Araştırma Makalesi
BibTex RIS Kaynak Göster

EVALUATION OF TOP 20 AIRPORTS IN THE EUROPE ACCORDING TO MULTI CRITERIA DECISION-MAKING METHODS AND DATA ENVELOPMENT ANALYSIS

Yıl 2017, Cilt: 22 Sayı: 4, 1049 - 1064, 30.10.2017

Fatma Gul Altin , Meltem Karaatlı , İbrahim Budak

Öz

In this study, which deals with the biggest 20 airports in term of the number of passengers in Europe, the efficiency of airports was evaluated by using Multi Criteria Decision Making Methods and Data Envelopment Analysis. Based on the years 2010-2015, the criteria related to 20 airports were firstly weighted by the Entropy method and then the performance ranking was carried out by COPRAS and Grey Relational Analysis methods. In the study, criteria affecting performance were determined as; the number of passengers, the number of terminals, the parking capacity, the number of runways, the distance of the airport to the city center, the number of exit doors and the number of aircraft desks. In the Data Envelopment Analysis, the number of terminals, the parking capacity, the number of runways, the distance of the airport to the city center, the number of exit doors and the number of aircraft desks were used as input variables; the number of passengers was used as output variable.

As a result of the study, "Atatürk International Airport" ranks as 11th while "Madrid Barajas International Airport", "Frankfurt am Main International Airport" and "Charles de Gaulle International Airport” were the top three in COPRAS method. The "Atatürk International Airport" ranks as 14th while “Madrid Barajas International Airport", "Frankfurt am Main International Airport" and "London Gatwick Airport" were the top three in the Gray Relational Analysis method. In both ranking methods, "International Sabiha Gökçen Airport" is at the last line. According to the CCR model in the Data Envelopment Analysis 10 airports have been determined as effective.

Anahtar Kelimeler

Multi Criteria Decision Making Grey Relational Analysis Entropy COPRAS Data Envelopment Analysis Airport

