying to operate and reach global markets.

scholarly journals Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4902
Author(s):  
Biswaranjita Mahapatra ◽  
Chandan Bhar ◽  
Sandeep Mondal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Primary Source ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Significant Difference ◽  
Using Data

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019).The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPIefficiency and productivity assessment throughout the years, changes in innovation and technology areincreasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluationof each variable with mines performance. The author formulated the strategies, which in turn help coalprofessionals to improve the efficiency of the mine.

scholarly journals ASSESSMENT OF CONTINENT-WISE ENERGY EFFICIENCY BASED ON CO2 EMISSIONS: A SLACK-BASED DEA APPROACH

2021 ◽  
pp. 17-31
Author(s):  
Mohd Afjal ◽  
Kavya C S
Keyword(s):  
Energy Efficiency ◽  
Data Envelopment Analysis ◽  
Co2 Emissions ◽  
Malmquist Index ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Dea Approach

This study uses the Data Envelopment Analysis (DEA) slack-based model (SBM) and Malmquist Productivity Index (MPI) to evaluate energy efficiency based on CO2 emissions in 42 countries belonging to 6 continents. First, the data envelopment analysis was employed to calculate the efficiency scores for the countries individually and continent basis and then Malmquist index was used to examine the improvement. The study period chosen was 2011-2020. The results of this study showed that on the basis of continents there has been fluctuations in energy efficiency except for Australia, with an efficiency score of equal to one throughout the study period. Additionally, from the results of Malmquist Productivity Index it was found that the 42 countries showed no significant energy enhancement during the period of 2011-2020. KEYWORDS: Energy Efficiency, CO2 emissions, Continents, Data Envelopment Analysis, Malmquist Productivity Index

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