Journals / Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2026 / Volume: 12 Issue: 1

Financial and Operational Performance Analysis Using LOPCOW Based MARCOS Method: A Case Study of the Asian Airline Market

Veysi Asker(DİCLE ÜNİVERSİTESİ)0000-0002-8969-7822
Zehra Kilinç(SÜLEYMAN DEMİREL ÜNİVERSİTESİ)0000-0002-8442-7882
Pages
—
Publication Date
2025-03-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The purpose of the study is to view how companies operating in the Asian airline market responded to the crisis caused by the COVID-19 pandemic.
📊
Key Findings & Data:Additionally, it aims to compare the financial and operational performance of airlines in the Asian airline market before, during, and after the COVID-19 pandemic.
💡
Conclusion & Impact:It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.
🔬Design:Research Article
📍Scope:2019-2022 Verileri
⚙️Variables:Financial Performance · Operational Performance · Lopcow Method

Abstract

The purpose of the study is to view how companies operating in the Asian airline market responded to the crisis caused by the COVID-19 pandemic. Additionally, it aims to compare the financial and operational performance of airlines in the Asian airline market before, during, and after the COVID-19 pandemic. In this context, the financial and operational performance of 18 airlines in the Asian airline market for the period 2019-2022 was analysed using the Lopcow-based Marcos method. Firstly, financial and operational variables related to airlines were weighted using the Lopcow method. As a result of the weighting conducted with the Lopcow method, it was determined that the Dept Ratio and ROA variables had the most weight on the performance of these airlines. Subsequently, the performance ranking of airlines was conducted using the Marcos method. According to the ranking results obtained by the Marcos method; Spring Airlines (2019), Qantas Airways (2020), Air Arabia (2021) and Singapore Airlines (2022) were found to have the best performance. This study will make a significant contribution to the performance management of airlines in the Asian airline market. It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.

Özet

The purpose of the study is to view how companies operating in the Asian airline market responded to the crisis caused by the COVID-19 pandemic. Additionally, it aims to compare the financial and operational performance of airlines in the Asian airline market before, during, and after the COVID-19 pandemic. In this context, the financial and operational performance of 18 airlines in the Asian airline market for the period 2019-2022 was analyzed using the Lopcow-based Marcos method. Firstly, financial and operational variables related to airlines were weighted using the Lopcow method. As a result of the weighting conducted with the Lopcow method, it was determined that the Dept Ratio and ROA variables had the most weight on the performance of these airlines. Subsequently, the performance ranking of airlines was conducted using the Marcos method. According to the ranking results obtained by the Marcos method; Spring Airlines (2019), Qantas Airways (2020), Air Arabia (2021) and Singapore Airlines (2022) were found to have the best performance. This study will make a significant contribution to the performance management of airlines in the Asian airline market. It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.

🔖

Cite This Article

Asker, V., Kilinç, Z. (2025). Financial and Operational Performance Analysis Using LOPCOW Based MARCOS Method: A Case Study of the Asian Airline Market. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Volume: 12 Issue: 1. https://doi.org/10.30798/makuiibf.1495165

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (71)

