Comparative Financial Efficiency and Performance Analysis with TOPSIS and MOORA Methods: An Application on Logistic Companies

Yıl 2025, Cilt: 59 Sayı: 3, 531 - 548, 21.07.2025

İsmail Öztanır

https://doi.org/10.51551/verimlilik.1656798

Öz

Purpose: This study aims to evaluate the financial performance and efficiency of logistics companies listed on Borsa Istanbul, with a focus on analyzing the impact of the pandemic through financial ratios from 2019 to 2023.
Methodology: In the research, TOPSIS and MOORA methods, which are multi-criteria decision-making methods, were used. These methods were used to assess the performance of the companies with the help of selected financial ratios.
Findings: Analysis of the top three performing companies showed notably high efficiency ratios—particularly receivables and inventory turnover—alongside low debt levels. GSDDE, ranked first by the TOPSIS method, stood out with significantly higher operating profitability in its peak years. Additionally, companies with stronger liquidity (e.g., higher acid-test ratios) outperformed others, highlighting the importance of solid cash reserves during economic uncertainty.
Originality: It is unique in that it focuses on measuring financial efficiency in the logistics sector by using TOPSIS and MOORA methods together and is research that compares pre- pandemic and post-pandemic performance results in the light of the findings of recent studies in the relevant sector. The study provides a unique perspective on the impact of the COVID-19 pandemic (2019–2023) on the logistics sector, offering insights into key financial indicators such as efficiency, debt structure, and profitability trends.

Anahtar Kelimeler

Financial Performance , Efficiency Analysis , TOPSIS , MOORA , Logistics Industry

Etik Beyan

It was declared by the author(s) that scientific and ethical principles have been followed in this study and all the sources used have been properly cited.

Destekleyen Kurum

Any specific grant has not been received from funding agencies in the public, commercial, or not-for-profit sectors.

TOPSIS ve MOORA Yöntemleri ile Karşılaştırmalı Finansal Verimlilik ve Performans Analizi: Lojistik Şirketlerine Yönelik Bir Uygulama

Öz

Amaç: Bu çalışma, Borsa İstanbul’da işlem gören lojistik şirketlerinin finansal performans ve verimliliğini değerlendirmeyi ve 2019-2023 yılları arasındaki finansal oranlar üzerinden pandeminin sektör üzerindeki etkilerini analiz etmeyi amaçlamaktadır.
Yöntem: Araştırmada yöntem olarak çok kriterli karar verme yöntemlerinden TOPSIS ve MOORA kullanılmıştır. Bu yöntemler, seçilen finansal oranlar yardımıyla şirketlerin performans sıralamasında kullanılmıştır.
Bulgular: En iyi performans gösteren ilk üç şirketin finansal oranları incelendiğinde, özellikle alacak ve stok devir hızları gibi verimlilik oranlarının sektör ortalamasının üzerinde olduğu ve borç oranlarının düşük olduğu görülmüştür. TOPSIS yöntemine göre birinci sırada yer alan GSDDE, yüksek puan aldığı yıllarda diğer şirketlere kıyasla dikkate değer ölçüde yüksek faaliyet kârlılığı göstermiştir. Ayrıca, likiditesi güçlü olan (örneğin, yüksek asit-test oranına sahip) şirketlerin daha iyi performans sergilediği ve ekonomik belirsizlik dönemlerinde güçlü nakit rezervlerinin önemini vurguladığı anlaşılmıştır.
Özgünlük: TOPSIS ve MOORA yöntemlerini birlikte kullanarak lojistik sektöründe finansal verimliliğin ölçülmesine odaklanmış olması ve ilgili sektörde literatürde yakın zamanda yapılan çalışmaların bulguları ışığında pandemi öncesi ve sonrası performans sonuçlarını karşılaştıran bir araştırma olması bakımından özgündür. Çalışma, COVID-19 salgınının (2019-2023) lojistik sektörü üzerindeki etkisine dair benzersiz bir bakış açısı sunarak verimlilik, borç yapısı ve kârlılık eğilimleri gibi temel finansal göstergelere ilişkin fikirler sunmaktadır.

