IDEAS home Printed from https://ideas.repec.org/a/eee/jaitra/v82y2020ics0969699719302509.html
   My bibliography  Save this article

How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis

Author

Listed:
  • Aydın, Umut
  • Karadayi, Melis Almula
  • Ãœlengin, Füsun

Abstract

In this empirical study, a five-stage methodology is used to examine the efficiency of 45 worldwide known airline companies from the financial, operation and marketing perspectives. Initially, the superefficient data envelopment model is run with inputs and outputs that are selected based on the literature review. However, because 21 out of 45 airline companies are found to be efficient based on this analysis, a stepwise regression-based mechanism is applied to four reduced models – one for each output variable – for better discrimination. The outputs are, namely, net profit margin (financial output), passengers carried, on-time departure performance (operational outputs), and customer satisfaction (marketing output). In this way, the significant input variables are found for each reduced model. In the third stage, in order to provide even more discrimination, social network-based eigenvector centrality values are used as the weights of the superefficiency scores, and the strengths and weaknesses of efficient airlines for each output are specified in terms of their related significant inputs. The results show that, when net profit margin is taken as an output, Vietnam Airlines has the top weighted superefficiency value and excels in terms of available seat kilometers and liquidity, but it should improve its debt level. Although Norwegian Airlines has the highest efficiency with respect to debt level, it is not the best role model because its eigenvector centrality value is relatively low. However, Norwegian airlines also has the highest weighted superefficiency and acts as a role model in terms of on-time departures with respect to this output. Its main strength is liquidity, and it has no significant weaknesses. On the other hand, in terms of overall satisfaction and passengers carried, Vietnam Airlines and Thai Airways are the leaders, respectively. Vietnam Airlines is the only superefficient company with respect to overall satisfaction, while the basic strengths of Thai Airways in terms of passengers carried are its employee and fleet, and it has no significant weakness. A final aggregation of the results is made by making pairwise comparisons of the relative importance of four outputs for 7 experts selected from different departments of airline companies. According to the results, Net Profit Margin has the highest priority, followed by On-time Departure and Overall Customer Satisfaction, while passengers carried has the lowest importance. Based on these relative priorities, it can be said that Vietnam Airlines can be accepted as the top performing airline company, followed by Norwegian Airlines.

