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Evaluation of Operational Performance of Major European International Airports with Data Envelopment

Yıl 2025, Cilt: 9 Sayı: 2, 436 - 444, 28.06.2025

Hakan Kaya , Ahmet İlbaş

https://doi.org/10.30518/jav.1639240

Öz

This paper studies the impact of air logistics and transportation on the operational efficiency of 10 major European International Airports over the 2021–2023 period using the Data Envelope Analysis (DEA) method, which is solved using MAXDEA 8 software.
For this purpose, a literature review was carried out to identify the input and output variables used in analysing the operational efficiency of airport logistics. In this study, the input variables include the airport's area, cargo terminal area, the number of passenger terminals, and the number of runways, while the output variables are the number of flights, the number of passengers, and amount of cargo are used. The DEA model provides the most efficient results in terms of output-oriented maximization. The performance of each airport is compared to others, and the efficiency rate for each airport is evaluated. The study identifies the effective airports, their reference points relative to others, and assesses how much improvement is needed for ineffective airports to enhance their outputs.
As a result of this application, it was concluded that the operational efficiency of airports is effective or ineffective according to air logistics and transportation activities. As a result of this study, it was revealed that the operational efficiency of 8 of 10 major international airports in the 2021-2023 period was effective, and only 2 of them (Paris Charles de Gaulle, Madrid) were ineffective. While two inefficient airports could have produced more output by better utilizing their potential with the same input amounts, they made less output where they were located. The study identifies relative efficiency levels across airports and highlights internal performance differences. Furthermore, the discussion addresses the influence of external factors such as geopolitical events, environmental policies, and technological innovations, offering deeper insights into the drivers of airport performance. The findings contribute to strategic airport management by highlighting both internal and external dimensions of efficiency.

Anahtar Kelimeler

Logistics Air Transportation Data Enlevopment Analysis (DEA) Logistics Operational Efficiency Airport Management

