Environmental efficiency assessment of U.S. transport sector: A slack-based data envelopment analysis approach

Abstract Sustainable transportation in the U.S. is essential for long-term economic growth and mobility, and environmental preservation. Using a non-radial slack-based measurement data envelopment analysis (SBM-DEA) model and state-level data, this study assesses the environmental efficiency of the transportation sector in the U.S. from years 2004 to 2012. In addition to environmental efficiency, carbon efficiency and potential carbon reduction were estimated for the 50 U.S. states. The findings of this study reveal that U.S. transportation sector was environmentally inefficient; U.S. states had an average transportation environmental efficiency score below 0.64. Therefore the states could substantially reduce carbon emissions to improve the environmental efficiency of their transportation sectors.

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

[2]  G. H. Brundtland.  World Commission on environment and development , 1985 .

[3]  Sebastián Lozano,et al.  Slacks-based measure of efficiency of airports with airplanes delays as undesirable outputs , 2011, Comput. Oper. Res..

[4]  Kevin Cullinane,et al.  Estimating the Relative Efficiency of European Container Ports: A Stochastic Frontier Analysis , 2006 .

[5]  Joe Zhu,et al.  Super-efficiency and DEA sensitivity analysis , 2001, Eur. J. Oper. Res..

[6]  Murat Kucukvar,et al.  Sustainability assessment of U.S. manufacturing sectors: an economic input output-based frontier approach , 2013 .

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

[8]  Carl A. Scheraga,et al.  Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis , 2004 .

[9]  Qing Liu,et al.  Toxic air pollution and container port efficiency in the USA , 2017 .

[10]  Chris Hendrickson,et al.  Transportation Sector and Supply Chain Performance and Sustainability , 2006 .

[11]  B. Adenso-Díaz,et al.  Eco-Efficiency of Electric and Electronic Appliances: A Data Envelopment Analysis (DEA) , 2009 .

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

[13]  Murat Kucukvar,et al.  A Novel Life Cycle-based Principal Component Analysis Framework for Eco-efficiency Analysis: Case of the United States Manufacturing and Transportation Nexus , 2015 .

[14]  David A. Hensher,et al.  The impact of strategic management and fleet planning on airline efficiency – A random effects Tobit model based on DEA efficiency scores , 2011 .

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

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

[17]  Russell Pittman,et al.  Multilateral Productivity Comparisons with Undesirable Outputs , 1983 .

[18]  Martin W. P. Savelsbergh,et al.  Carbon-aware transport and logistics , 2014, EURO J. Transp. Logist..

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

[20]  Ning Zhang,et al.  Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure , 2014 .

[21]  Guanghui Zhou,et al.  Measuring energy efficiency performance of China's transport sector: A data envelopment analysis approach , 2014, Expert Syst. Appl..

[22]  J. Leggett,et al.  President Obama’s Climate Action Plan , 2013 .

[23]  A. Hailu,et al.  Non‐Parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry , 2001 .

[24]  L. R. Christensen,et al.  MULTILATERAL COMPARISONS OF OUTPUT, INPUT, AND PRODUCTIVITY USING SUPERLATIVE INDEX NUMBERS* , 1982 .

[25]  Ju Dong Park,et al.  Development of an Aggregate Air Quality Index Using a PCA-Based Method: A Case Study of the US Transportation Sector , 2015 .

[26]  Wei Yang,et al.  Regional environmental efficiency evaluation in China: Analysis based on the Super-SBM model with undesirable outputs , 2013, Math. Comput. Model..

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

[28]  M Molinos-Senante,et al.  Energy efficiency in Spanish wastewater treatment plants: a non-radial DEA approach. , 2011, The Science of the total environment.

[29]  Hao Zhang,et al.  A Slacks-based Measure of Efficiency of Electric Arc Furnace Activity with Undesirable Outputs , 2011 .

[30]  Gokhan Egilmez,et al.  Transportation related carbon, energy and water footprint analysis of U.S. manufacturing: An eco-efficiency assessment , 2014 .

[31]  A. Charnes,et al.  Sensitivity and stability of efficiency classifications in Data Envelopment Analysis , 1996 .

[32]  J. Bi,et al.  Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach , 2008 .

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

[34]  L. C. Lin,et al.  Operational performance evaluation of international major airports: An application of data envelopment analysis , 2006 .

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

[36]  Young-Tae Chang,et al.  Environmental efficiency of ports: a Data Envelopment Analysis approach , 2013 .

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

[38]  Rolf Färe,et al.  Nonparametric Productivity Analysis with Undesirable Outputs: Comment , 2003 .

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

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

[41]  J. Rousseau,et al.  Radii of Classification Preservation in Data Envelopment Analysis: a Case Study of ‘Program Follow-Through’ , 1995 .

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

[43]  Roger Gorham,et al.  Sustainable urban transport: Four innovative directions , 2006 .

[44]  Katsuya Tanaka,et al.  Efficiency analysis of Chinese industry : A directional distance function approach , 2007 .

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

[46]  Cláudia S. Sarrico,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 2001, J. Oper. Res. Soc..

[47]  Nevzat Şimşek,et al.  Energy Efficiency with Undesirable Output at the Economy-Wide Level: Cross Country Comparison in OECD Sample , 2014 .

[48]  A. Charnes,et al.  SENSITIVITY OF EFFICIENCY CLASSIFICATIONS IN THE ADDITIVE MODEL OF DATA ENVELOPMENT ANALYSIS , 1992 .