  1. Abdullah, A., Achsani, N. A., & Suhendi. (2020). Bankruptcy analysis of national airlines companies in regional asia after Covid-19 Pandemic. Jurnal Aplikasi Manajemen Dan Bisnis, 6(3), 691-70. https://doi.org/10.17358/jabm.6.3.691
  2. Adrienne, N., Budd, L., & Stephen, I. (2020). Grounded aircraft: An airfield operations perspective of the challenges of resuming flights post COVID. Journal of Air Transport Management, 89(4), 1-6. https://doi.org/10.1016/j.jairtraman.2020.101921
  3. Airbus. (2019). Airbus global market forecast 2019-2038, https://www.airbus.com/sites/g/files/jlcbta136/files/2021-07/GMF-2019-2038-Airbus-Commercial-Aircraft-book.pdf
  4. Albers, S., & Rundshagen, V. (2020). European airlines′ strategic responses to the COVID-19 pandemic (January-May, 2020). Journal of Air Transport Management, 87(101863), 1-7. https://doi.org/10.1016/j.jairtraman.2020.101863
  5. Al-Najjar, S. M., & Kalaf, K. H. (2012). Designing a balanced scorecard to measure a bank's performance: A case study. International Journal of Business Administration, 3(4), 44-53. https://doi.org/10.5430/ijba.v3n4p44
  6. Altıntaş, F. F. (2022). Analysis of energy innovation performances of European countries: An application with Mabac and Marcos methods. Journal of Business Academy, 3(2), 188-216. https://doi.org/10.26677/TR1010.2022.1027
  7. Asker, V. (2021). Measurement of efficiency with two-stage data envelopment analysis in airline companies. MANAS Journal of Social Studies, 10(4), 2373-2385.
  8. Asker, V. (2022). Measurement of financial and operational efficiency with fuzzy data envelopment analysis in low-cost airline companies. Dicle University, Journal of Economics and Administrative Sciences, 12(23), 1-25. https://doi.org/10.53092/duiibfd.976524
  9. Asker, V. (2023). Financial performance of low-cost airlines during Covid-19 pandemic. Karamanoglu Mehmetbey University Journal of Social and Economic Research, 25(44), 87-102.
  10. Asker, V. (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, 318(2), 35-52. https://doi.org/10.33119/GN/184315
  11. Asker, V., & Aydın, N. (2021). Financial efficiency measurement in airlines and determining factors of efficiency. Alanya Akademic Rewiew Journal, 5(2), 793-814. https://doi.org/10.29023/alanyaakademik.809865
  12. Avcı, T., & Çınaroğlu, E. (2018). Financial performance evaluation of airline companies by AHP based TOPSIS approach. Cumhuriyet University Journal of Economics and Administrative Sciences, 19(1), 316-335.
  13. Bağcı, B., Çıtak, F., & Şişman, M. Y. (2020). The impact of coronavirus pandemic on airline stocks: An application of quantile-on-quantile regression model. Gaziantep University Journal of Social Sciences, 19(COVID-19 Special Issue), 429-446. https://doi.org/10.21547/jss.782043
  14. Bakır, M., Akan, Ş., Kiracı, K., Karabasevic, K., Stanujkıc, D. & Popovic, G. (2020). Multiple-criteria approach of the operational perfomance evaluation in the airline industry evidence from emerging market, Romanian Journal of Economic Forecasting, 2(2), 149-172.
  15. Barros, C., & Peypoch, N. (2009). An evaluation of European airlines’ operational performance. Int. J. Production Economics, 122(2), 525-533. https://doi.org/10.1016/j.ijpe.2009.04.016
  16. Bauer, L. B., Bloch, D., & Merkert, R. (2020). Ultra long-haul: An emerging business model accelerated by Covıd-19. Journal of Air Transport Management, 89(2020), 1-8. https://doi.org/10.1016/j.jairtraman.2020.101901 Boeing. (2019). Commercial market outlook 2019-2038, https://www.boeing.com/content/dam/boeing/boeingdotcom/commercial/market/commercial-market-outlook/assets/downloads/cmo-2019-report-final.pdf
  17. Bombelli, A. (2020). Integrators' global networks: A topology analysis with insights into the effect of the Covıd-19 pandemic. Journal of Transport Geography, 87(102815), 1-24. https://doi.org/10.1016/j.jtrangeo.2020.102815
