2019
DOI: 10.3390/pr7060325
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Measuring Energy Efficiency and Environmental Performance: A Case of South Asia

Abstract: When assessing energy efficiency, most studies have frequently ignored environmental aspects even though the concept has been widely used in the past. This study evaluates the energy efficiency and environmental performance of South Asia by using DEA (data envelopment analysis) like mathematical composite indicator. We construct a comprehensive set of indicators, including an energy self-sufficiency ratio, energy production over consumption ratio, energy imports, diversification index of energy imports, energy… Show more

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Cited by 103 publications
(56 citation statements)
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“…At this juncture, instead of totally trusting the counterfactual results generated by the AI, it would be an example of an opportunity where AI-Thinking can be educed. As a suggestion, sustainability analysts might like to consider asking further questions by perusing the works of other sustainability researchers (e.g., see [59][60][61][62][63]). To simulate the worst-case scenario, hard evidence was applied to the node Sustainable Development Goals Index (SDGI), so that 100% of the countries is at the low level (defined as, e.g., 56.7) compared to the original 25.19%; 0% is at the mid-level (defined as, e.g., 71.2) compared to the original 48.31%; and 0% is at the high level (defined as >71.2) compared to the original 26.49%.…”
Section: Predictive Analytics: What If We Want To Achieve High-level mentioning
confidence: 99%
“…At this juncture, instead of totally trusting the counterfactual results generated by the AI, it would be an example of an opportunity where AI-Thinking can be educed. As a suggestion, sustainability analysts might like to consider asking further questions by perusing the works of other sustainability researchers (e.g., see [59][60][61][62][63]). To simulate the worst-case scenario, hard evidence was applied to the node Sustainable Development Goals Index (SDGI), so that 100% of the countries is at the low level (defined as, e.g., 56.7) compared to the original 25.19%; 0% is at the mid-level (defined as, e.g., 71.2) compared to the original 48.31%; and 0% is at the high level (defined as >71.2) compared to the original 26.49%.…”
Section: Predictive Analytics: What If We Want To Achieve High-level mentioning
confidence: 99%
“…Moreover, while some researchers [15][16][17] argue that the use of biofuels and bioenergy have a strong impact on the reduction levels of CO 2 , other economists [18][19][20] conclude that resources productivity and energy efficiency have a higher impact on CO 2 emissions. Nevertheless, while some authors [21][22][23] argued that bioenergy productivity and biofuel production have a direct and significant impact on decreasing the levels of CO 2 emissions, other researchers [24,25] concluded that population and urbanization levels have a significant and negative impact on decreasing the levels of CO 2 emissions.…”
Section: Literature Review and Hypotheses Developmentmentioning
confidence: 99%
“…Zhang et al [3] present a real option model in order to analyze the investment decisions of a coal-fired power plant on Carbon capture, utilization, and storage (CCUS) technologies under imperfect carbon emission trading schemes in China, and the research results show that the utilization ratio of captured CO2 has significant impacts on the net present value and investment value of the CCUS project. Hou et al [4] evaluate the energy efficiency and environmental performance of South Asia, using a DEA (data envelopment analysis)-like mathematical composite indicator. They propose a policy that increases the cross-border trade of renewable energy for long term energy efficiency and environmental performance.…”
Section: Macro Analysis Issuesmentioning
confidence: 99%