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

Yıl 2024, Cilt: 17 Sayı: 1, 45 - 67, 30.04.2024

Nagihan Memiş Gül Gökay Emel

https://doi.org/10.37093/ijsi.1277040

Öz

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.

Anahtar Kelimeler

Network Data Envelopment Analysis Airport Efficiency Cross-Efficiency Measurement

Etik Beyan

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

Destekleyen Kurum

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

Kaynakça

  • 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
  • Karaoğlu, M. (2014). Evaluation of Turkish airports efficiencies using data envelopment analysis. In R. Banker, A. Emrouznejad, H. Bal, İ. Alp, & M. A. Cengiz (Eds.), Data Envelopment Analysis and Performance Measurement: Proceedings of the 11th International Conference of DEA (pp. 195–200). https://doi.org/10.13140/RG.2.1.3353.2966
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İki Aşamalı Ağ Veri Zarflama Analizinde Çapraz Etkinlik Ölçümü: Türkiye Havalimanları Uygulaması

Yıl 2024, Cilt: 17 Sayı: 1, 45 - 67, 30.04.2024

Nagihan Memiş Gül Gökay Emel

https://doi.org/10.37093/ijsi.1277040

Öz

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.

Anahtar Kelimeler

Ağ Veri Zarflama Analizi Havalimanı Etkinliği Çapraz Etkinlik Ölçümü

Etik Beyan

Bu çalışmada etik ilke ve standartlara uyulduğu beyan edilmiştir.

