Evaluating energy efficiency for airlines: An application of VFB-DEA

Journal of Air Transport Management

Volumn 44-45, Issue , 2015, Pages 34-41

  Cui, Qiang ^a   Li, Ye ^b  

^a DALIAN MARITIME UNIVERSITY   (China)

^b DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Airlines; Energy efficiency; VFB DEA

Indexed keywords

AIRLINE INDUSTRY; DATA ENVELOPMENT ANALYSIS; ENERGY EFFICIENCY; FINANCIAL CRISIS; NUMERICAL MODEL;

EID: 84923091774     PISSN: 09696997     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jairtraman.2015.02.008     Document Type: Article

References (46)

1. Andersen P., Petersen N.C. Aprocedure for ranking efficient units in data envelopment analysis. Manag. Sci. 1993, 39:1261-1294.
2. Azadeh A., Amalnick M.S., Ghaderi S.F., Asadzadeh S.M. An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors. Energy Policy 2007, 35:3792-3806.
3. Babikian R., Lukachko S.P., Waitz I.A. The historical fuel efficiency characteristics of regional aircraft from technological, operational, and cost perspectives. J.Air Transp. Manag. 2002, 8(6):389-400.
4. Barros C.P., Peypoch N. An evaluation of European airlines' operational performance. Int. J. Prod. Econ. 2009, 122(2):525-533.
5. Bian Y.W., Xu H. DEA ranking method based upon virtual envelopment frontier and TOPSIS. Syst. Eng. Theory Pract. 2013, 33(2):482-488. (in Chinese).
6. Blomberg J., Henriksson E., Lundmark R. Energy efficiency and policy in Swedish pulp and paper mills: a data envelopment analysis approach. Energy Policy 2012, 42:569-579.
7. Bonneterre J., Peyrat J.P., Beuscart R., Demaille A. Prognostic significance of insulin-like growth factor 1 receptors in human breast cancer. Cancer Res. 1990, 50(21):6931-6935.
8. Boyd G.A., Pang J.X. Estimating the linkage between energy efficiency and productivity. Energy Policy 2000, 28:289-296.
9. Charnes A., Cooper W.W., Rhodes E. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 1978, 2(6):429-444.
10. Charnes A., Cooper W.W., Thrall R.M. Astructure for classifying and characterizing efficiencies and inefficiencies in DEA. J.Prod. Anal. 1991, 2:197-237.
11. Chen Y. Measuring super-efficiency in DEA in the presence of infeasibility. Eur. J. Oper. Res. 2005, 161:545-551.
12. Chiu Y.H., Chen Y.C., Bai X.J. Efficiency and risk in Taiwan banking: SBM super-DEA estimation. Appl. Econ. 2011, 43(5):587-602.
13. Clinch J.P., Healy J.D., King C. Modelling improvements in domestic energy efficiency. Environ. Model. Softw. 2001, 16(1):87-106.
14. COMAC 2014, http://www.comac.cc/xwzx/gsxw/201411/11/t20141111_2075388.shtml.
15. Cui Q., Li Y. The evaluation of transportation energy efficiency: an application of three-stage virtual frontier DEA. Transp. Res. D 2014, 29:1-11.
16. Cui Q., Li Y. An empirical study on the influencing factors of transportation carbon efficiency: evidences from fifteen countries. Appl. Energy 2015, 141:209-217.
17. Cui Q., Kuang H.B., Wu C.Y., Li Y. The changing trend and influencing factors of energy efficiency: the case of nine countries. Energy 2014, 64:1026-1034.
18. Doyle J., Green R. Efficiency and cross efficiency in DEA: derivations, meanings and the uses. J.Oper. Res. Soc. 1994, 45:567-578.
19. 2 emission reduction potentials in the Chinese iron and steel industry. Energy 2013, 50:315-325.
20. Herring H. Energy efficiency-a critical view. Energy 2006, 31:10-20.
21. Hu J.L., Kao C.H. Efficient energy-saving targets for APEC economies. Energy Policy 2007, 35:373-382.
22. International Air Transport Association 2013, http://www.iata.org/Pages/default.aspx.
