scholarly journals Impacts of Air Pollution on Productivity Growth in the Air and Truck Transportation Industries in the US: an Application of the Data Envelopment Analysis Malmquist Environmental Productivity Index

2015 ◽  
Vol 03 (02) ◽  
pp. 120-129 ◽  
Author(s):  
Jaesung Choi ◽  
David C. Roberts
Keyword(s):  
Air Pollution ◽  
Data Envelopment Analysis ◽  
Productivity Growth ◽  
Productivity Index ◽  
Data Envelopment ◽  
The Us ◽  
Truck Transportation

Data envelopment analysis of efficiency of real estate investment trusts in Singapore

2017 ◽  
Vol 59 (6) ◽  
pp. 826-838 ◽  
Author(s):  
Aminath Amany Ahmed ◽  
Azhar Mohamad
Keyword(s):  
Data Envelopment Analysis ◽  
Real Estate ◽  
Productivity Growth ◽  
Real Estate Investment Trusts ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Real Estate Investment ◽  
Content Type ◽  
Investment Trusts

Purpose In this study, the authors use data envelopment analysis to assess the technical efficiency and performance of real estate investment trusts (REITs) in Singapore, for the years 2009 through 2013. Design/methodology/approach The authors apply the Malmquist Productivity Index to express the productivity change of the REITs over time. Findings The authors find that while most REITs have experienced efficiency improvements, there has been little productivity growth at the frontier during the study period. Originality/value The finding indicates that it is possible to improve the performance of the REITs by further improving technological efficiency because technological regress has been the main reason for the poor productivity growth of the REITs in Singapore.

scholarly journals ASSESSMENT OF TFP IN EUROPEAN AND AMERICAN HIGHER EDUCATION INSTITUTIONS – APPLICATION OF MALMQUIST INDICES

2016 ◽  
Vol 24 (2) ◽  
pp. 467-488 ◽  
Author(s):  
Joanna WOLSZCZAK-DERLACZ
Keyword(s):  
Higher Education ◽  
Data Envelopment Analysis ◽  
Productivity Growth ◽  
Negative Association ◽  
Distance Measures ◽  
Data Envelopment ◽  
Total Revenue ◽  
American Higher Education ◽  
Malmquist Indices ◽  
The U.S

In this study we apply Malmquist methodology, based on the estimation of distance measures through Data Envelopment Analysis (DEA), to a sample of 500 universities (in 10 European countries and the U.S.) over the period 2000 to 2010 in order to assess and compare their productivity. On average, a rise in TFP is registered for the whole European sample (strongest for Dutch and Italian HEIs), while the productivity of American HEIs suffered a slight decline. Additionally, we show that productivity growth is negatively associated with size of the institution and revenues from government, and positively with regional development in the case of the European sample, while American HEI productivity growth is characterised by a negative association with GDP and a positive one with the share of government resources out of total revenue.

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 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 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 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.

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