  18. Chen, H.-C., & Yeh, C.-W. (2021). Global financial crisis and Covid-19: Industrial reactions. Finance Research Letters, 42(4), 1-13. https://doi.org/10.1016/j.frl.2021.101940
  19. Czerny, A. I., Fu, X., Lei, Z., & Oum, T. H. (2021). Post pandemic aviation market recovery: Experience and lessons from China. Journal of Air Transport Management, 90(2021), 1-10. https://doi.org/10.1016/j.jairtraman.2020.101971
  20. Dave, S. R., & Dave, S. R. (2012). Applying balance scorecard in Indian banking sector: An empirical study of the state bank of India. Pasific Business Review International, 5(6), 108-120.
  21. Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017). Balanced scorecard-based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment. Journal of Air Transport Management, 63(2), 17-33. https://doi.org/10.1016/j.jairtraman.2017.05.005
  22. Dube, K., Nhamo, G., & Chikodzi, D. (2021). Covid-19 pandemic and prospects for recovery of the global aviation industry. Journal of Air Transport Management, 92(102022), 1-2. https://doi.org/10.1016/j.jairtraman.2021.102022
  23. Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model. Journal of Cleaner Production, 266(2), 1-18. https://doi.org/10.1016/j.jclepro.2020.121981
  24. Ecer, F., Küçükönder, H., Kayapınar Kaya, S., & Görçün, Ö. F. (2023). Sustainability performance analysis of micro-mobility solutions in urban transportation with a novel IVFNN-Delphi-LOPCOW-CoCoSo framework. Transportation Research Part A, 172(103667), 1-20. https://doi.org/10.1016/j.tra.2023.103667
  25. Ghoushchi, Jafarzadeh S., Shaffiee Haghshenas, S., Memarpour Ghiaci, A., Guido, G., & Vitale, A. (2023). Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment. Neural Computing and Applications, 35(6), 4549-4567. https://doi.org/10.1007/s00521-022-07929-4
  26. Gönüllü, O. (2022). Evaluation of the financial performances of Turkish basic metal industry companies during the Covid-19 pandemic with ENTROPY – MARCOS integrated approach. Marmara University Journal of Economic and Administrative Sciences, 44(1), 53-77. https://doi.org/10.14780/muiibd.1135471
  27. Gramani, M. (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
  28. Gualini, A., Zou, L., & Dresner, M. (2023). Airline strategies during the pandemic: what worked? Transportation Research Part A: Policy and Practice, 170(2023), 1-22. https://doi.org/10.1016/j.tra.2023.103625
  29. Hu, S., & Zhang, Y. (2021). Covıd-19 pandemic and firm performance: Cross-country evidence. International Review of Economics & Finance, 74(3), 365-372. https://doi.org/10.1016/j.iref.2021.03.016
  30. The International Civil Aviation Organization. (2023). Effect of novel coronavirus (Covid-19) on civil aviation: Economic impact analysis, https://www.icao.int/sustainability/Documents/Covid-19/ICAO_coronavirus_Econ_Impact.pdf
  31. Jandghi, G., & Ramshini, M. (2014). A performance measurement model for automotive and petrochemical companies using FAHP and CCR method. European Journal of Academic Essays, 1(2), 80-92.
  32. Jaroenjitrkam, A., Kotcharin, S., & Maneenop, S. (2023). Corporate resilience to the COVID-19 pandemic: Evidence from the airline industry. The Asian Journal of Shipping and Logistics, 39(4), 26-36. https://doi.org/10.1016/j.ajsl.2023.10.003
  33. Kaffash, S., & Khezrimotlagh, D. (2023). U.S. network and low-cost carriers' performance in response to Covid- 19: Strictness of government policies and passengers' panic. Research in Transportation Business & Management, 46(2023), 1-15. https://doi.org/10.1016/j.rtbm.2022.100835
  34. Kiracı, K. (2019). Does joining global alliances affect airlines financial performance. In H. Kapucu & C. Akar
  35. (Eds.), Contemporary challenges in business and life sciences (p. 39-59). IJOPEC.
  36. Kiracı, K., & Bakır, M. (2019). Application of performance measurment in airlines with CRITIC based EDAS method, Pamukkale University Journal of Social Sciences Institute, 13(35), 157-174. https://doi.org/10.30794/pausbed.421992
