Measuring environmental performance under different environmental DEA technologies

Data envelopment analysis (DEA) efficiency measures integrated with the environmental DEA technology have gained popularity in environmental performance measurement. Most studies assume that the environmental DEA technology exhibits constant returns to scale (CRS). In this paper we further discuss the environmental DEA technologies that exhibit non-increasing returns to scale (NIRS) and variant returns to scale (VRS). The pure measures under different situations and a mixed measure under the VRS environmental DEA technology for measuring environmental performance are proposed. For the measures that deal with nonlinear programming models, we also give their linear programming equivalents. Finally a study on measuring the carbon emission performance of eight world regions is presented.

[1]  Ming-Miin Yu,et al.  Measuring physical efficiency of domestic airports in Taiwan with undesirable outputs and environmental factors , 2004 .

[2]  Paul H. L. Nillesen,et al.  Strategic behaviour under regulatory benchmarking , 2004 .

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

[4]  J. Rączka,et al.  Explaining the performance of heat plants in Poland , 2001 .

[5]  R. Pacudan,et al.  Impact of energy efficiency policy to productive efficiency of electricity distribution industry in the Philippines , 2002 .

[6]  Osman Zaim,et al.  Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework , 2004 .

[7]  B. W. Ang,et al.  Slacks-based efficiency measures for modeling environmental performance , 2006 .

[8]  Dominique Deprins,et al.  Measuring Labor-Efficiency in Post Offices , 2006 .

[9]  Thomas G. Weyman-Jones,et al.  Productive efficiency in a regulated industry: The area electricity boards of England and Wales , 1991 .

[10]  P. W. Wilson,et al.  Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models , 1998 .

[11]  Jyoti K. Parikh,et al.  Study of efficiency and productivity growth in opencast and underground coal mining in india: a DEA analysis , 2002 .

[12]  David Hawdon,et al.  Efficiency, performance and regulation of the international gas industry—a bootstrap DEA approach , 2003 .

[13]  N. Petersen Data Envelopment Analysis on a Relaxed Set of Assumptions , 1990 .

[14]  Peter Bogetoft,et al.  DEA on relaxed convexity assumptions , 1996 .

[15]  D. Niemeijer Developing indicators for environmental policy: data-driven and theory-driven approaches examined by example , 2002 .

[16]  Rolf Färe,et al.  Environmental Performance : an Index Number Approach , 2004 .

[17]  José Luis Zofío,et al.  Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries , 2001 .

[18]  D. Primont,et al.  Multi-Output Production and Duality: Theory and Applications , 1994 .

[19]  Lawrence M. Seiford,et al.  A response to comments on modeling undesirable factors in efficiency evaluation , 2005, Eur. J. Oper. Res..

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

[21]  Rodrigo Taborda,et al.  Perfomance and Efficiency in Colombia's Power Distribution Sistem: Effects of the 1994 Reform , 2006 .

[22]  Finn R. Førsund,et al.  Productivity development of Norwegian electricity distribution utilities , 1998 .

[23]  B. W. Ang,et al.  Is the energy intensity a less useful indicator than the carbon factor in the study of climate change , 1999 .

[24]  Alexander Vaninsky,et al.  Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis , 2006 .

[25]  J. Yunos,et al.  The efficiency of the National Electricity Board in Malaysia: an intercountry comparison using DEA , 1997 .

[26]  Daniel Tyteca,et al.  On the Measurement of the Environmental Performance of Firms— A Literature Review and a Productive Efficiency Perspective , 1996 .

[27]  William W. Cooper,et al.  Chapter 1 Introduction: Extensions and new developments in DEA , 1996, Ann. Oper. Res..

[28]  M. Abbott,et al.  The productivity and efficiency of the Australian electricity supply industry , 2006 .

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

[30]  R. Ramanathan An Introduction to Data Envelopment Analysis: A Tool for Performance Measurement , 2003 .

[31]  Daniel Tyteca,et al.  Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results , 1997 .

[32]  Catherine Waddams Price,et al.  Efficiency and ownership in electricity distribution: A non-parametric model of the Turkish experience , 1996 .

[33]  R. Färe,et al.  An activity analysis model of the environmental performance of firms—application to fossil-fuel-fired electric utilities , 1996 .

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

[35]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[36]  Richard S.J. Tol,et al.  The marginal damage costs of carbon-dioxide emissions’ , 2005 .

[37]  P. Pestieau,et al.  Public Enterprise Economics.@@@The Performance of Public Enterprises: Concepts and Measurement. , 1987 .

[38]  Rolf Färe,et al.  Modeling undesirable factors in efficiency evaluation: Comment , 2004, Eur. J. Oper. Res..

[39]  A. Brent,et al.  Assessing the sustainability performances of industries , 2005 .

[40]  William W. Cooper,et al.  EXTENSIONS AND NEW DEVELOPMENTS IN DEA , 1996 .

[41]  B. W. Ang,et al.  A time-series analysis of energy-related carbon emissions in Korea , 2001 .

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

[43]  Holger Scheel,et al.  Undesirable outputs in efficiency valuations , 2001, Eur. J. Oper. Res..