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Cross Efficiency Measurement in Two-Stage Network Data Envelopment Analysis: An Application of the Airports in Türkiye

Year 2024, Volume: 17 Issue: 1, 45 - 67, 30.04.2024
https://doi.org/10.37093/ijsi.1277040

Abstract

This study deals with measuring the overall efficiency of a system by breaking it down into its constituent sub-processes. The airline sector, which is an important service sector for Türkiye, has been chosen as the application area. When the relevant literature is examined, it is seen that the production process in efficiency studies in the Turkish airline sector is carried out with traditional Data Envelopment Analysis (DEA) by considering the efficiency process as a single stage. This study aimed to measure the overall efficiency of airports in more detail on the basis of two sub-activities, operational and revenue efficiency, using Network Data Envelopment Analysis (NDEA). Kao and Hwang’s (2008) Relational Network Data Envelopment Analysis model was used in the efficiency analysis. In ranking efficiency values, peer evaluation was used based on Kao and Liu’s (2019) Cross-Efficiency Measurement approach. In the study, 27 airports operated by the State Airports Authority (DHMİ) with an annual passenger traffic of over 400.000 as of 2019 were examined. In the analysis, it was found that while an airport with relative overall efficiency could not be identified, some airports were partially effective in terms of sub-processes.

Ethical Statement

The authors declare that this article complies with ethical standards and rules.

Supporting Institution

No financial support was received from any person or institution for the study.

References

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İki Aşamalı Ağ Veri Zarflama Analizinde Çapraz Etkinlik Ölçümü: Türkiye Havalimanları Uygulaması

Year 2024, Volume: 17 Issue: 1, 45 - 67, 30.04.2024
https://doi.org/10.37093/ijsi.1277040

Abstract

Bu çalışma, bir sistemin genel etkinliğinin sisteminin alt süreçlere ayrıştırılarak ölçülmesini ele almaktadır. Uygulama alanı olarak Türkiye için önemli bir hizmet sektörü olan havayolu sektörü seçilmiştir. Yazın incelendiğinde, Türk havayolu sektöründe yapılan etkinlik çalışmalarında üretim sürecinin tek aşamalı olarak ele alınarak geleneksel Veri Zarflama Analizi (VZA) ile gerçekleştirildiği görülmektedir. Bu çalışmada ise havalimanlarının genel etkinliğinin, operasyonel ve gelir etkinliği olmak üzere iki alt etkinlik bazında, daha ayrıntılı bir şekilde Ağ Veri Zarflama Analizi ile ölçülmesi amaçlanmıştır. Etkinlik analizinde Kao ve Hwang’ın (2008) İlişkisel Ağ Veri Zarflama Analizi modeli kullanılmıştır. Etkinlik değerlerinin sıralanmasında ise Kao ve Liu’nun (2019) Çapraz Etkinlik Ölçümü kullanılarak akran değerlendirmeden yararlanılmıştır. Çalışmada, Devlet Hava Meydanları İşletmesi tarafından işletilen ve 2019 yılı itibarı ile yıllık yolcu trafiği 400.000’in üzerinde olan 27 havalimanı incelenmiştir. Yapılan analizlerde, göreli tam etkinliğe sahip bir havalimanı tespit edilememişken, bazı havalimanlarının alt süreçler bakımından kısmen etkin olduğu bulgusuna ulaşılmıştır.

Ethical Statement

Bu çalışmada etik ilke ve standartlara uyulduğu beyan edilmiştir.

Supporting Institution

Yazarlar bu çalışma için herhangi bir finansal destek almadıklarını beyan etmiştir.

