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Financial Performance Analysis Using the Merec-Based Cobra Method: An Application to Traditional and Low-Cost Airlines

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  • Veysi Asker

Abstract

The aim of this study is to examine the impact of the COVID-19 pandemic on the financial performance of traditional and low-cost airlines. In this context, the financial performance of 32 traditional and 14 low-cost airlines operating in different regions of the world was analysed using the Merec-based Cobra method for the before and during COVID-19 pandemic period (2018–2021). First, the financial ratios of the airlines were weighted using the Merec method, then the financial performance ranking of the airlines was conducted using the Cobra method. According to the results of the Cobra method, Ryanair (FR) was found to have the best financial performance in 2018 and 2020. Meanwhile, Allegiant Travel (G4) led the way in 2019, and Thai Airways (TG) came out on top in 2021. According to the analysis results, low-cost airlines such as Southwest Airlines (WN), Wizz Air (W6), Allegiant Air Travel (G4), and Ryanair (FR) showed better performance than a significant portion of traditional airlines in the period before the COVID- 19 pandemic. In contrast, during the COVID-19 pandemic, low-cost airlines such as Spring Airlines (9C), Air Arabia (G9), Cebu Air (5J), Easyjet (U2), and Jetblue Airways (B6) demonstrated worse performance than a significant portion of traditional airlines.

Suggested Citation

  • Veysi Asker, 2024. "Financial Performance Analysis Using the Merec-Based Cobra Method: An Application to Traditional and Low-Cost Airlines," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 35-52.
    • Handle: RePEc:sgh:gosnar:y:2024:i:2:p:35-52
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    1. Abate, Megersa & Christidis, Panayotis & Purwanto, Alloysius Joko, 2020. "Government support to airlines in the aftermath of the COVID-19 pandemic," Journal of Air Transport Management, Elsevier, vol. 89(C).
    2. 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.
    3. 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.
    4. Mladen Krstić & Giulio Paolo Agnusdei & Pier Paolo Miglietta & Snežana Tadić & Violeta Roso, 2022. "Applicability of Industry 4.0 Technologies in the Reverse Logistics: A Circular Economy Approach Based on COmprehensive Distance Based RAnking (COBRA) Method," Sustainability, MDPI, vol. 14(9), pages 1-30, May.
    5. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    6. Hsu, Chao-Che & Liou, James J.H., 2013. "An outsourcing provider decision model for the airline industry," Journal of Air Transport Management, Elsevier, vol. 28(C), pages 40-46.
    7. 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.
    8. Czerny, Achim I. & Fu, Xiaowen & Lei, Zheng & Oum, Tae H., 2021. "Post pandemic aviation market recovery: Experience and lessons from China," Journal of Air Transport Management, Elsevier, vol. 90(C).
    9. Ljubomir Gigović & Dragan Pamučar & Zoran Bajić & Milić Milićević, 2016. "The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots," Sustainability, MDPI, vol. 8(4), pages 1-30, April.
    10. Yalcin, Ahmet Selcuk & Kilic, Huseyin Selcuk & Delen, Dursun, 2022. "The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    11. 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.
    12. Heydari, Chiman & Omrani, Hashem & Taghizadeh, Rahim, 2020. "A fully fuzzy network DEA-Range Adjusted Measure model for evaluating airlines efficiency: A case of Iran," Journal of Air Transport Management, Elsevier, vol. 89(C).
    13. 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.
    14. Nguyen, Minh-Anh Thi & Yu, Ming-Miin & Lirn, Taih-Cherng, 2022. "Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach," Transport Policy, Elsevier, vol. 117(C), pages 108-117.
    15. 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.
    16. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    17. 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.
    18. Albers, Sascha & Rundshagen, Volker, 2020. "European airlines′ strategic responses to the COVID-19 pandemic (January-May, 2020)," Journal of Air Transport Management, Elsevier, vol. 87(C).
    19. Wang, Wei-Kang & Lin, Fengyi & Ting, Irene Wei Kiong & Kweh, Qian Long & Lu, Wen-Min & Chiu, Tzu-Yu, 2017. "Does asset-light strategy contribute to the dynamic efficiency of global airlines?," Journal of Air Transport Management, Elsevier, vol. 62(C), pages 99-108.
    20. 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.
    21. 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.
    22. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    23. 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).
    24. Veysi ASKER & Temel Caner USTAÖMER, 2022. "Financial Efficiency Analysis the Malmquist TFP Method An Application on Star Alliance Member Airlines," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, vol. 6(2), pages 39-57, December.
    25. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Atems, Bebonchu & Yimga, Jules, 2021. "Quantifying the impact of the COVID-19 pandemic on US airline stock prices," Journal of Air Transport Management, Elsevier, vol. 97(C).
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    More about this item

    Keywords

    COVID-19 pandemic; financial performance; Merec method; Cobra method;
    All these keywords.

    JEL classification:

    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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