scholarly journals Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

2017 ◽  
Vol 104 ◽  
pp. 012017
Author(s):  
Qiang Xu ◽  
Shuai Ding ◽  
Jingwen An
Keyword(s):  
Energy Efficiency ◽  
Empirical Study ◽  
Malmquist Index ◽  
Region Analysis

Analysis of Total Factor Energy Efficiency of Manufacturing Industry in Shandong Province Based on Malmquist Index Empirical Study

2011 ◽  
Vol 84-85 ◽  
pp. 747-751 ◽  
Author(s):  
Zheng Yuan Jia ◽  
Chuan Cai Li ◽  
Di Yuan
Keyword(s):  
Energy Efficiency ◽  
Empirical Study ◽  
Manufacturing Industry ◽  
Malmquist Index ◽  
Efficiency Index ◽  
Shandong Province ◽  
Factor Productivity ◽  
Light Industry ◽  
Technology Advancement ◽  
Object Of Study

This document takes the 30 completely state-owned manufacturing industry professions in Shandong Province as the object of study, has surveyed the total factor energy efficiency, the technology advancement index and the technology efficiency index of the manufacturing industry with the Malmquist productivity method. The conclusion believed that the value of the manufacturing total factor productivity in Shandong Province is relatively stable in recent years. Light industry or heavy chemical industry which is labor-intensive has lower total factor energy efficiency in various industries.

scholarly journals An Empirical Study of Hadoop's Energy Efficiency on a HPC Cluster

2014 ◽  
Vol 29 ◽  
pp. 62-72 ◽  
Author(s):  
Nidhi Tiwari ◽  
Santonu Sarkar ◽  
Umesh Bellur ◽  
Maria Indrawan
Keyword(s):  
Energy Efficiency ◽  
Empirical Study

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

scholarly journals Measurement and Analysis of Urban Total Factor Energy Efficiency in China

2021 ◽  
Vol 261 ◽  
pp. 01020
Author(s):  
Feifei Lu ◽  
Yinling Lu ◽  
Na Lei
Keyword(s):  
Energy Efficiency ◽  
Technological Progress ◽  
High Efficiency ◽  
Malmquist Index ◽  
Coastal Areas ◽  
Central China ◽  
Measurement And Analysis ◽  
Urban Energy ◽  
Research Objects ◽  
Low Efficiency

The improvement of urban energy efficiency is of great significance to reduce carbon emissions and achieve China’s goal of carbon peak in 2030. Taking 266 cities as the research objects, the energy efficiency of each city is measured by Super-SBM model. Then the energy efficiency is decomposed by Malmquist index. The results show that: In 2006, the number of cities in high-efficiency areas is small and high efficiency areas are mostly distributed in the northeast and southeast coastal areas. There was a phenomenon of low efficiency areas agglomeration. But in 2017, the number of high-efficiency cities increased significantly. The number of high-efficiency cities in Northeast China increased, the number of high-efficiency cities in Southeast coastal areas decreased, and the number of high-efficiency cities in Central China increased and showed a phenomenon of agglomeration of high-efficiency areas or relatively high efficiency areas. According to the decomposition of urban energy efficiency, technological progress is the main driving force for the improvement of energy efficiency, and the decline of technical efficiency inhibits the improvement of energy efficiency in various cities.

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