Anahtar Kelimeler

Finansal Performans , Verimlilik Analizi , TOPSIS , MOORA , Lojistik Sektörü

Kaynakça

• Akarçay, B. (2011). “Denizcilik İşletmelerinde Lojistik Yönetimi ve Türkiye Uygulaması”, Published Master Thesis, Beykent University Graduate of Social Sciences, İstanbul.
• Almeida, H. and Philippon, T. (2007). “The Risk‐Adjusted Cost of Financial Distress”, The Journal of Finance, 62(6), 2557-2586. https://doi.org/10.1111/j.1540-6261.2007.01286.x
• Altın, F.G. and Filiz, T. (2022). “Assessment of the Performance of Logistics Villages Operated by the Turkish State Railways Using MCDM and DEA Methods”. Ege Academic Review, 22(2), 169-182. Doi: 10.21121/eab.983220
• Anthony, P., Behnoee, B., Hassanpour, M. and Pamucar, D. (2019). “Financial Performance Evaluation of Seven Indian Chemical Companies”, Decision Making: Applications in Management and Engineering, 2(2), 81-99. https://doi.org/10.31181/dmame1902021a
• Atayah, O.F., Dhiaf, M.M., Najaf, K. and Frederico, G.F. (2022). “Impact of COVID-19 on Financial Performance of Logistics Firms: Evidence from G-20 Countries”, Journal of Global Operations and Strategic Sourcing, 15(2), 172-196. https://doi.org/10.1108/JGOSS-03-2021-0028
• Baños-Caballero, S., García-Teruel, P.J. and Martínez-Solano, P. (2014). “Working Capital Management, Corporate Performance, and Financial Constraints”, Journal of Business Research, 67(3), 332-338. https://doi.org/10.1016/j.jbusres.2013.01.016
• Bayramoğlu, M.F. and Başarır, Ç. (2016). “Borsa İstanbul’da İşlem Gören Sigorta Şirketlerinin Karşılaştırmalı Finansal Performans Analizi”, Anadolu Üniversitesi Sosyal Bilimler Dergisi (Anadolu University Journal of Social Sciences), 16(4), 135- 144.
• Behzadian, M., Otaghsara, S.K., Yazdani, M. and Ignatius, J. (2012). “A State-of the-Art Survey of TOPSIS Applications”, Expert Systems with Applications, 39(17), 13051–13069. https://doi.org/10.1016/j.eswa.2012.05.056
• Birou, L., Germain R.N. and Christensen W.J. (2011). “Applied Logistics Knowledge Impact on Financial Performance”, International Journal of Operations & Production Management, 31(8), 816-834. https://doi.org/10.1108/01443571111153058
• Brauers, W.K. and Zavadskas, E.K. (2006). „The MOORA Method and Its Application to Privatization in A Transition Economy”, Control and Cybernetics, 35(2), 445-469.
• Brauers, W. K. and Zavadskas, E. K. (2010). “Project Management by the MOORA Method”, Economic Computation and Economic Cybernetics Studies and Research, 44(1), 5-21.
• Bulgurcu, B. (2012). “Application of TOPSIS Technique for Financial Performance Evaluation of Technology Firms in Istanbul Stock Exchange Market”. Procedia - Social and Behavioral Sciences, 62, 1033-1040. https://doi.org/10.1016/j.sbspro.2012.09.176
• Campello, M., Graham, J.R. and Harvey, C.R. (2010). “The Real Effects of Financial Constraints: Evidence from A Financial Crisis”, Journal of Financial Economics, 97(3), 470-487. https://doi.org/10.1016/j.jfineco.2010.02.009
• Erdoğan, H.H. and Kırbaç, G. (2021). “Financial Performance Measurement of Logistics Companies Based on Entropy and WASPAS Methods”, Journal of Business Research-Turk, 13(2), 1093-1106.
• Ertuğrul, İ. and Karakasoğlu, N. (2009). “Performance Evaluation of Turkish Cement Firms with Fuzzy Analytic Hierarchy Process and TOPSIS Methods”, Expert Systems with Applications, 36, 702-715.
• Erturgut, R. and Oğuz, S. (2022). “Lojistik Merkezlerin İhracata Etkisi: AB Ülkeleri Üzerine Yatay Kesit Veriler ile Regresyon Analizi”, Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(4), 423-430. https://doi.org/10.52791/aksarayiibd.1075080
• Gümüş, Y. (2009). “Lojistik Faaliyetlerin Rekabet Stratejileri ve işletme Kârı İle Olan İlişkisi”, Muhasebe ve Finansman Dergisi, 41, 97-114.
• Gürkan, S. and Aldoury, N. (2021). “TOPSIS Çok Kriterli Karar Verme Yöntemi İle Karşılaştırmalı Finansal Performans Analizi: Teknoloji Şirketleri Üzerine Bir Araştırma”, Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 6(2), 225-239. https://doi.org/10.29106/fesa.868905
• Hofmann, E. and Lampe, K. (2013). “Financial Statement Analysis of Logistics Service Providers: Ways of Enhancing Performance”, International Journal of Physical Distribution & Logistics Management, 43(4), 321-342. https://doi.org/10.1108/IJPDLM-08-2012-0229
• Hwang, C.L. and Yoon, K. (1981). “Multiple Attribute Decision Making: Methods and Applications”. Springer- Verlag, New York.
• Hwang, C., Young-Jou, L. and Ting-Yun, L. (1993). “A New Approach for Multiple Objective Decision Making”, Computers and Operational Research, 20(8), 889-899. https://doi.org/10.1016/0305-0548(93)90109-V