  37. Kiracı, K., & Bakır, M. (2020). Evaluation of airlines performance using an integrated CRITIC and CODAS methodology: the case of star alliance member airlines. Studies in Business and Economics, 15(1), 83-99. https://doi.org/10.2478/sbe-2020-0008
  38. Kiracı, K., & Asker, V. (2021). Crisis in the air: A multi-dimensional analysis of the impact of the Covıd-19 pandemic on airline performance, Finance-Political & Economic Comments, 58(657), 33-60.
  39. Kiracı, K., Asker, V., & Güngör, Y. (2022). A review of financial performance of aircraft leasing companies. Journal of Aviation, 6(1), 61-72. https://doi.org/10.30518/jav.1032824
  40. Kirkwood, C. W. (1997). Strategic Decision making: Multiobjective decision analysis with spreadsheets. Duxbury Press.
  41. Lacus, S. M., Natale, F., Santamaria, C., Spyratos, S., & Vespe, M. (2020). Estimating and projecting air passenger traffic during the Covid-19 coronavirus outbreak and its socio-economic impact. Safety Science, 129(104791), 1-11. https://doi.org/10.1016/j.ssci.2020.104791
  42. Malighetti, P., Paleari, S., & Redondi, R. (2009). Pricing strategies of low-cost airlines: The Ryanair case study. Journal of Air Transport Management, 15(4), 195-103. https://doi.org/10.1016/j.jairtraman.2008.09.017
  43. Merkert, R., & Pearson, J. (2015). A non-parametric efficiency measure incorporating perceived airline service levels and profitability. Journal of Transport Economics and Policy, 49(2), 261-275.
  44. Mhlanga, O. (2019). Factors impacting airline efficiency in southern Africa: A data envelopment analysis. GeoJournal, 84(3), 759-770. https://doi.org/10.1007/s10708-018-9889-9
  45. Milne, R. J., Delcea, C., & Cotfas, L.-A. (2021). Airplane boarding methods that reduce risk from covid-19. Safety Science, 134(105061), 1-13. https://doi.org/10.1016/j.ssci.2020.105061
  46. Min, H., & Joo, S.-J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52(2), 90-110. https://doi.org/10.1016/j.jairtraman.2015.12.003
  47. Miškić, S., Stević, Ž., & Tanackov, I. (2021). A novel integrated SWARA-MARCOS model for inventory classification. IJIEPR, 32(4), 1-17.
  48. Özdağoğlu, A., Keleş, M. K., & Işildak, B. (2021). Evaluation of the world's busiest airports with PIPRECIA-E, SMART and MARCOS methods. Erciyes University Journal of Economics and Administrative Sciences, 2021(58), 333-352. https://doi.org/10.18070/erciyesiibd.856842
  49. Pamucar, D., Yazdani, M., Montero-Simo, M. J., Araque-Padilla, R. A., & Mohammed, A. (2021). Multi-criteria decision analysis towards robust service quality measurement. Expert Systems With Applications, 170(114508), 1-13. https://doi.org/10.1016/j.eswa.2020.114508
  50. Pereira, D., & Mello, J. (2021). Efficiency evaluation of Brazilian airlines operations considering the Covid-19 outbreak, Journal of Air Transport Management, 91(2), 1-6. https://doi.org/10.1016/j.jairtraman.2020.101976
  51. Perez, P. F., Vazquez, X. H., & Carou, D. (2022). The impact of the Covid-19 crisis on the US airline market: Are current business models equipped for upcoming changes in the air transport sector? Case Studies on Transport Policy, 10(2022), 647-656. https://doi.org/10.1016/j.cstp.2022.01.025
  52. Pineda, P. J., Liou, J. J., Hsu, C.-C., & Chuang, Y.-C. (2018). An integrated MCDM model for improving airline operational and financial performance. Journal of Air Transport Management, 68(2), 103-117. https://doi.org/10.1016/j.jairtraman.2017.06.003
  53. Pires, H. M., & Fernandes, E. (2012). Malmquist financial efficiency analysis for airlines. Transportation Research Part E, 48(5), 1049-1055. https://doi.org/10.1016/j.tre.2012.03.007
  54. Sakthidharan, V., & Sivaraman, S. (2018). Impact of operating cost components on airline efficiency in India: A DEA approach. Asia Pacific Management Review, 23(2), 258-267. https://doi.org/10.1016/j.apmrv.2017.12.001
  55. Sartal, A., Martinez-Senra, A. I., & Garcia, J. M. (2017). Balancing offshoring and agility in the apparel ındustry: Lessons from Benetton and Inditex. Fibres & Textiles in Eastern Europe, 25(2), 16-23.