Kaynakça

  • AKSOY, E., Ömürbek, N. ve Karaatlı, M., (2015), “AHP Temelli Multımoora ve COPRAS Yöntemi İle Türkiye Kömür İşletmeleri’nin Performans Değerlendirmesi”, Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 33:4, 1-28.
  • AYDEMİR, M. Ve Demirci, m. K., (2005), “Son Dönemlerde Yaşanan Krizlerin İşletmeler Üzerindeki Olumlu Etkilerinin Analizi” Cumhuriyet Üniversitesi Sosyal Bilimler Dergisi, 29:1, 65-81.
  • BAKIRCI F., Eslamian Shiraz S. ve Sattary A., (2014), “BIST’da Demir, Çelik Metal Ana Sanayii Sektöründe Faaliyet Gösteren İşletmelerin Finansal Performans Analizi: VZA Süper Etkinlik ve TOPSIS Uygulaması” Ege Akademik Bakış, 14:1, 9-19.
  • BALTAZAR, M. E., Jardim, J., Alves, P. ve Silva, J. (2014), “Air Transport Performance and Efficiency: MCDA vs. DEA Approaches”, Procedia- Social and Behaviral Sciences, 111, 790-799.
  • BANKER R.D., Cooper W.W., Seiford L.M., Thrall R.M., Zhu J. (2004) “Returns to Scale in Different DEA Models”, European Journal of Operational Research, 154:2, 345-362.
  • BARROS, C. P., ve Dieke, P. U., (2007), “Performance Evaluation of Italian Airports: A Data Envelopment Analysis”, Journal of Air Transport Management, 13:4, 184-191.
  • CHANG, Y. H., Shao, P. C., ve Chen, H. J., (2015), “Performance Evaluation of Airport Safety Management Systems in Taiwan”, Safety Science, 75, 72-86.
  • CHARNES A., Cooper W.W., Rhodes E. (1978), “Measuring The Efficiency of Decision Making Units”, European Journal of Operational Research, 2:6, 429–444.
  • CHARNES A., Cooper W.W., Lewin A.Y., Seiford L. M. (1993) Data Envelopment Analysis, Theory, Methodology and Applications, Kluwer Academic Publishers, Boston/Dordrecht/London.
  • CHATTERJEE, P. ve Chakraborty, S., (2012), “Materials Selection Using COPRAS and COPRAS-G Methods”, International Journal of Materials and Structural Integrity, 6, S.2-4.
  • CHEN, T., Jın, Y., Qiu, X. ve Chen, X., (2014), “A Hybrid Fuzzy Evaluation Method For Safety Assessment of Food-Waste Feed Based On Entropy And The Analytic Hierarchy Process Methods”, Expert Systems with Applications, An International Journal, Science Direct, 41:16, 7328-7337.
  • COELLRI T., Rao D.S.P., O’Donnell C.J., Battese,G.E. (2005) An Introduction to Efficiency and Productivity Analysis, Second Edition, Springer Science Business Media Inc., New York.
  • DİNÇ, M., Haynes K. E. (1999) “Sources of Regional Inefficiency: An Integrated Shift-Share, Data Envelopment Analysis and Input- Output Approach”, The Analysis of Regional Science, 33:4, 469-489.
  • ERMETITA., Wardoyo, R., Hartati, S. ve Harjoko, A., (2012), “ELECTRE- Entropy Method in Group Decision Support System Model To Gene Mutation Detection”, International Journal of Advanced Research in Artificial Intelligence, Indonesia, 1:1, 58-63.
  • ERSÖZ, F., ve Kabak, M., (2010), “Savunma Sanayi Uygulamalarında Çok Kriterli Karar Verme Yöntemlerinin Literatür Araştırması”, Kara Harp Okulu, Savunma Bilimleri Enstitüsü, Savunma Bilimleri Dergisi, Ankara, 9:1, 97-125.
  • European Aviation Environmental Report (2016), https://ec.europa.eu/ transport/sites/transport/files/european- aviation-environmental-report-2016- 72dpi.pdf, 15.07.2017)
  • GOMES, L.F.A.M., Mattos Fernandes, J.E., Mello, J.C.C.B.S., (2014), “A Fuzzy Stochastic Approach to The Multicriteria Selection of An Aircraft for Regional Chartering”, Journal of Advanced Transportation, 48:3, 223- 237.
  • GÖKDALAY, M. H. ve Evren, G., (2009), “Havaalanlarının Performans Analizinde Bulanık Çok Ölçütlü Karar Verme Yaklaşımı”, İstanbul Teknik Üniversitesi Dergisi, İstanbul, 8:6, 157-168.
  • JANIC, M., (2015), “A Multi-Criteria Evaluation of Solutions and Alternatives For Matching Capacity to Demand In An Airport System: The Case of London”, Transportation Planning and Technology, 38:7, 709- 737.
  • KADZINSKI, M., Labijak, A., Napieraj, M., (2017), “Integrated Framework for Robustness Analysis Using Ratio-Based Efficiency Model With Application to Evaluation of Polish Airports”, Omega, 67, 1-18.
  • KARAATLI, M., Ömürbek, N., Budak, İ. ve Dağ, O., (2015), “Çok Kriterli Karar Verme Yöntemleri İle Yaşanabilir İllerin Sıralanması”, Selçuk Üniversitesi, Sosyal Bilimler Enstitüsü Dergisi, 33, 215-228.
  • KARAMI, A, Johansson, R., (2014), “Utilization Of Multi Attribute Decision Making Techniques To Integrate Automatic And Manual Ranking Of Options”, Journal of Informatıon Science And Engineering, 30, 519-534.
  • KAKLAUSKAS, A., Zavadskas, E. K., Raslanas, S., Ginevicius, R., Komka, A. ve Malinauskas, P., (2006), “Selection of Low-e Windows In Retrofit of Public Buildings By Applying Multiple Criteria Method COPRAS: A Lithuanian Case”, Energy and Buildings, Lithuania, 38:5, 454-462.
  • KAKLAUSKAS, A., Zavadskas, E. K. ve Trinkunas, V., (2007), “A Multiple Criteria Decision Support On-Line System For Construction”, Engineering Applications Of Artificial Intelligence, 20, 163-175.
  • KUO, M. S., ve Liang, G. S., (2011), “Combining VIKOR with GRA Techniques to Evaluate Service Quality of Airports Under Fuzzy Environment”, Expert Systems With Applications, 38:3, 1304-1312.