Kaynakça

  • Adler, N. and Berechman, J. (2001). Measuring airport quality from the airlines’ viewpoint: An application of data envelopment analysis. Transport Policy, 8 (3), 171–181.
  • Altın, F. G., Karaatlı, M. and Budak, I. (2017). Evaluation of Europe's 20 largest airports with multi-criteria decision-making methods and data envelopment analysis. Süleyman Demirel University Journal of the Faculty of Economics and Administrative Sciences, 22(4):1049-1064
  • Asker, V. and Battal, Ü. (2017), Operatıonal effıcıency measurement at selected aırports. International Journal of Management Economics and Business, ICMEB17 Special Issue: 351-368
  • Avcı, T. and Aktaş, M. (2015), Evaluation of the performance of airports operating in Türkiye. International Journal of Alanya Business Faculty,7(3): 67-77.
  • Banker, R.D., Charnes, A. and Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30, 1984: 1085.
  • Barbara T.H. Yen, Jun-Sheng Li (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach, Transportation Research Part E: Logistics and Transportation Review, Volume 162, 102748, ISSN 1366-5545.
  • Barros, C. and Dieke, P. (2007). Performance evaluation of Italian airports: A data envelopment analysis. Journal of Air Transport Management - J Air Transp Manag. 13. 184-191. 10.1016/j.jairtraman.2007.03.001.
  • Bazargan, M., and Vasigh, B. (2003). Size versus efficiency: a case study of US commercial airports. Journal of Air Transport Management, 9(3), 187-193.
  • Bolat, B., Temur, G. T. and Gürler, H. (2016). Efficiency estimation of airports in Türkiye: Combined use of data envelopment analysis and artificial boundary networks. Ege Academic Review, 16(special issue):1-10.
  • Boussofiane, A., Dyson R.G. and Thanassoulis E. (1991). Applied Data Envelopment Analysis. European Journal Of Operational Research, vol 52, no.1, syf.1-15.
  • Charnes, A., Cooper, W.W. and Rhodes, E.L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444.
  • Charnes, A., Cooper, W.W., Lewin, A.Y. and Seiford, L. M. (1994). Data Envelopment Analysis: Theory, Methodology and Application. Kluwer Academic Publisher, Boston, USA.
  • Chiou Y.C., Lan L.W. and Yen B.T.H. (2012). Route-based data envelopment analysis models. Transportation Research Part E: Logistics and Transportation Review, Volume 48, Issue 2, Pages 415-425, ISSN 1366-5545.
  • Çınaroğlu E. and Avcı T. (2017). Comparison of domestic and international flight performances of major airports operating in Turkey, Busıness & Management Studıes: An Internatıonal Journal, 5(4): 55-75
  • Dyson, R.G., Thanassoulis, E. and Boussofiane, A. (1990). A DEA Tutorial, Wawick Business School,
  • Fernandes E and Pacheco R.R (2002). Efficient Use of Airport Capacity. Transportation Research Part A: Policy and Practice 36(3): 225-238.
  • Gadepalli R. and Rayaprolu S. (2020). Factors affecting performance of urban bus transport systems in India: A Data Envelopment Analysis (DEA) based approach. Transportation Research Procedia, Volume 48, Pages 1789-1804, ISSN 2352-1465.
  • Gillen, D., and Lall, A. (1997). Developing airport productivity and performance measures: an application of data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 33(4), 261- 273.
  • Hokey M. and Seong-Jong J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis, Journal of Air Transport Management, Volume 52, Pages 99-110, ISSN 0969-6997.
  • Kıyıldı, R. and Karaşahin, M. (2009). Evaluation of infrastructure performance of airports in Turkey through data envelopment analysis. Süleyman Demirel University Journal of Institute of Science and Technology, 10(3): 391-397.
  • Kottas, A.T., Madas, A. M. (2018), Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants, Journal of Air Transport Management, Volume 70, Pages 1-17, ISSN 0969-6997.
  • Kuah C. T., Wong K.Y., and Behrouzi F. (2010). A review on Data Envelopment Analysis (DEA). Fourth Asia International Conference on Mathematical / Analytical Modelling and Computer.
  • Lo Storto, C. and Evangelista P. (2023). Infrastructure efficiency, logistics quality and environmental impact of land logistics systems in the EU: A DEA-based dynamic mapping. Research in Transportation Business & Management, Volume 46, 100814, ISSN 2210-5395.
  • Lu W., Park S.H, Huang T. and Yeo G.T. (2019). An analysis for Chinese airport efficiency using weighted variables and adopting CFPR. The Asian Journal of Shipping and Logistics, Volume 35, Issue 4, Pages 230-242, ISSN 2092-5212,
  • Martin, J., and Roman, C. (2001). An application of DEA to measure the efficiency of Spanish Airport priority to privatization. Journal of Air Transport Management, 17, 149-157.
  • Montoya-Quintero, D. M., Larrea-Serna, O. L., and Jiménez-Builes, J. A. (2022). Evaluation of the efficiency of regional airports using Data Envelopment Analysis. Informatics, 9(4), 90.
  • Ömürbek, N., Demirgubuz, M. and Tunca, M. (2013). The use of data envelopment analysis in performance measurement in the service sector: an application on airports. Süleyman Demirel University Visionary Magazine,4(9): 21-43.
  • Özsoy, V. and Örkcü H. (2021). Structural and operational management of Turkish airports: A bootstrap data envelopment analysis of efficiency. Util. Policy 69, 101180.
  • Peker, İ. and Baki, B. (2009). An efficiency measurement application in Turkish airports with data envelopment analysis. Çukuova Univesity Journal of the Institute of Social Sciences, 18 (2): 72-88.
  • Pels, E., Nijkamp, P., and Rietveld, P. (2001). Relative efficiency of European airports. Transport Policy, 8(3), 183- 192.
  • Sarkis, J. (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3), 335-351.
  • Park S.H., Pham T.Y. and Yeo G.T. (2018). The impact of ferry disasters on operational efficiency of the South Korean Coastal Ferry Industry: A DEA-Window Analysis. The Asian Journal of Shipping and Logistics, Volume 34, Issue 3, Pages 248-255, ISSN 2092-5212.
  • Uludağ, A.S. (2020). Measuring the productivity of selected airports in Turkey. Transportation Research Part E: Logistics and Transportation Review, Volume 141, 102020, ISSN 1366-5545.
  • URL1 (2024), Airports Council International-ACI Annual Report 2023, https://store.aci.aero/product/aci- annual-report-2023/03.09.2024
  • URL2 (2024) European Union Against Aircraft Nuisances (UECNA) Retrieved December 18, 2024, https://www.uecna.eu/wp-content/uploads/2024/06/UECNA-STATS-EUROPE-Synthesis-til-2023-with-2007- En-cours.pdf
  • URL3 (2018), Air transport statistics. Luxembourg: Eurostat. Retrieved February 14, 2018. http://ec.europa.eu/eurostat/statistics-explained/index. php/ Air_ transport_ statistics
  • Yoshida, Y. (2004). Endogenous-Weight TFP measurement: Methodology and its application to Japanese- Airport benchmarking. Transportation Research Part E: Logistics and Transportation Review, 40(2), 151-182.
  • Yu, M. M. (2004). Measuring physical efficiency of domestic airports in Taiwan with undesirable outputs and environmental factors. Journal of Air Transport Management, 10, 295-303.

