Çok Aşamalı ve Dinamik Etkinlik Analizi: Türkiye Turizm Şirketlerinin Finansal Değerlendirmesi (Multi-Stage and Dynamic Efficiency Analysis: Financial Evaluation of Turkish Tourism Companies)

Authors

  • Cemil ŞENEL

DOI:

https://doi.org/10.63556/jotags.2026.1780

Keywords:

Tourism, Dynamic Data Envelopment Analysis (DEA), Financial performance, Efficiency, Borsa Istanbul (BIST)

Abstract

This study analyzes the financial efficiency of tourism companies listed on Borsa Istanbul (BIST) during the 2018–2024 period using the Dynamic Network Data Envelopment Analysis (DZVA) method. A two-stage model is employed to evaluate the transition from financial structure to profitability. In the first stage, inputs include current ratio, leverage ratio, and fixed assets-to-equity ratio, while outputs are return on assets (ROA) and net profit margin. These intermediate outputs are then used as inputs in the second stage, with return on equity (ROE) and operating profit margin serving as final outputs. The findings reveal significant variations in efficiency levels across firms and time periods. While some firms maintained consistent efficiency, others experienced performance declines in specific years. The study demonstrates that the DZVA method offers a robust analytical framework to assess the dynamic nature of the tourism sector over time, providing valuable insights for performance monitoring, resource allocation, and strategic decision-making.

References

Aksungur, M. & Deran, A. (2021). Borsa İstanbul’a kayıtlı ulaştırma ve depolama sektörü şirketlerinin etkinlik değerlendirmesi: Veri zarflama analizi uygulaması. Uluslararası İşletme, Ekonomi ve Yönetim Perspektifleri Dergisi (IJBEMP), 5(2), 760-771.

Aprea, I.L. & Sbaiz, G.A. (2025). Neural Network-Particle Swarm Solver For sustainable portfolio optimization problems. In Decisions in Economics and Finance; Springer: Berlin/Heidelberg, Germany, 1–40.

Assaf, A. G., & Tsionas, M. (2018). The Estimation and Decomposition of Tourism Productivity. Tourism Management, 65, 131-142.

Assaf, A. G., & Josiassen, A. (2012). Identifying and ranking the determinants of tourism performance: A global investigation. Journal of Travel Research, 51(4), 388–399. Https://doi.org/10.1177/0047287511426337

Bardî, Ş. (2024). İmalat alt sektörlerinin finansal performans ile etkinlikleri arasındaki ilişki: Maliyet girdi odaklı yaklaşım. Anadolu Üniversitesi İİBF Dergisi, 25(2), 459–490.

Cenger, H. (2023). Borsa İstanbul Konaklama Sektöründe Yer Alan Şirketlerin Covid-19 Öncesi ve Covid-19 Dönemi Finansal Performanslarının Süper Etkinlik Yöntemi ile Karşılaştırması. İçinde: Levent Karadağ & Gizem Özgürel (Ed.), Teorik Yaklaşımlarla Disiplinlerarası Turizm Araştırmaları.Ankara: Detay Yayıncılık.

Chen, T.-A. (2022). Business performance evaluation for tourism factory: Using DEA approach and Delphi method. Sustainability, 14(15), 9209. Https://doi.org/10.3390/su14159209

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. Https://doi.org/10.1016/0377-2217(78)90138-8

Dobrovič, J., Čabinová, V., Gallo, P., Partlová, P., Váchal, J., & Balogová, B. (2021). Application of the DEA model in tourism smes: An empirical study from Slovakia in the context of business sustainability. Sustainability, 13(7422). Https://doi.org/10.3390/su130207422

Doğan, N. Ö., & Tan, A. (2008). Konaklama şirketlerinde veri zarflama analizi yöntemiyle faaliyet denetimi: Kapadokya örneği. İİBF Dergisi, 22(1), 239–254.

Fenyves, V., Tarnóczi, T., & Zsidó, K. (2015). Financial performance evaluation of agricultural enterprises with DEA method. Procedia Economics and Finance, 32, 423–431. Https://doi.org/10.1016/S2212-5671(15)01413-6

Goodwin, H. (2019). Overtourism: Causes, symptoms and treatment. Tourismus Wissen Quarterly.

Gülcü, A., & Cenger, H. (2013). İMKB’de işlem gören turizm şirketlerinin veri zarflama analizi yöntemiyle mali performanslarının ölçümü ve benchmarking uygulaması. Journal of Academic Social Science Studies, 6(8), 853–870.

Huang, C. (2018). Assessing the performance of tourism supply chains by a hybrid network DEA model. Annals of Operations Research, 268(1–2), 167–186. Https://doi.org/10.1007/s10479-017-2702-5

Hosseini, S. P., & Hosseini, S. M. (2021). Efficiency assessment of tourism industry in developing countries in the context of infrastructure: A two-stage super-efficiency slacks-based measure. Open Journal of Social Sciences, 9(9), 346–372. Https://doi.org/10.4236/jss.2021.99025

İnceöz, S. (2024). Teorik yaklaşımlarla disiplinlerarası turizm araştırmaları. Detay Yayıncılık.

Köksal, C. D., & Aksu, A. (2007). Efficiency evaluation of A-group travel agencies with data envelopment analysis: A case study in the Antalya region, Turkey. Tourism Management, 28(2), 530–541. Https://doi.org/10.1016/j.tourman.2006.04.021

Stoiljković, A., Marcikić Horvat, A., & Tomić, S. (2025). Assessing the tourism efficiency of European countries using data envelopment analysis: A sustainability approach. Sustainability, 17(4), 1493. Https://doi.org/10.3390/su17041493

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

TÜRSAB. (2022). TÜRSAB İstatistik Aralık 2022 Raporu. Türkiye Seyahat Acentaları Birliği. Https://www.tursab.org.tr/ziyaretci-sayilari/ziyaretci-sayilari-2022

UNWTO. (2018). Overtourism? Understanding and managing urban tourism growth. World Tourism Organization.

UNWTO. (2020). International tourism highlights. World Tourism Organization.

Wang, D., Li, M., Guo, P. & Xu, W. (2016). The Impact of Sharing Economy on the Diversification of Tourism Products: Implications for Tourist Experience. Information and Communication Technologies in Tourism, 683-694.

WTTC. (2023). Travel & Tourism Economic Impact 2023. Apec. Https://assets-global.website-files.com/6329bc97af73223b575983ac/647df24b7c4bf560880560f9_EIR2023-APEC.pdf

Zha, J., Yuan, W., Dai, J., Tan, T., & He, L. (2020). Eco-efficiency, eco-productivity and tourism growth in China: A non-convex metafrontier DEA-based decomposition model. Journal of Sustainable Tourism, 28(5), 663–685. Https://doi.org/10.1080/09669582.2019.1708914

Published

30-03-2026

How to Cite

ŞENEL , C. (2026). Çok Aşamalı ve Dinamik Etkinlik Analizi: Türkiye Turizm Şirketlerinin Finansal Değerlendirmesi (Multi-Stage and Dynamic Efficiency Analysis: Financial Evaluation of Turkish Tourism Companies). Journal of Tourism & Gastronomy Studies, 14(1), 70–82. https://doi.org/10.63556/jotags.2026.1780