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Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants

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  • Kottas, Angelos T.
  • Madas, Michael A.

Abstract

The establishment of alliance groups during the end of 1990s has marked the beginning of an era that is characterized by increased consolidation among Full-Service Network Carriers (FSNCs). In the context of increased competition, membership in a global airline alliance group has served as the main avenue for FSNCs to maintain or increase market share and attain economic viability. Although previous literature has repeatedly stressed the enhancement of operational efficiency as a major incentive for airline alliance membership, existing research related to the assessment of comparative efficiency between allied and non-allied airlines and among alliance groups is fairly scarce. In the current paper, an integrated methodological framework employing Data Envelopment Analysis (DEA) with super-efficiency and intertemporal approach is implemented to assess the effect of alliance group membership on 30 major international airlines regarding period 2012–2016. Primary findings suggest that alliance group membership is not associated with superior airline efficiency. In addition, airlines with high freight traffic revenue share are found to be more efficient than airlines demonstrating lower freight traffic revenue share. Finally, a statistically significant superior efficiency of Asian and European air carriers over American air carriers is substantiated.

Suggested Citation

  • Kottas, Angelos T. & Madas, Michael A., 2018. "Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 1-17.
    • Handle: RePEc:eee:jaitra:v:70:y:2018:i:c:p:1-17
    DOI: 10.1016/j.jairtraman.2018.04.014
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    as
    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Seufert, Juergen Heinz & Arjomandi, Amir & Dakpo, K. Hervé, 2017. "Evaluating airline operational performance: A Luenberger-Hicks-Moorsteen productivity indicator," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 52-68.
    3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    4. Choi, Kanghwa, 2017. "Multi-period efficiency and productivity changes in US domestic airlines," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 18-25.
    5. Joe Zhu, 2014. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, edition 3, number 978-3-319-06647-9, December.
    6. Brueckner, Jan K. & Pels, Eric, 2005. "European airline mergers, alliance consolidation, and consumer welfare," Journal of Air Transport Management, Elsevier, vol. 11(1), pages 27-41.
    7. Dennis, Nigel, 2005. "Industry consolidation and future airline network structures in Europe," Journal of Air Transport Management, Elsevier, vol. 11(3), pages 175-183.
    8. Marcel Timmer & Bart Los, 2005. "Localized Innovation and Productivity Growth in Asia: An Intertemporal DEA Approach," Journal of Productivity Analysis, Springer, vol. 23(1), pages 47-64, January.
    9. Min, Hokey & Joo, Seong-Jong, 2016. "A comparative performance analysis of airline strategic alliances using data envelopment analysis," Journal of Air Transport Management, Elsevier, vol. 52(C), pages 99-110.
    10. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    11. Oum, Tae Hoon & Park, Jong-Hun, 1997. "Airline alliances: current status, policy issues, and future directions," Journal of Air Transport Management, Elsevier, vol. 3(3), pages 133-144.
    12. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    13. Mark R. Greer, 2016. "Airline Mergers in the United States since 2005: What Impact Have They Had on Airline Efficiency?," Advances in Airline Economics, in: Airline Efficiency, volume 5, pages 161-195, Emerald Group Publishing Limited.
    14. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    15. Budd, Lucy & Ison, Stephen, 2017. "The role of dedicated freighter aircraft in the provision of global airfreight services," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 34-40.
    16. Saranga, Haritha & Nagpal, Rajiv, 2016. "Drivers of operational efficiency and its impact on market performance in the Indian Airline industry," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 165-176.
    17. Dennis, Nigel, 2000. "Scheduling issues and network strategies for international airline alliances," Journal of Air Transport Management, Elsevier, vol. 6(2), pages 75-85.
    18. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    19. Barros, Carlos Pestana & Peypoch, Nicolas, 2009. "An evaluation of European airlines' operational performance," International Journal of Production Economics, Elsevier, vol. 122(2), pages 525-533, December.