23. Kaufman N., Palmer K.L. Energy efficiency program evaluations: opportunities for learning and inputs to incentive mechanisms. Energy Effic. 2012, 5:243-268.
24. Lesurtel M., Cherqui D., Laurent A., Tayar C., Fagniez P.L. Laparoscopic versus open left lateral hepatic lobectomy: a case-control study. J.Am. Coll. Surg. 2003, 196(2):236-242.
25. Mandal S.K. Do undesirable output and environmental regulation matter in energy efficiency analysis? Evidence from Indian cement industry. Energy Policy 2010, 38(10):6076-6083.
26. Merkert R., Smith A.S.J., Nash C.A. Benchmarking of train operating firms - a transaction cost efficiency analysis. J.Transp. Plan. Technol. 2010, 33:35-53.
27. Merkert R., Hensher D.A. The impact of strategic management and fleet planning on airline efficiency-A random effects Tobit model based on DEA efficiency scores. Transp. Res. A 2011, 45(7):686-695.
28. Miyoshi C., Merkert R. Changes in carbon efficiency, unit cost of firms over time and the impacts of the fuel price-an empirical analysis of major European airlines. Proceedings of the 14th Air Transport Research Society (ATRS) World Conference, Porto, Portugal 2010.
29. 2 emissions reduction through the use of larger jet aircraft. J.Air Transp. Manag. 2009, 15:151-157.
30. Mukherjee K. Energy use efficiency in the Indian manufacturing sector: an interstate analysis. Energy Policy 2008, 36:662-672.
31. Mukherjee K. Energy use efficiency in US manufacturing: a nonparametric analysis. Energy Econ. 2008, 30:76-97.
32. Önüt S., Soner S. Energy efficiency assessment for the Antalya region hotels in Turkey. Energy Build. 2006, 38:964-971.
33. Patterson M.G. What is energy efficiency? Concepts, indicators and methodological issues. Energy Policy 1996, 24(5):377-390.
34. Ramanathan R. An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa. Energy 2005, 30:2831-2842.
35. Song M.L., Zhang L.L., Liu W., Fisher R. Bootstrap-DEA analysis of BRICS' energy efficiency based on small sample data. Appl. Energy 2013, 112:1049-1055.
36. Tao F., Li L., Xia X.H. Industry efficiency and total factor productivity growth under resources and environmental constraint in China. Sci. World J. 2012, 10.1100/2012/310407.
37. Wang K., Yu S., Zhang W. China's regional energy and environmental efficiency: a DEA window analysis based dynamic evaluation. Math. Comput. Model. 2013, 58(5):1117-1127.
38. 2 emissions nexus: an empirical analysis from China. Energy Policy 2012, 42:248-260.
39. Wei Y.M., Liao H., Fan Y. An empirical analysis of energy efficiency in China's iron and steel sector. Energy 2007, 32:2262-2270.
40. Worrell E., Bernstein L., Roy J., Price L., Harnisch J. Industrial energy efficiency and climate change mitigation. Energy Effic. 2009, 2:109-123.
41. Xue M., Harker P.T. Ranking DMUs with infeasible super-efficiency DEA methods. Manag. Sci. 2002, 48(5):705-710.
42. Yang F., Xia Q., Liang L. DEA cross efficiency evaluation method for competitive and cooperative decision making units. Syst. Eng. Theory Pract. 2011, 31(1):92-98. (in Chinese).
43. Zhou P., Ang B.W. Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy 2008, 38:2911-2916.
44. Zhou P., Ang B.W., Poh K.L. Asurvey of data envelopment analysis in energy and environmental studies. Eur. J. Oper. Res. 2008, 189(1):1-18.
45. Zhu J. Super-efficiency and DEA sensitivity analysis. Eur. J. Oper. Res. 2001, 129:443-455.
46. Zou B., Elke M., Hansen M., Kafle N. Evaluating air carrier fuel efficiency in the US airline industry. Transp. Res. A 2014, 59:306-330.