Financial Performance Analysis of TAV Airports Listed in Borsa Istanbul with Entropy Based VIKOR Method

Year 2025, Volume: 9 Issue: 2, 417 - 427, 28.06.2025

İlknur Ülkü Armağan , Demet Dağlı

https://doi.org/10.30518/jav.1679094

Abstract

The aviation sector is a strategic service domain that is highly sensitive to global economic fluctuations, pandemics, and geopolitical crises. This study analyzes the financial performance of TAV Airports, a publicly traded company listed on Borsa Istanbul and operating within the aviation industry, for the period 2019–2024 using the Entropy-based VIKOR method. In this context, assessing the financial resilience of sectoral actors is of great importance. Financial ratios were weighted using the Entropy method, and the performance ranking was carried out through the VIKOR approach. The findings reveal that 2019 was the year with the strongest financial performance (Qj = 0.056), while 2020 exhibited the weakest performance (Qj = 1.000). Additionally, the strongest and weakest financial indicators were identified for each year, allowing for the evaluation of the company’s annual strengths and areas for improvement. These findings are particularly significant for investors, analysts, financial market participants, and decision-makers focusing on Borsa Istanbul and the broader Turkish capital markets, as they support more informed portfolio strategies and risk assessments within the aviation sector.

Keywords

Borsa Istanbul , Financial Performance , Aviation Management , VIKOR , Entropy

References

• Abbruzzo, A., Fasone, V., & Scuderi, R. (2016). Operational and financial performance of Italian airport companies: A dynamic graphical model. Transport Policy, 52, 231-237.
• Alp, I., Öztel, A., & Köse, M. S. (2015). Corporate sustainability performance measuring with Entropy Based MAUT method: A case study, The International Journal of Economic and Social Research, Vol. 11, Year 11, No. 2.
• Asker, V., & Kiracı, K. (2016). A research on review of financial performance: airport groups sample. International Journal of Shipping and Transport Logistics, 16, 38.
• Bakır, M., & Atalık, Ö. (2018). Evaluation of service quality in airlines by Entropy and ARAS methods. Journal of Business Research Turk, 10(1), 617-638.
• Battal, Ü. (2020). Measurement of financial performance of airport groups companies in Europe: Data envelopment analysis method. Academic Review of Economics and Administrative Sciences, 13(1) pp: 171-184.
• Chen, Y. H., & Wang, T. C. (2009). Optimizing partner’s choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR. International Journal of Production Economics, 120(1), 233–242.
• de Neufville, R., & Odoni, A. (2013). Airport systems: Planning, design, and management (2nd ed.). McGraw-Hill Education.
• Demirarslan, P. Ç., Küçükönder, H., & Kıngır, S. (2019). Evaluation of emotional performance on academicians with Entropy based TOPSIS and VIKOR methods: Bartin case. Electronic Journal of Social Sciences, 18(69), 232- 251.
• Durak, İ., & Bal, B. Ç. (2024). Comparison of banks’ performances in the pre-and post-COVID-19 period using Entropy and VIKOR methods. Unye Journal of Economics and Administrative Sciences, 6(2), 102-113.
• Ertuğrul, İ., & Karakaşaoğlu, N. (2009). Performance evaluation of bank branches with VIKOR Method. Journal of Industrial Engineering (Turkish Chamber of Mechanical Engineers), 20(1), 19-28.
• Eş, A., & Kocadağ, D. (2020). Supplier selection with entropy based MAUT and VIKOR methods: A public institution case study. Manisa Celal Bayar University Journal of Social Sciences, 18, 265-280.
• Forsyth, P., Gillen, D., Müller, J., & Niemeier, H. M. (2010). Airport competition: The European experience. Ashgate Publishing.
• Graham, A. (2013). Managing airports: An international perspective (4th ed.). Routledge.
• Hacıfettahoğlu, Ö., & Perçin, S. (2020). Evaluation of the performance of Turkish construction companies in the financial dimension with integrated MCDM approach. Dokuz Eylül University Journal of Social Sciences Institute, 22(2), 543-567.
• Humphreys, I., & Francis, G. (2002). Policy issues and planning of UK regional airports. Journal of Transport Geography, 10(4), 249–258.
• ICAO. (2021). Effects of COVID-19 on Civil Aviation: Economic impact analysis. Montreal: International Civil Aviation Organization.
• IATA. (2021). World Air Transport Statistics (WATS). International Air Transport Association.
• Kahraman, C. (2008). Multi-Criteria Decision Making and Fuzzy Systems. Springer.
• Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.
• Opricovic, S., & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514–529.
• Oum, T. H., Adler, N., & Yu, C. (2006). Privatization, corporatization, ownership forms and their effects on the performance of the world's major airports. Journal of air Transport management, 12(3), 109-121.
• Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area comparison (MABAC). Expert systems with applications, 42(6), 3016-3028.
• Public Disclosure Platform, Companies, TAV Airports, https://www.kap.org.tr/en/sirket-bilgileri/ozet/1452-tav- havalimanlari-holding-a-s.
• Raghavan, S., & Yu, C. (2021). Evaluating financial performance of commercial service airports in the United States. Journal of Air Transport Management, 96, 102111.
• Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill.
• Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379– 423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
• Şeker, M., & İslamoglu, M. (2024). Analysis of takaful insurance companies’ performance in 2022 using the VIKOR method. Econder International Academic Journal, 8(2), 228-242.
• Şenkal, E., & Öztel, A. (2020). Measuring the financial performance of the retail sector by entropy based COPRAS method: The Carrefoursa case. Journal of Management Economics Literature Islamic and Political Sciences, 5(1), 8-24.
• Tanino, T. (1999). Sensitivity analysis in MCDM. In Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications (pp. 173-201). Boston, MA: Springer US.
• TAV Airports, Investor Relations, Annual Reports, https://ir.tav.aero/en-EN/
• Tzeng, G. H., & Huang, J. J. (2011). Multiple Attribute Decision Making: Methods and Applications. CRC Press.
• Yılmaz, Ö., & Yakut, E. (2021). Evaluation of financial performance in banking sector using Entropy Based TOPSIS and VIKOR methods. Atatürk University Journal of Economics and Administrative Sciences, 35(4), 1297- 1321.
• Wang, Y. M., & Elhag, T. M. S. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems with Applications, 31(2), 309–319.
• Wang, Y. M., & Lee, H. S. (2009). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers & Mathematics with Applications, 57(6), 1072–1080.
• Zhang, X., Wang, C., Li, E., & Xu, C. (2014). Assessment model of ecoenvironmental vulnerability based on improved entropy weight method. The Scientific World Journal, 2014(1), 797814.
• Zavadskas, E. K., & Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: An overview. Technological and Economic Development of Economy, 17(2), 397–427.
• Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179.
• Zeleny, M. (1982). Multiple criteria decision making. McGraw-Hill.