    20. Joe Sarkis, 2007. "Preparing Your Data for DEA," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 305-320, Springer.
    21. Cui, Qiang & Li, Ye, 2015. "Evaluating energy efficiency for airlines: An application of VFB-DEA," Journal of Air Transport Management, Elsevier, vol. 44, pages 34-41.
    22. Rico Merkert & James Pearson, 2015. "A Non-parametric Efficiency Measure Incorporating Perceived Airline Service Levels and Profitability," Journal of Transport Economics and Policy, University of Bath, vol. 49(2), pages 261-275, April.
    23. Arjomandi, Amir & Seufert, Juergen Heinz, 2014. "An evaluation of the world's major airlines' technical and environmental performance," Economic Modelling, Elsevier, vol. 41(C), pages 133-144.
    24. Wing Chow, Clement Kong, 2010. "Measuring the productivity changes of Chinese airlines: The impact of the entries of non-state-owned carriers," Journal of Air Transport Management, Elsevier, vol. 16(6), pages 320-324.
    25. Brueckner, Jan K., 2001. "The economics of international codesharing: an analysis of airline alliances," International Journal of Industrial Organization, Elsevier, vol. 19(10), pages 1475-1498, December.
    26. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    27. Scheraga, Carl A., 2004. "Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(5), pages 383-404, June.
    28. Good, David H. & Roller, Lars-Hendrik & Sickles, Robin C., 1995. "Airline efficiency differences between Europe and the US: Implications for the pace of EC integration and domestic regulation," European Journal of Operational Research, Elsevier, vol. 80(3), pages 508-518, February.
    29. Tarja Joro & Pekka J. Korhonen, 2015. "Extension of Data Envelopment Analysis with Preference Information," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4899-7528-7, December.
    30. Francis, Graham & Humphreys, Ian & Fry, Jackie, 2005. "The nature and prevalence of the use of performance measurement techniques by airlines," Journal of Air Transport Management, Elsevier, vol. 11(4), pages 207-217.
    31. Cao, Qian & Lv, Jinfeng & Zhang, Jun, 2015. "Productivity efficiency analysis of the airlines in China after deregulation," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 135-140.
    32. Greer, Mark R., 2008. "Nothing focuses the mind on productivity quite like the fear of liquidation: Changes in airline productivity in the United States, 2000-2004," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 414-426, February.
    33. Joseph C. Paradi & Zijiang Yang & Haiyan Zhu, 2011. "Assessing Bank and Bank Branch Performance," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 315-361, Springer.
    34. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    35. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2015. "Evaluating airline efficiency: An application of Virtual Frontier Network SBM," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 1-17.
    36. Tavassoli, Mohammad & Faramarzi, Gholam Reza & Farzipoor Saen, Reza, 2014. "Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 146-153.
    37. A. George Assaf & Alexander Josiassen, 2011. "The operational performance of UK airlines: 2002‐2007," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 38(1), pages 5-16, January.
    38. Barbot, Cristina & Costa, Ã lvaro & Sochirca, Elena, 2008. "Airlines performance in the new market context: A comparative productivity and efficiency analysis," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 270-274.
    39. Merkert, Rico & Morrell, Peter S., 2012. "Mergers and acquisitions in aviation – Management and economic perspectives on the size of airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 853-862.
    40. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures using a Dynamic Epsilon-Based Measure model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 121-134.
    41. Tarja Joro & Pekka J. Korhonen, 2015. "Value Efficiency Analysis," International Series in Operations Research & Management Science, in: Extension of Data Envelopment Analysis with Preference Information, edition 127, chapter 0, pages 95-109, Springer.
    42. Tarja Joro & Pekka J. Korhonen, 2015. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Extension of Data Envelopment Analysis with Preference Information, edition 127, chapter 0, pages 15-26, Springer.
    43. Bhadra, Dipasis, 2009. "Race to the bottom or swimming upstream: Performance analysis of US airlines," Journal of Air Transport Management, Elsevier, vol. 15(5), pages 227-235.
