A longitudinal Perspective on Efficiency of Airlines in Europe and the U.S
Article Sidebar
Main Article Content
Abstract
The aviation industries in Europe and the US have been well-established since a very early age and have attracted great attention from both industry practitioners and academics. To derive a different perspective on the efficiency levels of airlines operating in the two matured markets, we adopted dynamic data envelopment analysis (DEA). Using the data of the period 2014 – 2016 of 7 European airlines and 9 US airlines that are publicly traded, the study offers an overall picture of airlines' efficiency in the two regions. Notably, the resource flow between the consecutive periods is incorporated into the measure to yield a longitudinal perspective on airlines' efficiency. The study reveals the two major findings. First, most publicly traded airlines in Europe and the US are efficient, except for Hawaiian airline headquartered in the US. Second, Hawaiian airline's inefficiency is majorly contributed by the overuse of the number of employees, consumed fuel, and the deficit of revenue seat-miles in 2014 and 2015. To improve the efficiency level, Hawaiian airlines could consider increasing employee productivity, using more fuel-efficient aircraft, and implementing new marketing strategies to boost sales.
Downloads
Article Details
Copyright (c) 2021 Minh-Anh Nguyen Thi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Alperovych, Y., Amess, K., & Wright, M. (2013). Private equity firm experience and buyout vendor source: What is their impact on efficiency?. European Journal of Operational Research, 228(3), 601-611. https://doi.org/10.1016/j.ejor.2013.01.019 DOI: https://doi.org/10.1016/j.ejor.2013.01.019
Arjomandi, A., Dakpo, K. H., & Seufert, J. H. (2018). Have Asian airlines caught up with European Airlines? A by-production efficiency analysis. Transportation Research Part A: Policy and Practice, 116, 389-403. https://doi.org/10.1016/j.tra.2018.06.031 DOI: https://doi.org/10.1016/j.tra.2018.06.031
Assaf, A. G., & Josiassen, A. (2012). European vs. US airlines: Performance comparison in a dynamic market. Tourism Management, 33(2), 317-326. https://doi.org/10.1016/j.tourman.2011.03.012 DOI: https://doi.org/10.1016/j.tourman.2011.03.012
Barros, C. P., & Couto, E. (2013). Productivity analysis of European airlines, 2000–2011. Journal of Air Transport Management, 31, 11-13. https://doi.org/10.1016/j.jairtraman.2012.10.006 DOI: https://doi.org/10.1016/j.jairtraman.2012.10.006
Barros, C. P., & Wanke, P. (2015). An analysis of African airlines efficiency with two-stage TOPSIS and neural networks. Journal of Air Transport Management, 44, 90-102. https://doi.org/10.1016/j.jairtraman.2015.03.002 DOI: https://doi.org/10.1016/j.jairtraman.2015.03.002
Cao, Q., Lv, J., & Zhang, J. (2015). Productivity efficiency analysis of the airlines in China after deregulation. Journal of Air Transport Management, 42, 135-140. https://doi.org/10.1016/j.jairtraman.2014.09.009 DOI: https://doi.org/10.1016/j.jairtraman.2014.09.009
Chang, Y. C., & Yu, M. M. (2014). Measuring production and consumption efficiencies using the slack‐based measure network data envelopment analysis approach: the case of low‐cost carriers. Journal of advanced transportation, 48(1), 15-31. https://doi.org/10.1002/atr.198 DOI: https://doi.org/10.1002/atr.198
Chow, C. K. W. (2010). Measuring the productivity changes of Chinese airlines: the impact of the entries of non-state-owned carriers. Journal of Air Transport Management, 16(6), 320-324. https://doi.org/10.1016/j.jairtraman.2010.04.001 DOI: https://doi.org/10.1016/j.jairtraman.2010.04.001
Cui, Q., & Li, Y. (2017). Airline efficiency measures using a Dynamic Epsilon-Based Measure model. Transportation Research Part A: Policy and Practice, 100, 121-134. https://doi.org/10.1016/j.tra.2017.04.013 DOI: https://doi.org/10.1016/j.tra.2017.04.013
Cui, Q., Li, Y., & Lin, J. L. (2018). Pollution abatement costs change decomposition for airlines: An analysis from a dynamic perspective. Transportation Research Part A: Policy and Practice, 111, 96-107. https://doi.org/10.1016/j.tra.2018.03.014 DOI: https://doi.org/10.1016/j.tra.2018.03.014
Emrouznejad, A., & Yang, G. L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4-8. https://doi.org/10.1016/j.seps.2017.01.008 DOI: https://doi.org/10.1016/j.seps.2017.01.008