Avrupa'daki Büyük Uluslararası Havalimanlarının Veri Zarflama Analizi ile Operasyonel Etkinliklerinin Değerlendirilmesi

Yıl 2025, Cilt: 9 Sayı: 2, 436 - 444, 28.06.2025

Hakan Kaya , Ahmet İlbaş

https://doi.org/10.30518/jav.1639240

Öz

Bu makale, MAXDEA 8 yazılımı kullanılarak çözülen Veri Zarfı Analizi (VZA) yöntemini kullanarak 2021-2023 döneminde 10 büyük Avrupa Uluslararası Havaalanının operasyonel etkinliği üzerinde hava lojistiği ve taşımacılığının etkisini incelemektedir.
Bu amaçla, havaalanı lojistiğinin operasyonel etkinliğini analiz etmede kullanılan girdi ve çıktı değişkenlerini belirlemek için bir literatür taraması yapılmıştır. Bu çalışmada, girdi değişkenleri olarak havaalanının alanı, kargo terminali alanı, yolcu terminali sayısı ve pist sayısı, çıktı değişkenleri olarak uçuş sayısı, yolcu sayısı ve kullanılan kargo miktarı verileri kullanılmıştır. VZA modeli, çıktı odaklı maksimizasyon açısından en verimli sonuçları sağlar. Her havaalanının performansı diğerleriyle karşılaştırılır ve her havaalanı için verimlilik oranı değerlendirilir. Çalışmada, etkin olan havaalanları ve diğerlerine göre referans noktaları belirlenmiş ve etkin olmayan havaalanlarının çıktılarını iyileştirmek için ne kadar iyileştirmeye ihtiyaç duydukları değerlendirilmiştir.
Bu uygulama sonucunda havalimanlarının operasyonel etkinliğinin hava lojistiği ve taşımacılık faaliyetlerine göre, hangi havaalanlarının etkin olduğu veya olmadığı sonucuna varılmıştır. Bu çalışma sonucunda 2021-2023 döneminde 10 büyük uluslararası havalimanından 8'inin operasyonel verimliliğinin etkin olduğu, bunlardan sadece 2'sinin (Paris Charles de Gaulle, Madrid) etkin olmadığı ortaya çıkmıştır. Aynı girdi miktarlarıyla potansiyellerini daha iyi kullanarak daha fazla çıktı üretebilecekken, etkin olmayan iki havaalanı daha az çıktı üretmişlerdir.

