Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis

The study investigated the technical efficiency of rubber production in Thailand. Secondary data were collected from the Thai rubber plantations in four regions from 2005 to 2014 by using a three-stage data envelopment analysis (DEA) model. The DEA was used to evaluate the technical efficiency levels and to remove undesirable environmental impacts. Furthermore, the Malmquist productivity index was used to measure the changes in the rubber production efficiency and estimate the rubber productivity trend. The findings indicate that the efficiency scores obtained using adjusted inputs in stage 3 of the DEA approach were higher than the efficiency scores in stage 1 of the DEA approach. Moreover, the results also showed that the Northern region has the worst scores of technical efficiency and declination of productivity among the four regions. However, the technical performance of the Thai rubber production has shown a good performance, an upward productivity trend, and has demonstrated the advantages of the method used. Findings from the study could provide crucial information to farmers, the Thai government, and agricultural planners for formulating effective strategies or plans to improve their technology and efficiency levels.

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

Energies ◽

10.3390/en13184902 ◽

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.

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

EPRA International Journal of Economic and Business Review ◽

10.36713/epra8817 ◽

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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Measuring Efficiency of Public Hospitals in Iran: A Comparative Study Using Extended Data Envelopment Analysis, 2012-2016

10.21203/rs.3.rs-36996/v1 ◽

2020 ◽

Author(s):

Efat Mohamadi ◽

Amirhossein Takian ◽

Alireza Olyaee Manesh ◽

Reza Majdzadeh ◽

Farhad Hosseinzadeh Lotfi ◽

...

Keyword(s):

Data Envelopment Analysis ◽

Technical Efficiency ◽

Public Hospitals ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Data Envelopment ◽

Use Of Resources ◽

District Hospitals ◽

Geographical Regions ◽

Efficiency And Productivity

Abstract Background: Aiming to enhance quality of care and increase efficiency, public hospitals have undergone several reforms in the course of last two decades in Iran. This paper reports the result of a national research that aimed to measure the technical efficiency and productivity change of public hospitals during 2012-2016 in Iran. Methods: We used Extended Data Envelopment Analysis (Extended-DEA) (an innovative modification to conventional DEA) to measure technical efficiency and productivity of 568 public hospitals. Nationally representative data were extracted from the official annual health reports. Data were analysed using GAMS software 24.3. Results: The average efficiency score of all hospitals was 0.733. 10.1% of all hospitals were efficient while 2.68% of them were under 0.2. The Malmquist Productivity Index (MPI) progressed in 49.3% of hospitals, remained constant in 2.3%, while 48.2% of hospitals regressed during 2015-2016. The average of MPI was 1.07 over the period of analysis. Conclusions: Extra efforts seem to be essential to enhance the efficient use of resources and develop appropriate policy solutions and tools. In particular, to increase the return to scale, we advocate the merger of small-size district hospitals towards establishing bigger efficient hospitals in various geographical regions across the country.

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Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

International Business Research ◽

10.5539/ibr.v14n12p111 ◽

2021 ◽

Vol 14 (12) ◽

pp. 111

Author(s):

Jui-Lung Chen

Keyword(s):

Data Envelopment Analysis ◽

Machine Tool ◽

Technical Efficiency ◽

Technical Progress ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Business Strategies ◽

Scale Efficiency ◽

Data Envelopment ◽

Business Efficiency

Data envelopment analysis (DEA) is widely used to measure the business efficiency of many industries, among which the Taiwanese machine tool industry is well-known for its complete supply-chain system. Relying on DEA and Malmquist Productivity Index to analyze the business efficiency of Taiwanese listed machine tool manufacturers from 2018 to 2019, this study compared the changes in their business efficiencies and productivities. According to the five change indicators of Malmquist, only the technical efficiency, pure technical efficiency, and scale efficiency of the overall industry posted some growth during the research period, showing that the whole industry is actively improving its technical efficiency and striving to achieve the scale efficiency. However, technical change and total factor productivity declined slightly, indicating that the industry still makes more technical progress. Thus, companies should adjust their inputs and outputs to improve the production boundary for technical progress. The purposes of this study are to identify the success factors of the excellent performance of manufacturers and the benchmarking indicators of the decision-making unit on the efficient frontier results to provide some references for formulating future business strategies and direction.