• Işık, Ö. (2022). “Gri Entropi, FUCOM ve EDAS-M Yöntemleriyle Türk Lojistik Firmalarının Çok Kriterli Performans Analizi”, Yaşar Üniversitesi E-Dergisi, 17(66), 472-489. https://doi.org/10.19168/jyasar.939276
• Jang, S.W. and Ahn, W.C. (2021). “Financial Analysis Effect on Management Performance in the Korean Logistics Industry”, The Asian Journal of Shipping and Logistics, 37(3), 245-252. https://doi.org/10.1016/j.ajsl.2021.06.003
• Komchornrit, K. (2021). “Financial Evaluation by the Combined AHP-PROMETHEE Method: A Case Study of Integrated Logistics Service Providers in Thailand”, Journal of Community Development Research (Humanities and Social Sciences), 14(2), 77-89.
• Komchornit, D. (2021). “An Evaluation of Financial Performance of Logistics Firms Using Financial Ratio Analysis”, Journal of Supply Chain and Operations Management, 19(1), 45–60.
• Konak, T., Elbir, G., Yılmaz, S., Karataş, B., Durman, Y. and Düzakın, H. (2018). “Borsa İstanbul’da İşlem Gören Tekstil Firmalarının TOPSIS ve MOORA Yöntemi İle Analizi”. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(1), 11-44.
• Küçükaltan, B., Irani, Z. and Aktas, E. (2016). “A Decision Support Model for Identification and Prioritization of Key Performance Indicators in the Logistics Industry”, Computers in Human Behavior, 65, 346-358. https://doi.org/10.1016/j.chb.2016.08.045
• Laari, S., Töyli, J. and Ojala, L. (2018). “The Effect of A Competitive Strategy and Green Supply Chain Management on the Financial and Environmental Performance of Logistics Service Providers”, Business Strategy and the Environment, 27(7), 872-883. https://doi.org/10.1002/bse.2038
• Lee, P.F., Lam, W.S. and Lam, W.H. (2021). “Evaluation and Improvement of the Efficiency of Logistics Companies with Data Envelopment Analysis Model”, Engineering Journal, 25(6), 45-54. https://doi.org/10.4186/ej.2021.25.6.45
• Meng, J. and Wang, S. (2022). “The Performance Evaluation of Logistics Enterprises in Online Supply Chain Finance Based on Analytic Hierarchy Process”, Mathematical Problems in Engineering, 2022(1), 8393223. https://doi.org/10.1155/2022/8393223
• Nenavani, J., Prasuna, A., Siva Kumar, S.N.V. and Kasturi, A. (2024). “ESG Measures and Financial Performance of Logistics Companies”, Letters in Spatial and Resource Sciences, 17(1), 5. https://doi.org/10.1007/s12076-023-00358-4
• Nguyen, H.T.X. (2022). “The Effect of COVID-19 Pandemic on Financial Performance of Firms: Empirical Evidence from Vietnamese Logistics Enterprises”, The Journal of Asian Finance, Economics and Business, 9(2), 177-183. https://doi.org/10.13106/jafeb.2022.vol9.no2.0177
• Orçun, Ç. and Eren, S. (2017). “TOPSIS Yöntemi ile Finansal Performans Değerlendirmesi: XUTEK Üzerinde Bir Uygulama”, Muhasebe ve Finansman Dergisi 75, 139-154. https://doi.org/10.25095/mufad.399899
• Pamučar, D. and 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. https://doi.org/10.1016/j.eswa.2014.11.057
• Sharma, N.K., Kumar, V., Verma, P. and Luthra, S. (2021). “Sustainable Reverse Logistics Practices and Performance Evaluation with Fuzzy TOPSIS: A Study on Indian Retailers”, Cleaner Logistics and Supply Chain, 1, 100007. https://doi.org/10.1016/j.clscn.2021.100007
• Sobieralski, J.B. (2020). “COVID-19 and Airline Employment: Insights from Historical Uncertainty Shocks to the Industry”, Transportation Research Interdisciplinary Perspectives, 5, 100123. https://doi.org/10.1016/j.trip.2020.100123
• Stanujkic, D., Zavadskas, E.K., Brauers, W.K. and Karabasevic, D. (2012). “An Approach to Personnel Selection Based on the MOORA Method”, Business: Theory and Practice, 13(2), 103-111.
• Uygurtürk, H. and Korkmaz, T. (2012). “Finansal Performansın TOPSIS Çok Kriterli Karar Verme Yöntemi İle Belirlenmesi: Ana Metal Sanayi İşletmeleri Üzerine Bir Uygulama”, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 7(2), 95-115.
• Yazdani, M. and Payam, A.F. (2015). “A Comparative Study on MCDM Methods for Material Selection: The Case of Automotive Industry”, Decision Science Letters, 4(3), 345-358. https://doi.org/10.5267/j.dsl.2015.2.004
• Yoon, K. (1987). “A Reconciliation among Discrete Compromise Situations”, Journal of the Operational Research Society, 38(3), 277-286.
• Yürüyen, A.A., Ulutaş, A. and Özdağoğlu, A. (2023). “Lojistik İşletmelerinin Performansının Bir Hibrit ÇKKV Modeli ile Değerlendirilmesi”, Business & Management Studies: An International Journal, 11(3), 731-751. https://doi.org/10.15295/bmij.v11i3.2245
• Zavadskas, E.K., Turskis, Z. and Kildienė, S. (2016). “State of Art Surveys of Overviews on MCDM/MADM Methods”, Technological and Economic Development of Economy, 22(2), 165-200. https://doi.org/10.3846/20294913.2016.1164560