Suggested Citation

  • Aydın, Umut & Karadayi, Melis Almula & Ãœlengin, Füsun, 2020. "How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis," Journal of Air Transport Management, Elsevier, vol. 82(C).
  • Handle: RePEc:eee:jaitra:v:82:y:2020:i:c:s0969699719302509
    DOI: 10.1016/j.jairtraman.2019.101725
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969699719302509
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jairtraman.2019.101725?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simon de Blas, Clara & Simon Martin, Jose & Gomez Gonzalez, Daniel, 2018. "Combined social networks and data envelopment analysis for ranking," European Journal of Operational Research, Elsevier, vol. 266(3), pages 990-999.
    2. 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.
    3. B. Hollingsworth & P. Smith, 2003. "Use of ratios in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 10(11), pages 733-735.
    4. Ha, Hun-Koo & Wan, Yulai & Yoshida, Yuichiro & Zhang, Anming, 2013. "Airline market structure and airport efficiency: Evidence from major Northeast Asian airports," Journal of Air Transport Management, Elsevier, vol. 33(C), pages 32-42.
    5. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    6. 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.
    7. John Ruggiero, 2005. "Impact Assessment Of Input Omission On Dea," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 359-368.
    8. Zhang, Qiong & Yang, Hangjun & Wang, Qiang & Zhang, Anming, 2014. "Market power and its determinants in the Chinese airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 1-13.
    9. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.
    10. 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.
    11. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    12. Gudiel Pineda, Pedro Jose & Liou, James J.H. & Hsu, Chao-Che & Chuang, Yen-Ching, 2018. "An integrated MCDM model for improving airline operational and financial performance," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 103-117.
    13. 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.
    14. Chow, Clement Kong Wing, 2014. "Customer satisfaction and service quality in the Chinese airline industry," Journal of Air Transport Management, Elsevier, vol. 35(C), pages 102-107.
    15. 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.
    16. Wagner, Janet M. & Shimshak, Daniel G., 2007. "Stepwise selection of variables in data envelopment analysis: Procedures and managerial perspectives," European Journal of Operational Research, Elsevier, vol. 180(1), pages 57-67, July.
    17. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    18. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    19. Kanghwa Choi & DonHee Lee & David Olson, 2015. "Service quality and productivity in the U.S. airline industry: a service quality-adjusted DEA model," Service Business, Springer;Pan-Pacific Business Association, vol. 9(1), pages 137-160, March.
    20. Wen-Chih Chen & Andrew Johnson, 2010. "The dynamics of performance space of Major League Baseball pitchers 1871–2006," Annals of Operations Research, Springer, vol. 181(1), pages 287-302, December.
    21. Feng, Cheng-Min & Wang, Rong-Tsu, 2000. "Performance evaluation for airlines including the consideration of financial ratios," Journal of Air Transport Management, Elsevier, vol. 6(3), pages 133-142.
    22. Põldaru, Reet & Roots, Jüri, 2014. "A PCA–DEA approach to measure the quality of life in Estonian counties," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 65-73.
    23. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    24. Barros, Carlos Pestana & Wanke, Peter, 2015. "An analysis of African airlines efficiency with two-stage TOPSIS and neural networks," Journal of Air Transport Management, Elsevier, vol. 44, pages 90-102.
    25. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    26. Wanke, Peter & Pestana Barros, Carlos & Chen, Zhongfei, 2015. "An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models," International Journal of Production Economics, Elsevier, vol. 169(C), pages 110-126.
    27. Li, Ye & Cui, Qiang, 2017. "Carbon neutral growth from 2020 strategy and airline environmental inefficiency: A Network Range Adjusted Environmental Data Envelopment Analysis," Applied Energy, Elsevier, vol. 199(C), pages 13-24.
    28. Stepanyan Armen, 2013. "Performance Assessment Of Major U.S. Airlines Via Cash Flow Ratios," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 398-408, December.
    29. 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.
    30. 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.
    31. 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.
    32. Çavdar, Ahmet Birol & Ferhatosmanoğlu, Nilgün, 2018. "Airline customer lifetime value estimation using data analytics supported by social network information," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 19-33.
    33. Ofrit Lesser & Lihi Naamani-Dery & Meir Kalech & Yuval Elovici, 2017. "Group Decision Support for Leisure Activities Using Voting and Social Networks," Group Decision and Negotiation, Springer, vol. 26(3), pages 473-494, May.
    34. Seyed Ali Rakhshan, 2017. "Efficiency ranking of decision making units in data envelopment analysis by using TOPSIS-DEA method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 906-918, August.
    35. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    36. 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.
    37. Oum, Tae Hoon & Fu, Xiaowen & Yu, Chunyan, 2005. "New evidences on airline efficiency and yields: a comparative analysis of major North American air carriers and its implications," Transport Policy, Elsevier, vol. 12(2), pages 153-164, March.