Good, D. H., Nadiri, M. I., Röller, L. H., & Sickles, R. C. (1993). Efficiency and productivity growth comparisons of European and US air carriers: a first look at the data. Journal of Productivity analysis, 4(1-2), 115-125. https://doi.org/10.1007/978-94-011-2200-9_8 DOI: https://doi.org/10.1007/978-94-011-2200-9_8
Good, D. H., Röller, L. H., & Sickles, R. 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, 80(3), 508-518. https://doi.org/10.1016/0377-2217(94)00134-X DOI: https://doi.org/10.1016/0377-2217(94)00134-X
Gramani, M. C. N. (2012). Efficiency decomposition approach: A cross-country airline analysis. Expert Systems with Applications, 39(5), 5815-5819. https://doi.org/10.1016/j.eswa.2011.11.086 DOI: https://doi.org/10.1016/j.eswa.2011.11.086
Hung, S. W., He, D. S., & Lu, W. M. (2014). Evaluating the dynamic performances of business groups from the carry-over perspective: A case study of Taiwan׳ s semiconductor industry. Omega, 46, 1-10. https://doi.org/10.1016/j.omega.2014.01.003 DOI: https://doi.org/10.1016/j.omega.2014.01.003
Kottas, A. T., & Madas, M. 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, 70, 1-17. https://doi.org/10.1016/j.jairtraman.2018.04.014 DOI: https://doi.org/10.1016/j.jairtraman.2018.04.014
Lampe, H. W., & Hilgers, D. (2015). Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA. European Journal of Operational Research, 240(1), 1-21. https://doi.org/10.1016/j.ejor.2014.04.041 DOI: https://doi.org/10.1016/j.ejor.2014.04.041
Liu, J., Zhu, J., & Zhang, J. (2018). A DEA-based approach for competitive environment analysis in global operations strategies. International Journal of Production Economics, 203, 110-123. https://doi.org/10.1016/j.ijpe.2018.05.029 DOI: https://doi.org/10.1016/j.ijpe.2018.05.029
Lu, W. M., Wang, W. K., & Kweh, Q. L. (2014). Intellectual capital and performance in the Chinese life insurance industry. Omega, 42(1), 65-74. https://doi.org/10.1016/j.omega.2013.03.002 DOI: https://doi.org/10.1016/j.omega.2013.03.002
Merkert, R., & Pearson, J. (2015). A non-parametric efficiency measure incorporating perceived airline service levels and profitability. Journal of Transport Economics and Policy (JTEP), 49(2), 261-275. https://www.jstor.org/stable/jtranseconpoli.49.2.0261
Merkert, R., & Williams, G. (2013). Determinants of European PSO airline efficiency–Evidence from a semi-parametric approach. Journal of Air Transport Management, 29, 11-16. https://doi.org/10.1016/j.jairtraman.2012.12.002 DOI: https://doi.org/10.1016/j.jairtraman.2012.12.002
Morrell, P. S., & Taneja, N. K. (1979). Airline productivity redefined: an analysis of US and European carriers. Transportation, 8(1), 37-49. https://doi.org/10.1007/BF00149850 DOI: https://doi.org/10.1007/BF00149850
Omrani, H., & Soltanzadeh, E. (2016). Dynamic DEA models with network structure: An application for Iranian airlines. Journal of Air Transport Management, 57, 52-61. https://doi.org/10.1016/j.jairtraman.2016.07.014 DOI: https://doi.org/10.1016/j.jairtraman.2016.07.014
Saranga, H., & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165-176. https://doi.org/10.1016/j.jairtraman.2016.03.001 DOI: https://doi.org/10.1016/j.jairtraman.2016.03.001
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509. https://doi.org/10.1016/S0377-2217(99)00407-5 DOI: https://doi.org/10.1016/S0377-2217(99)00407-5
Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145-156. https://doi.org/10.1016/j.omega.2009.07.003 DOI: https://doi.org/10.1016/j.omega.2009.07.003
Tsionas, M. G., Chen, Z., & Wanke, P. (2017). A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines. Transportation Research Part A: Policy and Practice, 101, 1-10. https://doi.org/10.1016/j.tra.2017.05.003 DOI: https://doi.org/10.1016/j.tra.2017.05.003
Yu, M. M., Chang, Y. C., & Chen, L. H. (2016). Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers. Journal of Air Transport Management, 53, 186-198. https://doi.org/10.1016/j.jairtraman.2016.03.005 DOI: https://doi.org/10.1016/j.jairtraman.2016.03.005
Yu, M. M., Chen, L. H., & Chiang, H. (2017). The effects of alliances and size on airlines’ dynamic operational performance. Transportation Research Part A: Policy and Practice, 106, 197-214. https://doi.org/10.1016/j.tra.2017.09.015 DOI: https://doi.org/10.1016/j.tra.2017.09.015