    44. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    45. Ming-Miin Yu, 2012. "Performance assessment of transport services with the ERM-NDEA model: evidence from a domestic airline in Taiwan," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(7), pages 697-714, July.
    46. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    47. Lee, Boon L. & Worthington, Andrew C., 2014. "Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 15-20.
    48. Sebastián Lozano & Ester Gutiérrez, 2014. "A slacks-based network DEA efficiency analysis of European airlines," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(7), pages 623-637, October.
    49. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 130-143.
    50. Boon L. Lee & Andrew C. Worthington, 2010. "The Relative Efficiency of International, Domestic, and Budget Airlines: Nonparametric Evidence," Discussion Papers in Economics economics:201002, Griffith University, Department of Accounting, Finance and Economics.
    51. Mette Asmild & Joseph Paradi & Vanita Aggarwall & Claire Schaffnit, 2004. "Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry," Journal of Productivity Analysis, Springer, vol. 21(1), pages 67-89, January.
    52. Chiou, Yu-Chiun & Chen, Yen-Heng, 2006. "Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(2), pages 116-127, March.
    53. Oum, Tae Hoon & Zhang, Anming, 2001. "Key aspects of global strategic alliances and the impacts on the future of Canadian airline industry," Journal of Air Transport Management, Elsevier, vol. 7(5), pages 287-301.
    54. Sengupta, Jati K., 1999. "A dynamic efficiency model using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 62(3), pages 209-218, September.
    55. Wang, Wei-Kang & Lu, Wen-Min & Tsai, Chia-Jen, 2011. "The relationship between airline performance and corporate governance amongst US Listed companies," Journal of Air Transport Management, Elsevier, vol. 17(2), pages 148-152.
    56. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    57. Barros, Carlos Pestana & Couto, Eduardo, 2013. "Productivity analysis of European airlines, 2000–2011," Journal of Air Transport Management, Elsevier, vol. 31(C), pages 11-13.
    58. Button, Kenneth, 2009. "The impact of US–EU “Open Skies†agreement on airline market structures and airline networks," Journal of Air Transport Management, Elsevier, vol. 15(2), pages 59-71.
    59. Merkert, Rico & Williams, George, 2013. "Determinants of European PSO airline efficiency – Evidence from a semi-parametric approach," Journal of Air Transport Management, Elsevier, vol. 29(C), pages 11-16.
    60. Merkert, Rico & Hensher, David A., 2011. "The impact of strategic management and fleet planning on airline efficiency - A random effects Tobit model based on DEA efficiency scores," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 686-695, August.
    61. Coto-Millán, Pablo & Inglada, Vicente & Fernández, Xose Luis & Inglada-Pérez, Lucía & Pesquera, Miguel Ángel, 2016. "The “effect procargo” on technical and scale efficiency at airports: The case of Spanish airports (2009–2011)," Utilities Policy, Elsevier, vol. 39(C), pages 29-35.
    62. Barros, Carlos P. & Liang, Qi Bin & Peypoch, Nicolas, 2013. "The technical efficiency of US Airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 139-148.
    63. Pires, Heloisa Márcia & Fernandes, Elton, 2012. "Malmquist financial efficiency analysis for airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 1049-1055.
    64. Patrick L. Brockett & Boaz Golany, 1996. "Using Rank Statistics for Determining Programmatic Efficiency Differences in Data Envelopment Analysis," Management Science, INFORMS, vol. 42(3), pages 466-472, March.
    65. Omrani, Hashem & Soltanzadeh, Elham, 2016. "Dynamic DEA models with network structure: An application for Iranian airlines," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 52-61.
    66. Mallikarjun, Sreekanth, 2015. "Efficiency of US airlines: A strategic operating model," Journal of Air Transport Management, Elsevier, vol. 43(C), pages 46-56.
    67. Lu, Wen-Min & Wang, Wei-Kang & Hung, Shiu-Wan & Lu, En-Tzu, 2012. "The effects of corporate governance on airline performance: Production and marketing efficiency perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 529-544.
    68. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, June.
    69. Yu, Ming-Miin & Chen, Li-Hsueh & Chiang, Hui, 2017. "The effects of alliances and size on airlines’ dynamic operational performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 197-214.
    70. Gillen, David, 2005. "The Evolution of Networks with Changes in Industry Structure and Strategy: Connectivity, Hub-and-Spoke and Alliances," Research in Transportation Economics, Elsevier, vol. 13(1), pages 49-73, January.
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