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Technical efficiency of private sector hospitals in India using data envelopment analysis

Benchmarking An International Journal ◽

10.1108/bij-06-2017-0135 ◽

2018 ◽

Vol 25 (9) ◽

pp. 3570-3591 ◽

Cited By ~ 6

Author(s):

Aradhana Vikas Gandhi ◽

Dipasha Sharma

Keyword(s):

Data Envelopment Analysis ◽

Technical Efficiency ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Data Envelopment ◽

Hospital Industry ◽

Technological Advancement ◽

Tobit Regression ◽

Content Type ◽

Input Variables

Purpose The purpose of this paper is to ascertain the performance of Indian hospitals in recent past and derive meaningful insights for policy makers and practicing managers in this area. Design/methodology/approach This paper analyses the technical efficiency of select Indian private hospitals using three related methodologies: data envelopment analysis (DEA), Malmquist Productivity Index (MPI) and Tobit regression. Two output variables (i.e. total income and profit after tax) and four input variables (i.e. cost of labour, net fixed assets, current assets and other operating expenses) were selected for the purpose of the study. Findings DEA analysis has shown that 14 out of 37 hospitals are found to be efficient under the Cooper and Rhodes model of DEA and 20 out of 37 hospitals are efficient under the Banker, Charles and Cooper model of DEA. The empirical results pertaining to MPI indicate an overall productivity progress in the private Indian hospital industry during the study period, which is largely due to technological advancement in the industry. Tobit regression demonstrates that chain affiliated, specialized and multi-city located hospitals exhibit a higher technical efficiency. Research limitations/implications This study has a limitation with reference to the unavailability of data on the input and output parameters of the model. The data related to the number of beds, number of doctors, number of nurses, etc., were not available for the period under consideration. Originality/value This study seems to be one of the few studies applying productivity and performance analysis using DEA, MPI and Tobit regression for the Indian private hospital industry.

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Performance evaluation of e-commerce firms in China: Using three-stage data envelopment analysis and the Malmquist productivity index

PLoS ONE ◽

10.1371/journal.pone.0255851 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255851

Author(s):

Sufang Zheng ◽

Rabnawaz Khan

Keyword(s):

Data Envelopment Analysis ◽

Technical Efficiency ◽

Economies Of Scale ◽

Stochastic Frontier Analysis ◽

Advanced Technology ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Operating Efficiency ◽

Data Envelopment ◽

Frontier Analysis

As a new business form of international trade and electronic commerce, e-commerce has been a controversial topic that has attracted the attention of scholars and industry professionals. This study estimated the operating efficiency and total factor productivity (TFP) of listed e-commerce firms in China from 2015 to 2019. Three related methodologies were applied: data envelopment analysis (DEA), the Malmquist TFP index, and stochastic frontier analysis. The DEA analysis results showed that environmental variables exerted a substantial effect on technical efficiency. Most firms demonstrated effective technical efficiency after adjustment for input variables. Business-to-business firms had the highest operating efficiency, followed by business-to-consumer and production-to-consumer firms. Technical progress and scale were identified as two major factors affecting improvement in TFP. Hence, e-commerce firms should make full use of advanced technology and aim to achieve economies of scale.

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Seaport efficiency and productivity based on Data Envelopment Analysis and Malmquist Productivity Index

Logistics & sustainable transport ◽

10.1515/jlst-2015-0008 ◽

2015 ◽

Vol 6 (1) ◽

pp. 25-33 ◽

Cited By ~ 4

Author(s):

Joanna Baran ◽

Aleksandra Górecka

Keyword(s):

Data Envelopment Analysis ◽

Technical Efficiency ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Scale Efficiency ◽

Data Envelopment ◽

Data Set ◽

Container Ports ◽

Efficiency Ranking ◽

Efficiency And Productivity

Abstract Seaport efficiency and productivity are the critical factors for handling of goods in the international supply chains and plays an important role in trade exchange with other countries. It is important to evaluate efficiency and productivity of seaports to reflect their status and reveal their position in competitive environment. The main purpose of this article is to use Data Envelopment Analysis and Malmquist Productivity Index to measure the technical efficiency and total factor productivity of container ports. DEA analysis enables one to assess how efficiently a seaports uses the available inputs to generate a set of outputs relative to other units in the data set. This article presents the use CCR and BCC DEA model, to determine overall technical efficiency, pure technical efficiency and scale efficiency of container ports. The analysis gives a possibility to create a efficiency ranking of seaports. The study also applies the Malmquist Productivity Index (MPI), which was used to analyze changes in seaports productivity. The study indicated that technological progress had a greater impact on the change in productivity of container ports than changes in technical efficiency.

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Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

International Business Research ◽

10.5539/ibr.v14n12p125 ◽

2021 ◽

Vol 14 (12) ◽

pp. 125

Author(s):

Jui-Lung Chen

Keyword(s):

Data Envelopment Analysis ◽

Machine Tool ◽

Technical Efficiency ◽

Technical Progress ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Business Strategies ◽

Scale Efficiency ◽

Data Envelopment ◽

Business Efficiency

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

Mathematical Problems in Engineering ◽

10.1155/2014/121804 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 6

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.

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

European Journal of Engineering Research and Science ◽

10.24018/ejers.2020.5.6.1924 ◽

2020 ◽

Vol 5 (6) ◽

pp. 651-658 ◽

Cited By ~ 1

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.

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