Anahtar Kelimeler

Lojistik Havayolu Taşımacılığı Veri Zarflama Analizi Lojistik Operasyonel Etkinlik Havaalanı Yönetimi

Kaynakça

  • Adler, N. and Berechman, J. (2001). Measuring airport quality from the airlines’ viewpoint: An application of data envelopment analysis. Transport Policy, 8 (3), 171–181.
  • Altın, F. G., Karaatlı, M. and Budak, I. (2017). Evaluation of Europe's 20 largest airports with multi-criteria decision-making methods and data envelopment analysis. Süleyman Demirel University Journal of the Faculty of Economics and Administrative Sciences, 22(4):1049-1064
  • Asker, V. and Battal, Ü. (2017), Operatıonal effıcıency measurement at selected aırports. International Journal of Management Economics and Business, ICMEB17 Special Issue: 351-368
  • Avcı, T. and Aktaş, M. (2015), Evaluation of the performance of airports operating in Türkiye. International Journal of Alanya Business Faculty,7(3): 67-77.
  • Banker, R.D., Charnes, A. and Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30, 1984: 1085.
  • Barbara T.H. Yen, Jun-Sheng Li (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach, Transportation Research Part E: Logistics and Transportation Review, Volume 162, 102748, ISSN 1366-5545.
  • Barros, C. and Dieke, P. (2007). Performance evaluation of Italian airports: A data envelopment analysis. Journal of Air Transport Management - J Air Transp Manag. 13. 184-191. 10.1016/j.jairtraman.2007.03.001.
  • Bazargan, M., and Vasigh, B. (2003). Size versus efficiency: a case study of US commercial airports. Journal of Air Transport Management, 9(3), 187-193.
  • Bolat, B., Temur, G. T. and Gürler, H. (2016). Efficiency estimation of airports in Türkiye: Combined use of data envelopment analysis and artificial boundary networks. Ege Academic Review, 16(special issue):1-10.
  • Boussofiane, A., Dyson R.G. and Thanassoulis E. (1991). Applied Data Envelopment Analysis. European Journal Of Operational Research, vol 52, no.1, syf.1-15.
  • Charnes, A., Cooper, W.W. and Rhodes, E.L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444.
  • Charnes, A., Cooper, W.W., Lewin, A.Y. and Seiford, L. M. (1994). Data Envelopment Analysis: Theory, Methodology and Application. Kluwer Academic Publisher, Boston, USA.
  • Chiou Y.C., Lan L.W. and Yen B.T.H. (2012). Route-based data envelopment analysis models. Transportation Research Part E: Logistics and Transportation Review, Volume 48, Issue 2, Pages 415-425, ISSN 1366-5545.
  • Çınaroğlu E. and Avcı T. (2017). Comparison of domestic and international flight performances of major airports operating in Turkey, Busıness & Management Studıes: An Internatıonal Journal, 5(4): 55-75
  • Dyson, R.G., Thanassoulis, E. and Boussofiane, A. (1990). A DEA Tutorial, Wawick Business School,
  • Fernandes E and Pacheco R.R (2002). Efficient Use of Airport Capacity. Transportation Research Part A: Policy and Practice 36(3): 225-238.
  • Gadepalli R. and Rayaprolu S. (2020). Factors affecting performance of urban bus transport systems in India: A Data Envelopment Analysis (DEA) based approach. Transportation Research Procedia, Volume 48, Pages 1789-1804, ISSN 2352-1465.
  • Gillen, D., and Lall, A. (1997). Developing airport productivity and performance measures: an application of data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 33(4), 261- 273.
  • Hokey M. and Seong-Jong J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis, Journal of Air Transport Management, Volume 52, Pages 99-110, ISSN 0969-6997.
  • Kıyıldı, R. and Karaşahin, M. (2009). Evaluation of infrastructure performance of airports in Turkey through data envelopment analysis. Süleyman Demirel University Journal of Institute of Science and Technology, 10(3): 391-397.
  • Kottas, A.T., Madas, A. M. (2018), Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants, Journal of Air Transport Management, Volume 70, Pages 1-17, ISSN 0969-6997.
