The Examination of Financial Performance of Turkish Airports Using Cluster Analysis Method

Yıl 2023, , 109 - 121, 29.12.2023

İsmail Çağrı Özcan

https://doi.org/10.56668/jefr.1308082

Öz

The purpose of this study is to group Turkish companies through cluster analysis and implement a performance evaluation methodology based on the financial variables. In this context, using the data obtained from the financial statements and annual reports of 39 airports, which are operated by the General Directorate of State Airports Authority and not yet partially or completely privatized, (i) investment management (the ratio of annual investment amount to operating income), (ii) cost efficiency (ratio of operating costs to the amount of airport unit traffic served), (iii) profitability (ratio of operating revenues to operating costs), (iv) capital efficiency (ratio of apron capacity to operating revenues), and (v) labor capital efficiency (aerodrome unit serviced) are calculated first. In the next stage, 39 airports were divided into 4 different groups with similar characteristics with the help of cluster analysis. The results of the study reveal that cluster analysis can be a meaningful method to compare the financial performances of airports.

Anahtar Kelimeler

Financial Performance, Profitability, Capital Efficiency, Investment Management, Cluster Analysis

Türk Havalimanlarının Finansal Performanslarının Kümeleme Analizi Yöntemiyle İncelenmesi

Öz

Çalışmanın amacı, kümeleme analizi yoluyla Türk havalimanlarını gruplandırarak, finansal değişkenleri baz alan bir performans ölçme yöntemini hayata geçirmektir. Bu kapsamda, Devlet Hava Meydanları İşletmesi Genel Müdürlüğü tarafından işletilmekte olan ve henüz kısmen veya tamamen özelleştirilmemiş toplam 39 adet havalimanına ait finansal tablolardan ve faaliyet raporlarından elde edilen veriler kullanılarak (i) yatırım yönetimi (yıllık yatırım tutarının işletme gelirlerine oranı), (ii) maliyet verimliliği (işletme maliyetlerinin hizmet verilen havalimanı birim trafik miktarına oranı), (iii) karlılık (işletme gelirlerinin işletme maliyetlerine oranı), (iv) sermaye verimliliği (apron kapasitesinin işletme gelirlerine oranı) ve (v) iş gücü sermaye verimliliği (hizmet verilen havalimanı birim trafik miktarının çalışan sayısına oranı) için çeşitli finansal değişkenler hesaplanmıştır. Daha sonra 39 havalimanı kümeleme analizi yardımıyla benzer özelliklere sahip dört farklı gruba ayrılmıştır. Çalışmanın sonuçları, kümeleme analizinin havalimanlarının finansal performanslarını karşılaştırmak için anlamlı bir yöntem olabileceğini ortaya koymaktadır.

Anahtar Kelimeler

Finansal Performans, Karlılık, Sermaye Verimliliği, Yatırım Yönetimi, Kümeleme Analizi

Kaynakça

• Ahn, Y.H. and Min, H. (2014). Evaluating the multi-period operating efficiency of international airports using data envelopment analysis and the Malmquist productivity index. Journal of Air Transport Management, 39: 12-22.
• Barros, C.P. and Dieke, P.U. (2007). Performance evaluation of Italian airports: A data envelopment analysis. Journal of Air Transport Management, 13(4): 184-191.
• Behn, R.D. (2003). Why measure performance? Different purposes require different measures. Public Administration Review, 63(5): 586-606.
• Cifuentes-Faura, J. and Faura-Martínez, U. (2023). Measuring Spanish airport performance: A bootstrap data envelopment analysis of efficiency. Utilities Policy, 80: 101457.
• Fernandes, E. and Pacheco, R.R. (2002). Efficient use of airport capacity. Transportation Research Part A: Policy and Practice, 36(3): 225-238.
• Fernandes, E., Pacheco, R.R. and Braga, M.E. (2014). Brazilian airport economics from a geographical perspective. Journal of Transport Geography, 34: 71-77.
• Gillen, D. and Lall, A. (1997). Developing measures of airport productivity and performance: An application of data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 33(4): 261-273.
• Güner, S. and Codal, K.S. (2022). Endogenous and exogenous sources of efficiency in the management of Turkish airports. Utilities Policy, 76: 101370.
• Iyer, K.C. and Jain, S. (2019). Performance measurement of airports using data envelopment analysis: A review of methods and findings. Journal of Air Transport Management, 81: 101707.
• Kato, K., Uemura, T., Indo, Y., Okada, A., Tanabe, K., Saito, S. and Migita, K. (2011). Current accounts of Japanese airports. Journal of Air Transport Management, 17(2): 88-93.
• Kaya, G., Aydın, U., Karadayı, M.A., Ülengin, F., Ülengin, B. and İçken, A. (2022). Integrated methodology for evaluating the efficiency of airports: A case study in Turkey. Transport Policy, 127: 31-47.
• Keskin, B. and Köksal, C.D. (2019). A hybrid AHP/DEA-AR model for measuring and comparing the efficiency of airports. International Journal of Productivity and Performance Management, 68(3): 524-541.
• Malighetti, P., Meoli, M., Paleari, S. and Redondi, R. (2011). Value determinants in the aviation industry. Transportation Research Part E: Logistics and Transportation Review, 47(3): 359-370.
• Lin, L.C. and Hong, C.H. (2006). Operational performance evaluation of international major airports: An application of data envelopment analysis. Journal of Air Transport Management, 12(6): 342-351.
• Liu, D. (2016). Measuring aeronautical service efficiency and commercial service efficiency of East Asia airport companies: An application of network data envelopment analysis. Journal of Air Transport Management, 52: 11-22.
• Özcan, İ.Ç. (2019). Capital structure and firm performance: Evidence from the airport industry. European Journal of Transport and Infrastructure Research, 19(3): 177-195.
• Özcan, İ.Ç. (2021). Do the companies benefit from improved disclosure performance? Evidence from the airport industry. New Approaches to CSR, Sustainability and Accountability, 2: 113-124.
• Özsoy, V.S. and Örkcü, H.H. (2021). Structural and operational management of Turkish airports: A bootstrap data envelopment analysis of efficiency. Utilities Policy, 69: 101180.
• Sarkis, J. and Talluri, S. (2004). Performance based clustering for benchmarking of US airports. Transportation Research Part A: Policy and Practice, 38(5): 329-346.
• Suzuki, S., Nijkamp, P., Rietveld, P. and Pels, E. (2010). A distance friction minimization approach in data envelopment analysis: A comparative study on airport efficiency. European Journal of Operational Research, 207(2): 1104-1115.
• Uludağ, A.S. (2020). Measuring the productivity of selected airports in Turkey. Transportation Research Part E: Logistics and Transportation Review, 141: 102020.
• Usami, M. and Akai, N. (2012). Financial performance of airport terminal companies in Japan–Harmful effects of government participation. Journal of Air Transport Management, 25: 40-43.
• Vogel, H.A. and Graham, A. (2013). Devising airport groupings for financial benchmarking. Journal of Air Transport Management, 30: 32-38.
• Yu, M.M., Chern, C.C. and Hsiao, B. (2013). Human resource rightsizing using centralized data envelopment analysis: Evidence from Taiwan's airports. Omega, 41(1): 119-130.