Evaluation of relative performance of Indian states in PV resource utilization through MPI

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Vinod Kumar Yadav ◽  
Preeti Goyal ◽  
Arshiya Thukral ◽  
Nandni Varshney ◽  
Santosh Ghosh
Keyword(s):  
Climate Change ◽  
Relative Performance ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
National Goal ◽  
Indian States ◽  
Model Time Series ◽  
Installed Capacity ◽  
Insight Into

Abstract To participate in the global fight against climate change, India has set an aggressive target of installing 100 GW of photovoltaic (PV) energy resources by 2022. However, only about 37% of this target is achieved till date, and, presently, the set target appears to be elusive. Hence it is crucial and the need of the hour to analyze the performance of different utilities to identify the regions that need a course correction. In the present work, the relative performance of the Indian states in realizing the national target of PV installed capacity is analyzed through the Data Envelopment Analysis (DEA) model. Time series analysis of the PV sector’s growth in different Indian states over the period 2017–2021 is quantified through the Malmquist productivity index (MPI). The applied methodology revealed that Rajasthan, which has the highest PV potential and second-highest PV installed capacity, is less productive than the small hilly states and union territories, which have meager PV potential. The result provides insight into the factors contributing to the inefficiencies in the development of the PV energy sector, which will help the policymakers take necessary corrective actions to improve the states’ productivity and thereby contribute more effectively to the national goal. The work may be extended to other regions of the world to strengthen the global effort to fight climate change.

Impact of merger on efficiency and productivity : a case study of commercial banks in Malaysia

1970 ◽  
Vol 5 (1) ◽  
pp. 77
Author(s):  
Mahadzir Ismail ◽  
Saliza Sulaiman ◽  
Hasni Abdul Rahim ◽  
Nordiana Nordin
Keyword(s):  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Master Plan ◽  
Before And After ◽  
Domestic Banks ◽  
The Impact ◽  
Efficiency And Productivity

The Financial Master Plan (2001- 2010) aims to enhance the capacity of banking industry so that higher effic iency and productivity can be reaped in the future. This study seeks to determine the impact of merger on the efficiency and productivity ofcommercial banks in Malaysia for the period 1995 until 2005. The study uses a non-parametric approach, nam ely DEA (data envelopment analysis?) to estimate the efficiency scores and to construct the Malmquist productivity index. To enable this estimation, three bank inputs and outputs are used. Amongst the findings are those banks exhibit higher efficiency score after the merger and thefo reign banks are more efficient than the local banks. Productivity of the banks is calculated in both periods, before and after the merger: The results show that, it is the local banks that have improved the most after the merger. The main source of productivity is technical change or innovation. The findings support the existing policy of having larger domestic banks in term of size.

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 An Efficiency and Productivity of Zakat Institution in Malaysia and Indonesia: The Comparative Study

2019 ◽  
pp. 243-257
Author(s):  
Aas Nurasyiah ◽  
Risa Sari Pertiwi ◽  
Faqih Adam
Keyword(s):  
Role Model ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Fourth Quadrant ◽  
High Efficient ◽  
Using Data ◽  
The Comparative Study ◽  
Standardization Policy ◽  
Efficiency And Productivity

The efficiency and productivity of Zakat institution have widely discussed, it is an organization based on social which looks after economic disparities. Most recently, Indonesia made a standardization policy and system of zakat institution, so that the zakat institution in Indonesia can reach the same quality or higher rather than other countries. It called Zakat Core Principles. Therefore, this research will focus on the zakat institution in Indonesia and Malaysia. The purpose of this study is to measure and compare the efficiency and productivity using Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI), which is a non-parametric and deterministic methodology for determining the relative efficiency and productivity. The result of this research shows, The first quadrant is the best efficient and productive institutions gained by zakat institution in Indonesia namely Sinergi Foundation and 3 zakat institutions in Malaysia namely Kedah, Melayu Perak, and Selangor. The second quadrant is highly productive but low efficient achieved by zakat institutions in Indonesia namely Baznas, RZ, Dompet Dhuafa and 1 zakat institution in Malaysia namely Jawhar. The third quadrant is high efficient but low productive didn’t achieve by any zakat institution in Indonesia or Malaysia. The fourth quadrant is low efficient and low productive reached by 1 zakat institution in Indonesia namely PKPU and 3 zakat institution in Malaysia namely Kelantan, PPZ and Pahang. The implication in this study is describing the position of zakat institution in Indonesia and Malaysia so that it is known which zakat institution could be a role model or benchmarking for other zakat institution.  

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 Efficiency Analysis of Microfinance Institutions in Bangladesh: Does Regulation Matter?

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Farhana Ferdousi
Keyword(s):  
Efficiency Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Microfinance Institutions ◽  
Tobit Regression ◽  
Productivity Increase ◽  
Before And After ◽  
Tools And Techniques ◽  
Productive Growth

The aim of this study is to measure efficiency of various Microfinance Institutions (MFIs) in Bangladesh before and after introducing Microcredit Regulatory Authority (MRA) in order to capture the immediate impact of regulation. Data Envelopment Analysis (DEA) and Malmquist Productivity index technique have been used for this study. Findings reveal that 35% firms’ average productivity increase sharply after enacting microfinance regulation. Seven firms have been graduated from the inefficiency level to efficiency level. However, most of the firms among the increased efficiency list are comparatively young in terms of starting their microfinance operations. Result of Tobit regression does not find any significant relationship between efficiency and regulation. Due to regulation, only number of outreach increases but to ensure more productive growth, MRA needs to be more proactive in strengthening policy environment and educating MFIs to be better equipped with sound financial and managerial tools and techniques.

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.

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.

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