  • Kuah C. T., Wong K.Y., and Behrouzi F. (2010). A review on Data Envelopment Analysis (DEA). Fourth Asia International Conference on Mathematical / Analytical Modelling and Computer.
  • Lo Storto, C. and Evangelista P. (2023). Infrastructure efficiency, logistics quality and environmental impact of land logistics systems in the EU: A DEA-based dynamic mapping. Research in Transportation Business & Management, Volume 46, 100814, ISSN 2210-5395.
  • Lu W., Park S.H, Huang T. and Yeo G.T. (2019). An analysis for Chinese airport efficiency using weighted variables and adopting CFPR. The Asian Journal of Shipping and Logistics, Volume 35, Issue 4, Pages 230-242, ISSN 2092-5212,
  • Martin, J., and Roman, C. (2001). An application of DEA to measure the efficiency of Spanish Airport priority to privatization. Journal of Air Transport Management, 17, 149-157.
  • Montoya-Quintero, D. M., Larrea-Serna, O. L., and Jiménez-Builes, J. A. (2022). Evaluation of the efficiency of regional airports using Data Envelopment Analysis. Informatics, 9(4), 90.
  • Ömürbek, N., Demirgubuz, M. and Tunca, M. (2013). The use of data envelopment analysis in performance measurement in the service sector: an application on airports. Süleyman Demirel University Visionary Magazine,4(9): 21-43.
  • Özsoy, V. and Örkcü H. (2021). Structural and operational management of Turkish airports: A bootstrap data envelopment analysis of efficiency. Util. Policy 69, 101180.
  • Peker, İ. and Baki, B. (2009). An efficiency measurement application in Turkish airports with data envelopment analysis. Çukuova Univesity Journal of the Institute of Social Sciences, 18 (2): 72-88.
  • Pels, E., Nijkamp, P., and Rietveld, P. (2001). Relative efficiency of European airports. Transport Policy, 8(3), 183- 192.
  • Sarkis, J. (2000). An analysis of the operational efficiency of major airports in the United States. Journal of Operations Management, 18(3), 335-351.
  • Park S.H., Pham T.Y. and Yeo G.T. (2018). The impact of ferry disasters on operational efficiency of the South Korean Coastal Ferry Industry: A DEA-Window Analysis. The Asian Journal of Shipping and Logistics, Volume 34, Issue 3, Pages 248-255, ISSN 2092-5212.
  • Uludağ, A.S. (2020). Measuring the productivity of selected airports in Turkey. Transportation Research Part E: Logistics and Transportation Review, Volume 141, 102020, ISSN 1366-5545.
  • URL1 (2024), Airports Council International-ACI Annual Report 2023, https://store.aci.aero/product/aci- annual-report-2023/03.09.2024
  • URL2 (2024) European Union Against Aircraft Nuisances (UECNA) Retrieved December 18, 2024, https://www.uecna.eu/wp-content/uploads/2024/06/UECNA-STATS-EUROPE-Synthesis-til-2023-with-2007- En-cours.pdf
  • URL3 (2018), Air transport statistics. Luxembourg: Eurostat. Retrieved February 14, 2018. http://ec.europa.eu/eurostat/statistics-explained/index. php/ Air_ transport_ statistics
  • Yoshida, Y. (2004). Endogenous-Weight TFP measurement: Methodology and its application to Japanese- Airport benchmarking. Transportation Research Part E: Logistics and Transportation Review, 40(2), 151-182.
  • Yu, M. M. (2004). Measuring physical efficiency of domestic airports in Taiwan with undesirable outputs and environmental factors. Journal of Air Transport Management, 10, 295-303.
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Hava Taşımacılığı ve Nakliye Hizmetleri
Bölüm Araştırma Makaleleri
Yazarlar

Hakan Kaya 0000-0003-1512-8739

Ahmet İlbaş 0000-0002-1786-613X

Yayımlanma Tarihi 28 Haziran 2025
Gönderilme Tarihi 13 Şubat 2025
Kabul Tarihi 22 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 2

Kaynak Göster

APA Kaya, H., & İlbaş, A. (2025). Evaluation of Operational Performance of Major European International Airports with Data Envelopment. Journal of Aviation, 9(2), 436-444. https://doi.org/10.30518/jav.1639240
 Kapak Resmi İndir

Journal of Aviation - JAV 

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