Regional carbon emission efficiency and its dynamic evolution in China: A novel cross efficiency-malmquist productivity index

2019 ◽  
Vol 241 ◽  
pp. 118260 ◽  
Author(s):  
Lili Ding ◽  
Ying Yang ◽  
Wei Wang ◽  
Adrian Cantemir Calin
1970 ◽  
Vol 5 (1) ◽  
pp. 77
Author(s):  
Mahadzir Ismail ◽  
Saliza Sulaiman ◽  
Hasni Abdul Rahim ◽  
Nordiana Nordin

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad Fallah ◽  
Amir Mohajeri ◽  
Esmaeil Najafi

The VIKOR method was developed for multicriteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the given weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. Here, the VIKOR method is used for two timestandt+1. In order to calculate the progress or regression via Malmquist productivity index, the positive and negative ideals at timestandt+1are calculated first. Then we introduce the multi-criteria ranking index based on the particular measure of “closeness” to the ideal solution and calculate the separation of each alternative from the ideal solution at timestandt+1. Then we use the Malmquist productivity index to calculate the progress or regression of all alternatives. In this paper, productivity of alternatives available in decision matrix with interval numbers and their improvement or deterioration is researched. To achieve this practical goal, use of extended VIKOR is made to calculate Malmquist productivity index for multicriteria decision-making (MCDM) problem with interval numbers, and by applying Malmquist productivity index, productivity rate of growth for alternatives is calculated. Finally, a numerical example illustrates and clarifies the main results developed in this paper.


2021 ◽  
Vol 13 (13) ◽  
pp. 7401
Author(s):  
Sedef E. Kara ◽  
Mustapha D. Ibrahim ◽  
Sahand Daneshvar

This paper examines the dual efficiency of bioenergy, renewable hydro energy, solar energy, wind energy, and geothermal energy for selected OECD countries through an integrated model with energy, economic, environmental, and social dimensions. Two questions are explored: Which renewable energy alternative is more dual efficient and productive? Which renewable energy alternative is best for a particular country? Data envelopment analysis (DEA) is used for the efficiency evaluation, and the global Malmquist productivity index is applied for productivity analysis. Results indicate bioenergy as the most efficient renewable energy alternative with a 20% increase in average efficiency in 2016 compared to 2012. Renewable hydro energy, wind energy, and solar energy show a 17.5%, 16%, and 11% increase, respectively. The average efficiency growth across all renewable energy alternatives signifies major advancement. Country performance in renewable energy is non-monolithic; therefore, they should customize their renewable energy portfolio accordingly to their strengths to enhance renewable energy efficiency. Renewable hydro appears to have the most positive productivity change in 2016 compared to 2012, while solar energy regressed in productivity due to its scale inefficiency. All renewable energy alternatives have relatively equal average pure efficiency change. The positive trend in efficiency and productivity provides an incentive for policy makers to pursue further development of renewable energy technologies with a focus on improving scale efficiency.


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