References

  • Adler, N., Liebert, V., & Yazhemsky, E. (2013). Benchmarking airports from a managerial perspective. Omega, 41(2), 442–458. https://doi.org/10.1016/j.omega.2012.02.004
  • Altın, F. G., Karaatlı, M., & Budak, İ. (2017). Avrupa’nın en büyük 20 havalimanının çok kriterli karar verme yöntemleri ve veri zarflama analizi ile değerlendirilmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(4), 1049–1064. https://dergipark.org.tr/tr/pub/sduiibfd/issue/52995/704359
  • Ar, İ. M. (2012). Türkiye’deki havalimanlarının etkinliklerindeki değişimin incelenmesi: 2007-2011 dönemi için Malmquist-TFV Endeksi uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 26(3–4), 143–160. https://dergipark.org.tr/tr/pub/atauniiibd/issue/2707/35812
  • Asker, V. (2016). The measurement of airports operational effectiveness: An application of the major 10 airports in Turkey. Transport & Logistics: the International Journal, 16(41), 1–9.
  • Asker, V., & Battal, Ü. (2017). Operational efficiency measurement at selected airports. International Journal of Management Economics and Business, ICMEB17 Special Issue, 351–368. https://dergipark.org.tr/en/download/article-file/1124049
  • Avcı, T., & Aktaş, M. (2016). Türkiye’de faaliyet gösteren havalimanlarının performanslarının değerlendirilmesi. Uluslararası Alanya İşletme Fakültesi Dergisi, 7(3), 67–77. https://dergipark.org.tr/en/download/article-file/201849
  • Battal, Ü. (2020). Avrupadaki havaalanı grup şirketlerinin finansal performanslarının ölçülmesi: Veri Zarflama Analizi Yöntemi. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(1), 171–184. https://doi.org/10.25287/ohuiibf.622991
  • Bolat, B., Temur, G. T., & Gürler, H. (2016). Türkiye deki havalimanlarının etkinlik tahmini: Veri zarflama analizi ve yapay sinir ağlarının birlikte kullanımı. Ege Academic Review, 16(OZEL), 1–10. https://doi.org/10.21121/eab.2016OZEL24424
  • Charnes, A., Cooper, W. W., Golany, B., Seiford, L., & Stutz, J. (1985). Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of Econometrics, 30(1), 91-107. https://doi.org/10.1016/0304-4076(85)90133-2
  • Chiou, Y.-C., & Chen, Y.-H. (2006). Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 42(2), 116–127. https://doi.org/10.1016/j.tre.2005.09.005
  • Çınaroğlu, E., & Avcı, T. (2017). Türkiye’de faaliyette bulunan büyük havalimanlarının iç ve dış hat performanslarının karşılaştırılması. Business & Management Studies: An International Journal, 5(4), 55–75. https://doi.org/10.15295/bmij.v5i4.184
  • Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4. https://doi.org/10.1016/j.omega.2013.09.004
  • Devlet Hava Meydanları İşletmesi Genel Müdürlüğü [DHMİ]. (2020a, Mayıs). 2019 Havayolu Sektör Raporu. Strateji Geliştirme Daire Başkanlığı. https://www.dhmi.gov.tr/Lists/HavaYoluSektorRaporlari/Attachments/13/2019 Havayolu Sektör Raporu.pdf
  • Devlet Hava Meydanları İşletmesi Genel Müdürlüğü [DHMİ]. (2020b, Mayıs). 2019 Faaliyet Raporu. https://www.dhmi.gov.tr/Lists/FaaliyetRaporlari/Attachments/20/49453_1_DHMI2019FaaliyetRaporu(pdf)_FaaliyetRaporu_2019webformati.pdf
  • Doyle, J., & Green, R. (1994). Efficiency and cross-efficiency in DEA derivations, meanings and uses. Journal of the Operational Research Society, 45(5), 567–578. https://doi.org/10.1057/jors.1994.84
  • European Comission. (2005). Community guidelines on financing of airports and start-up aid to airlines departing from regional airports (2005/C 312/01). Official Journal of the European Union. https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX%3A52005XC1209%2803%29
  • Färe, R., & Grosskopf, S. (1996). Productivity and intermediate products: A frontier approach. Economics Letters, 50(1), 65–70. https://doi.org/10.1016/0165-1765(95)00729-6
  • Färe, R., Grosskopf, S., & Whittaker, G. (2007). Network DEA. In J. Zhu & W. D. Cook (Eds.), Modeling data irregularities and structural complexities in data envelopment analysis (pp. 209-240). Springer US. https://doi.org/10.1007/978-0-387-71607-7_12
  • Gramani, M. C. N. (2012). Efficiency decomposition approach: A cross-country airline analysis. Expert Systems with Applications, 39(5), 5815–5819. https://doi.org/10.1016/j.eswa.2011.11.086
  • Güner, S., Ergüzel, O. Ş., & Cebeci, H. İ. (2019). Uluslararası havalimanlarının operasyonel etkinliğinin değerlendirilmesi: Bölgesel bir karşılaştırma. Alphanumeric Journal, 7(3), 37–44. https://doi.org/10.17093/alphanumeric.499533
  • Halkos, G. E., Tzeremes, N. G., & Kourtzidis, S. A. (2014). A unified classification of two-stage DEA models. Surveys in operations research and management science, 19(1), 1-16. https://doi.org/10.1016/j.sorms.2013.10.001
  • Hong, J.-D., & Jeong, K.-Y. (2019). Combining data envelopment analysis and multi-objective model for the efficient facility location–allocation decision. Journal of Industrial Engineering International, 15(2), 315–331. https://doi.org/10.1007/s40092-018-0294-2
  • Kao, C. (2017). Network data envelopment analysis (Vol. 240). Springer International Publishing. https://doi.org/10.1007/978-3-319-31718-2
  • Kao, C., & Hwang, S.-N. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185(1), 418–429. https://doi.org/10.1016/j.ejor.2006.11.041
  • Kao, C., & Liu, S.-T. (2019). Cross efficiency measurement and decomposition in two basic network systems. Omega, 83, 70–79. https://doi.org/10.1016/j.omega.2018.02.004
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There are 56 citations in total.

Details

Primary Language Turkish
Subjects Econometric and Statistical Methods, Quantitative Decision Methods
Journal Section Articles
Authors

Nagihan Memiş 0000-0003-3423-0835

Gül Gökay Emel 0000-0002-2921-1368

Publication Date April 30, 2024
Submission Date April 4, 2023
Published in Issue Year 2024 Volume: 17 Issue: 1

Cite

APA Memiş, N., & Gökay Emel, G. (2024). İki Aşamalı Ağ Veri Zarflama Analizinde Çapraz Etkinlik Ölçümü: Türkiye Havalimanları Uygulaması. International Journal of Social Inquiry, 17(1), 45-67. https://doi.org/10.37093/ijsi.1277040

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