Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure

Improving energy efficiency has been widely regarded as one of the most cost-effective ways to improve sustainability and mitigate climate change. This paper presents a sequential slack-based efficiency measure (SSBM) application to model total-factor energy efficiency with undesirable outputs. This approach simultaneously takes into account the sequential environmental technology, total input slacks, and undesirable outputs for energy efficiency analysis. We conduct an empirical analysis of energy efficiency incorporating greenhouse gas emissions of Korean power companies during 2007–2011. The results indicate that most of the power companies are not performing at high energy efficiency. Sequential technology has a significant effect on the energy efficiency measurements. Some policy suggestions based on the empirical results are also presented.

[1]  Kaoru Tone,et al.  A slacks-based measure of efficiency in data envelopment analysis , 1997, Eur. J. Oper. Res..

[2]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[3]  J. Pastor,et al.  Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries , 1995 .

[4]  Jie Wu,et al.  Environmental efficiency evaluation based on data envelopment analysis: A review , 2012 .

[5]  Ning Zhang,et al.  A note on the evolution of directional distance function and its development in energy and environmental studies 1997–2013 , 2014 .

[6]  R. Färe,et al.  Benefit and Distance Functions , 1996 .

[7]  Philippe Vanden Eeckaut,et al.  Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects☆ , 1995 .

[8]  Ning Zhang,et al.  A comparative study of dynamic changes in CO 2 emission performance of fossil fuel power plants in China and Korea , 2013 .

[9]  Chu Wei,et al.  China's energy inefficiency: A cross-country comparison , 2011 .

[10]  M. Porter,et al.  Toward a New Conception of the Environment-Competitiveness Relationship , 1995 .

[11]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[12]  B. W. Ang,et al.  Linear programming models for measuring economy-wide energy efficiency performance , 2008 .

[13]  B. W. Ang,et al.  Boundary problem in carbon emission decomposition , 2002 .

[14]  B. W. Ang,et al.  Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index , 2006 .

[15]  Almas Heshmati,et al.  A sequential Malmquist-Luenberger productivity index : Environmentally sensitive productivity growth considering the progressive nature of technology , 2010 .

[16]  Hui Wang,et al.  Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach , 2012, Eur. J. Oper. Res..

[17]  A. R. Gómez-Calvet,et al.  Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures? , 2014 .

[18]  B. Casu,et al.  Regulatory Reform and Productivity Change in Indian Banking , 2009, Review of Economics and Statistics.

[19]  Hojeong Park,et al.  Valuation of marginal CO2 abatement options for electric power plants in Korea , 2009 .

[20]  Jun Bi,et al.  Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs , 2010 .

[21]  P. Eng CO2 emissions from fuel combustion: highlights , 2009 .

[22]  Ning Zhang,et al.  Environmental energy efficiency of China's regional economies: A non-oriented slacks-based measure analysis , 2013 .

[23]  Lawrence M. Seiford,et al.  Modeling undesirable factors in efficiency evaluation , 2002, Eur. J. Oper. Res..

[24]  William L. Weber,et al.  A directional slacks-based measure of technical inefficiency , 2009 .

[25]  Rolf Färe,et al.  Productivity and Undesirable Outputs: A Directional Distance Function Approach , 1995 .

[26]  Junjie Wu,et al.  Comparative study on efficiency performance of listed coal mining companies in China and the US , 2009 .

[27]  Peng Zhou,et al.  A non-radial DEA approach to measuring environmental performance , 2007, Eur. J. Oper. Res..

[28]  Ning Zhang,et al.  A comparative study of dynamic changes in CO2 emission performance of fossil fuel power plants in China and Korea , 2013 .

[29]  Rolf Färe,et al.  Environmental production functions and environmental directional distance functions , 2007 .

[30]  Ning Zhang,et al.  Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis , 2013 .

[31]  Ling Wang,et al.  Measuring Carbon Emissions Performance in 123 Countries: Application of Minimum Distance to the Strong Efficiency Frontier Analysis , 2013 .

[32]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[33]  C.A.K. Lovell,et al.  Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach , 1989 .

[34]  Lawrence M. Seiford,et al.  Data envelopment analysis (DEA) - Thirty years on , 2009, Eur. J. Oper. Res..

[35]  Dequn Zhou,et al.  Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis , 2012 .

[36]  Manhong Shen,et al.  Empirical Analysis of Provincial Energy Efficiency in China , 2009 .

[37]  Jin-Li Hu,et al.  Total-factor energy efficiency of regions in China , 2006 .

[38]  Ning Zhang,et al.  Environmental efficiency analysis of transportation system in China:A non-radial DEA approach , 2013 .

[39]  Kaoru Tone,et al.  A slacks-based measure of super-efficiency in data envelopment analysis , 2001, Eur. J. Oper. Res..

[40]  Heike Wetzel,et al.  Transport and CO2: Productivity Growth and Carbon Dioxide Emissions in the European Commercial Transport Industry , 2012 .

[41]  Jin-Li Hu,et al.  Total-factor water efficiency of regions in China , 2006 .