Destekleyen Kurum

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

Kaynakça

  • 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
  • Karaoğlu, M. (2014). Evaluation of Turkish airports efficiencies using data envelopment analysis. In R. Banker, A. Emrouznejad, H. Bal, İ. Alp, & M. A. Cengiz (Eds.), Data Envelopment Analysis and Performance Measurement: Proceedings of the 11th International Conference of DEA (pp. 195–200). https://doi.org/10.13140/RG.2.1.3353.2966
  • Kıyıldı, R. K., & Karaşahin, M. (2006). Türkiye’deki hava alanlarının veri zarflama analizi ile altyapı performansının değerlendirilmesi. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 10(3), 391–397. https://doi.org/10.19113/sdufbed.16973
  • Koçak, H. (2011). Efficiency examination of Turkish airports with DEA approach. International Business Research, 4(2), 204–209. https://doi.org/10.5539/ibr.v4n2p204
  • Köçken, K., Timor, M., & Karakaplan, M. U. (2022). COVID-19 Pandemisi öncesinde ve pandemi döneminde Türkiye’deki havalimanı etkinliklerinin üç aşamalı veri zarflama analizi ile belirlenmesi. Avrupa Bilim ve Teknoloji Dergisi, 35, 643–652. https://doi.org/10.31590/ejosat.1085597
  • Lee, M. J., & Kim, C. (2018). A network DEA aeronautical and non-aeronautical production model: An application to South Korea airports. Journal of Economic Structures, 7(1), 1–12. https://doi.org/10.1186/s40008-018-0130-2
  • Li, Y., Wang, Y., & Cui, Q. (2015). Evaluating airline efficiency: An application of Virtual Frontier Network SBM. Transportation Research Part E: Logistics and Transportation Review, 81, 1–17. https://doi.org/10.1016/j.tre.2015.06.006
  • 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. https://doi.org/10.1016/j.jairtraman.2015.12.001
  • lo Storto, C. (2018). Ownership structure and the technical, cost, and revenue efficiency of Italian airports. Utilities Policy, 50, 175–193. https://doi.org/10.1016/j.jup.2018.01.003
  • Lovell, C. A. K. (1993). Production frontiers and productive efficiency. In H. O. Fried, C. A. K. Lovell, & S. S. Schmidt (Eds.), The measurement of productive efficiency: Techniques and applications (pp. 3–67). Oxford University Press.
  • Lozano, S., Gutiérrez, E., & Moreno, P. (2013). Network DEA approach to airports performance assessment considering undesirable outputs. Applied Mathematical Modelling, 37(4), 1665–1676. https://doi.org/10.1016/j.apm.2012.04.041
  • Lu, W.-M., Hung, S.-W., Kweh, Q. L., Wang, W.-K., & Lu, E.-T. (2014). Production and marketing efficiencies of the U.S. airline industry: A two-stage network DEA approach. In W. Cook & J. Zhu (Eds.), Data envelopment analysis. international series in operations research & management science (Vol. 208; pp. 537–568). Springer New York LLC. https://doi.org/10.1007/978-1-4899-8068-7_21
  • Maghbouli, M., Amirteimoori, A., & Kordrostami, S. (2014). Two-stage network structures with undesirable outputs: A DEA based approach. Measurement, 48(1), 109–118. https://doi.org/10.1016/j.measurement.2013.10.032
  • Mallikarjun, S. (2015). Efficiency of US airlines: A strategic operating model. Journal of Air Transport Management, 43, 46–56. https://doi.org/10.1016/j.jairtraman.2014.12.004
  • Orhan, M. (2019). Türkiye’deki havalimanlarının etkinliklerinin veri zarflama analizi ile değerlendirilmesi. Turkish Studies-Economics, Finance, Politics, 14(4), 1455–1472. https://doi.org/10.29228/TurkishStudies.39243
  • Ömürbek, N., Öksüz Demirgubuz, M., & Tunca, M. Z. (2013). Hizmet sektöründe performans ölçümünde veri zarflama analizinin kullanımı: havalimanları üzerine bir uygulama. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 4(9), 21–43. https://dergipark.org.tr/tr/pub/vizyoner/issue/23008/246064
  • Özsoy, V. S., & Örkcü, H. H. (2021). Structural and operational management of Turkish airports: a bootstrap data envelopment analysis of efficiency. Utilities Policy, 69, 101180. https://doi.org/10.1016/j.jup.2021.101180
  • Öztürk, E., Durak, H. A., & Bal, H. (2014). Evaluation of Turkish airport efficiencies using data envelopment analysis and Moora Method. In M. A. C. Rajiv Banker, Ali Emrouznejad, Hasan Bal, Ihsan Alp (Eds.), Data Envelopment Analysis and Performance Measurement: Proceedings of the 11th International Conference of DEA (pp. 189–194). https://doi.org/10.13140/RG.2.1.3353.2966
  • Peker, İ., & Baki, B. (2009). Veri zarflama analizi ile Türkiye havalimanlarında bir etkinlik ölçümü uygulaması. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18(2), 72–88. https://dergipark.org.tr/tr/pub/cusosbil/issue/4382/60125
  • Sarkis, J. (2007). Preparing your data for DEA. In Modeling data irregularities and structural complexities in Data Envelopment Analysis (pp. 305–320). Springer US. https://doi.org/10.1007/978-0-387-71607-7_17
  • Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 U.S. commercial banks. Management Science, 45(9), 1270–1288. https://doi.org/10.1287/mnsc.45.9.1270
  • Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. New Directions for Program Evaluation, 1986(32), 73–105. https://doi.org/10.1002/ev.1441
  • Shao, Y., & Sun, C. (2016). Performance evaluation of China’s air routes based on network data envelopment analysis approach. Journal of Air Transport Management, 55, 67–75. https://doi.org/10.1016/j.jairtraman.2016.01.006
  • Tavassoli, M., Faramarzi, G. R., & Farzipoor Saen, R. (2014). Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input. Journal of Air Transport Management, 34, 146–153. https://doi.org/10.1016/j.jairtraman.2013.09.001
  • Ulutaş, B., & Ulutaş, B. (2009, July 29–August 1). An analytic network process combined data envelopment analysis methodology to evaluate the performance of airports in Turkey [Paper presentation]. 10th International Symposium on the Analytic Hierarchy Process. University of Pittsburgh, Pennsylvania, United States. https://www.isahp.org/2009Proceedings/Final_Papers/90_Ulutas_DEA_ANP_TurkishAirport_Performance_REV_FIN.pdf
  • Ülkü, T. (2015). A comparative efficiency analysis of Spanish and Turkish airports. Journal of Air Transport Management, 46, 56–68. https://doi.org/10.1016/j.jairtraman.2015.03.014
  • Wanke, P. F. (2013). Physical infrastructure and flight consolidation efficiency drivers in Brazilian airports: A two-stage network-DEA approach. Journal of Air Transport Management, 31, 1–5. https://doi.org/10.1016/j.jairtraman.2012.09.001
  • Yavuz, İ. (2003). Verimlilik ve etkinlik ölçümüne yeni yaklaşımlar ve illere göre imalat sanayiinde etkinlik karşılaştırmaları (Yayın No. 667). Milli Prodüktivite Merkez Yayınları.
  • Yazgan, A. E., & Karkacier, O. (2015). Veri Zarflama Analizi ile etkinlik ölçümleri ve havalimanı işletmeciliği sektöründe bir uygulama. Uluslararası Alanya İşletme Fakültesi Dergisi, 7(2), 15–28. https://dergipark.org.tr/tr/pub/uaifd/issue/21603/232022
  • Yu, M.-M. (2010). Assessment of airport performance using the SBM-NDEA model. Omega, 38(6), 440–452. https://doi.org/10.1016/j.omega.2009.11.003
  • Zhu, J. (2011). Airlines performance via two-stage network DEA approach. Journal of CENTRUM Cathedra: The Business and Economics Research Journal, 4(2), 260–269. https://papers.ssrn.com/abstract=1931862
  • Zhu, J. (2014). Quantitative models for performance evaluation and benchmarking. Springer International Publishing. https://doi.org/10.1007/978-3-319-06647-9
Toplam 56 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonometrik ve İstatistiksel Yöntemler, Nicel Karar Yöntemleri
Bölüm Makaleler
Yazarlar

Nagihan Memiş 0000-0003-3423-0835

Gül Gökay Emel 0000-0002-2921-1368

Yayımlanma Tarihi 30 Nisan 2024
Gönderilme Tarihi 4 Nisan 2023
Yayımlandığı Sayı Yıl 2024 Cilt: 17 Sayı: 1

Kaynak Göster

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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