    38. Wanke, Peter & Barros, C.P. & Nwaogbe, Obioma R., 2016. "Assessing productive efficiency in Nigerian airports using Fuzzy-DEA," Transport Policy, Elsevier, vol. 49(C), pages 9-19.
    39. 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.
    40. Retzlaff-Roberts, Donna & Chang, Cyril F. & Rubin, Rose M., 2004. "Technical efficiency in the use of health care resources: a comparison of OECD countries," Health Policy, Elsevier, vol. 69(1), pages 55-72, July.
    41. 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.
    42. Chen, Zhongfei & Wanke, Peter & Antunes, Jorge Junio Moreira & Zhang, Ning, 2017. "Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model," Energy Economics, Elsevier, vol. 68(C), pages 89-108.
    43. Mallikarjun, Sreekanth, 2015. "Efficiency of US airlines: A strategic operating model," Journal of Air Transport Management, Elsevier, vol. 43(C), pages 46-56.
    44. 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.
    45. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kaya, Gizem & Aydın, Umut & Karadayı, Melis Almula & Ülengin, Füsun & Ülengin, Burç & İçken, Ayhan, 2022. "Integrated methodology for evaluating the efficiency of airports: A case study in Turkey," Transport Policy, Elsevier, vol. 127(C), pages 31-47.
    2. Gobbo, Simone Cristina de Oliveira & Mariano, Enzo Barberio & Gobbo Jr., José Alcides, 2021. "Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications," Omega, Elsevier, vol. 103(C).
    3. Kaya, Gizem & Aydın, Umut & Ülengin, Burç & Karadayı, Melis Almula & Ülengin, Füsun, 2023. "How do airlines survive? An integrated efficiency analysis on the survival of airlines," Journal of Air Transport Management, Elsevier, vol. 107(C).
    4. Teeris Thepchalerm, 2021. "Impacts of COVID-19 on Airline Business: An Overview," GATR Journals jber202, Global Academy of Training and Research (GATR) Enterprise.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaya, Gizem & Aydın, Umut & Ülengin, Burç & Karadayı, Melis Almula & Ülengin, Füsun, 2023. "How do airlines survive? An integrated efficiency analysis on the survival of airlines," Journal of Air Transport Management, Elsevier, vol. 107(C).
    2. 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.
    3. Chen, Zhongfei & Tzeremes, Panayiotis & Tzeremes, Nickolaos G., 2018. "Convergence in the Chinese airline industry: A Malmquist productivity analysis," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 77-86.
    4. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2016. "Has airline efficiency affected by the inclusion of aviation into European Union Emission Trading Scheme? Evidences from 22 airlines during 2008–2012," Energy, Elsevier, vol. 96(C), pages 8-22.
    5. Yakath Ali, Nurul Syuhadah & Yu, Chunyan & See, Kok Fong, 2021. "Four decades of airline productivity and efficiency studies: A review and bibliometric analysis," Journal of Air Transport Management, Elsevier, vol. 96(C).
    6. Kaya, Gizem & Aydın, Umut & Karadayı, Melis Almula & Ülengin, Füsun & Ülengin, Burç & İçken, Ayhan, 2022. "Integrated methodology for evaluating the efficiency of airports: A case study in Turkey," Transport Policy, Elsevier, vol. 127(C), pages 31-47.
    7. 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.
    8. Cui, Qiang & Li, Ye & Yu, Chen-lu & Wei, Yi-Ming, 2016. "Evaluating energy efficiency for airlines: An application of Virtual Frontier Dynamic Slacks Based Measure," Energy, Elsevier, vol. 113(C), pages 1231-1240.
    9. Mahmut BAKIR & Şahap AKAN & Kasım KIRACI & Darjan KARABASEVIC & Dragisa STANUJKIC & Gabrijela POPOVIC, 2020. "Multiple-Criteria Approach of the Operational Performance Evaluation in the Airline Industry: Evidence from the Emerging Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 149-172, July.
    10. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    11. Ye Li & Qiang Cui, 2017. "Airline energy efficiency measures using the Virtual Frontier Network RAM with weak disposability," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(4), pages 479-504, May.
    12. 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.
    13. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    14. 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.
    15. Tanrıverdi, Gökhan & Merkert, Rico & Karamaşa, Çağlar & Asker, Veysi, 2023. "Using multi-criteria performance measurement models to evaluate the financial, operational and environmental sustainability of airlines," Journal of Air Transport Management, Elsevier, vol. 112(C).
    16. Chen, Zhongfei & Wanke, Peter & Antunes, Jorge Junio Moreira & Zhang, Ning, 2017. "Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model," Energy Economics, Elsevier, vol. 68(C), pages 89-108.
    17. Wanke, Peter & Barros, C.P., 2016. "Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 93-103.
    18. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    19. Huang, Fei & Zhou, Dequn & Hu, Jin-Li & Wang, Qunwei, 2020. "Integrated airline productivity performance evaluation with CO2 emissions and flight delays," Journal of Air Transport Management, Elsevier, vol. 84(C).
    20. Liu, Dan & Zhang, Jiahuang & Yu, Ming-Miin, 2023. "Decomposing airline profit inefficiency in NDEA through the non-competitive Nerlovian profit inefficiency model," Journal of Air Transport Management, Elsevier, vol. 107(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jaitra:v:82:y:2020:i:c:s0969699719302509. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-air-transport-management/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.