  56. Sumerli Sarıgül, S., Ünlü, M., & Yaşar, E. (2023). Financial Performance Analysis of Airlines Operating in Europe: CRITIC Based MAUT and MARCOS Methods. International Journal of Business and Economic Studies, 5(2), 76-97. https://doi.org/10.54821/uiecd.1257488
  57. Sanchez, P. S., Voltes-Dorta, A., & Cuguero-Escofet, N. (2020). An early assessment of the impact of COVID-19 on air transport: Just another crisis or the end of aviation as we know it? Journal of Transport Geography, 86(102749), 1-8. https://doi.org/10.1016/j.jtrangeo.2020.102749
  58. Stankovic, M., Stević, Z., Das, D. K., Subotic, M., & Pamucar, D. (2020). A new fuzzy MARCOS method for road traffic risk analysis. Mathematics, 8(3), 1-17. https://doi.org/10.3390/math8030457
  59. Stević, Z., & Brkoviç, N. (2020). A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company. Logistics 4(1), 1-14. https://doi.org/10.3390/logistics4010004
  60. Stević, Z., Pamucar, D., Puska, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to compromise solution (MARCOS). Computers & Industrial Engineering, 140(2), 1-15. https://doi.org/10.1016/j.cie.2019.106231
  61. Taliah, A. R., & Zervopoulos, P. D. (2024). Airline performance measurement using bias-corrected network data envelopment analysis estimates: Evidence from a turbulent era. Heliyon, 10(19), 1-15. https://doi.org/10.1016/j.heliyon.2024.e38990
  62. Tanrıverdi, G., & Eryaşar, M. (2022). Global airline alliances and during the Covid-19 crisis: Exploring the critical succes factors through CRITIC-CoCoSo methods, Anadolu University Journal of Economics and Administrative Sciences, 23(4), 177-201. https://doi.org/10.53443/anadoluibfd.1142910
  63. Tanrıverdi, G., Merkert, R., Karamasa, Ç., & Asker, V., (2023). Using multi-criteria performance measurement models to evaluate the financial, operational and environmental sustainability of airlines. Journal of Air Transport Management, 112(102456), 102456. https://doi.org/10.1016/j.jairtraman.2023.102456
  64. Teker, S., Teker, D., & Güner, A. (2016). Financial performance of top 20 airlines. Procedia Social and Behavioral Sciences, 1(1), 603-610. https://doi.org/10.1016/j.sbspro.2016.11.035
  65. Uzgör, M. (2024). Evaluation of airport environmental management performance with multi criteria decision making methods: an application at five major airports in Turkey [Unpublished doctoral dissertation]. Anadolu University.
  66. Vasigh, B., Fleming, K., & Humphreys, B. (2015). Foundations of airline finance. Taylor Francis Group.
  67. Wang, Y. (2008). Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan. Expert Systems with Applications, 34(3), 1837-1845. https://doi.org/10.1016/j.eswa.2007.02.029
  68. Wu, S., Kremantzis, M. D., Tanveer, U., Ishaq, S., Xianghan, O., & Jin, H. (2024). Performance evaluation of the global airline industry under the impact of the COVID-19 pandemic: A dynamic network data envelopment analysis approach. Journal of Air Transport Management, 118(7), 1-17. https://doi.org/10.1016/j.jairtraman.2024.102597
  69. Wu, X., Wang, K., Fu, X., Dong, K., Sun, X., & Oum, T. H. (2025). How does COVID-19 pandemic affect airline’s route choice and market contact? − Full-service carriers vs. low-cost carriers in China. Transportation Research Part A: Policy and Practice, 191(1), 1-30. https://doi.org/10.1016/j.tra.2024.10429
  70. Zhang, Q., Yang, H., Wang, Q., & Zhang, A. (2014). Market power and its determinants in the Chinese airline industry. Transportation Research Part A, 64(1), 1-13. https://doi.org/10.1016/j.tra.2014.03.003
  71. Wu, S., Kremantzis, M. D., Tanveer, U., Ishaq, S., Xianghan, O., & Jin, H. (2024). Performance evaluation of the global airline industry under the impact of the COVID-19 pandemic: A dynamic network data envelopment analysis approach. Journal of Air Transport Management, 118(7), 1-17. https://doi.org/10.1016/j.jairtraman.2024.102597