  • LEE, W. ve Lin, Y., (2011), “Evaluating and Ranking Energy Performance of Office Buildings Using Grey Relational Analysis”, Science Direct, 36:5, 2551-2556.
  • LIMA, M. G. ve Belderrain, M. C. N., (2016), “Structuring Multicriteria Model for Airports Selection for Cargo Airlines Exclusively”, Ingeniare. Revista Chilena de Ingenieria, 24:3, 465-479.
  • LIN, J. L. ve Lin, C. L., (2002), “The Use Ofthe Orthogonal Array With Grey Relational Analysis To Optimize The Electrical Discharge Machining Process With Multiple Performance Characteristics”, International Journal Of Machine Tool And Manufacturing, 42:2, 237-244.
  • LU, H. S., Chang, C. K., Hwang, N. C. ve Chung, C. T., (2009), “Grey Relational Analysis Coupled with Principal Component Analysis For Optimization Design of The Cutting Parameters In High-Speed End Milling”, Journal of Materials Processing Technology, 209:8, 3808- 3817.
  • MARTÍN, J. C., ve Román, C., (2006), “A Benchmarking Analysis of Spanish Commercial Airports. A Comparison Between SMOP and DEA Ranking Methods”, Networks and Spatial Economics, 6:2, 111-134.
  • NORESE, M.F. ve Carbone, V., (2014), “An Application of ELECTRE Tri to Support Innovation”, Journal of Multi-Criteria Decision Analysis, 21:1-2, 77-93.
  • ORUÇ, K.O., (2008), Veri Zarflama Analizi ile Bulanık Ortamda Etkinlik Ölçümleri ve Üniversitelerde Bir Uygulama, Yayınlanmamış Doktora Tezi, Süleyman Demirel Üniversitesi, Sosyal Bilimler Enstitüsü, Isparta.
  • ÖMÜRBEK, N., Demirgubuz Öksüz, M., Tunca, M. Z., (2013), “Hizmet Sektöründe performans Ölçümünde Veri Zarflama Analizinin Kullanımı: Havalimanları Üzerine Bir Uygulama”, Süleyman Demiral Üniversitesi Vizyoner Dergisi, 4:9, 21-43.
  • PALANIKUMAR, K., Karunamoorthy, L. ve Karthikeyan, R., (2006), “Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool”, Materials and Manufacturing Processes, 21:8, 846–852.
  • ROCHA, P.M., Barros, A.P., Silva, G.B. ve Costa, H.G., (2016), “Analysis of The Operational Performance of Brazilian Airport Terminals: A Multicriteria Approach with De Borda- AHP Integraation”, Journal of Air Transport Management, 51, 19-26.
  • SARSIN Kaya, D., (2016), Havayolu Yolcu Taşımacılığı Sektörü, Türkiye İş Bankası Yayınları.
  • SOFYALIOĞLU, Ç., (2011), “Süreç Hata Modu Etki Analizini Gri Değerlendirme Modeli”, Ege Üniversitesi, Ekonomi, İşletme, Uluslararası İlişkiler ve Siyaset Bilimi Dergisi, Ege Akademik Bakış, 11:1, 155-164.
  • ŞİŞMAN, B. ve Eleren, A., (2013),” En Uygun Otomobilin Gri İlişkisel Analiz ve ELECTRE Yöntemleri ile Seçimi”, Süleyman Demirel Üniversitesi, İ.İ.B.F. Dergisi, 18:3, 411-429.
  • TARNG, T. S., Juang, S. C. ve Chang C. H., (2002), “The Use of Grey Based Taguchi Methods To Determine Submerged Arc Welding Process Parameters In Hardfacing”, Journal of Materials Processing Technology, 128, 1-6.
  • ÖZDAĞOĞLU, A., (2013), “Çok Ölçütlü Karar Verme Modellerinde Normalizasyon Tekniklerinin Sonuçlara Etkisi: COPRAS Örneği”, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 8:2, 229-252.
  • ÜLKÜ, T., (2015), “A Comparative Efficiency Analysis of Spanish and Turkish Airports”, Journal of Air Transport Management, 46, 56-68.
  • WU, Z., Sun, J., Liang, L. ve Zha, Y., (2011), "Determination Of Weights For Ultimate Cross Efficiency Using Shannon Entropy", Expert Systems With Applications, 38, 5162-5165.
  • YUN Y.B., Nakayama H., Tanino T. (2004) “A Generalized Model For Data Envelopment Analysis”, European Journal of Operational Research, 157:1, 87-105.
  • ZAVADSKAS, E. K., Kaklauskas, A., Turskıs, Z. ve Tamosaitiene, J., (2008), “Contractor Selectıon Multı- Attrıbute Model Applynıg COPRAS Method with Grey Interval Numbers”, 20th EURO Mini Conference, ‘Continuous Optimization and Knowledge-Based Technologies’, Neringa, Lithuania, 241-247.
  • ZHAI, L., Khoo, L. ve Zhong, Z., (2009), “Design Concept Evaluation In Product Development Using Rough Sets and Grey Relation Analysis”, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 7072-7079.
  • ZHANG, H., Gu, C., Gu, L. ve Zhang, Y. (2011), "The Evaluation Of Tourism Destination Competitiveness By TOPSIS & Information Entropy E A Case In The Yangtze River Delta Of China", Tourism Management, 32, 443-451.
  • ZHOU, H., You, J. ve Lıu, H., (2016), “Failure Mode and Effect Analysis Using MULTIMOORA Method with Continuous Weighted Entropy Under Interval-Valued Intuitionistic Fuzzy Environment”, Springer, Berlin, s.1- 13.
  • Zolfani, S. H. ve Bahrami, M., (2014), “Investment Prioritizing In High Tech Industries Based On SWARA- COPRAS Approach”, Technological and Economic Development of Economy, Iran, 20:3, 534-553.
  • ZHU J. (2015) Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, Third Edition, Springer Science Business Media Inc., New York/Dordrecht/London.
  • (http://airportdatabase.net/all- airports.html, 14.05.2017).
  • (https://www.aci- europe.org/policy/position- papers.html?view=group&group=1&id=11, 15.07.2017).
  • (http://www.iata.org/pressroom/pr/Pag es/2016-12-08-01.aspx, 15.07.2017).

AVRUPA’NIN EN BÜYÜK 20 HAVALİMANININ ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİ VE VERİ ZARFLAMA ANALİZİ İLE DEĞERLENDİRİLMESİ

Yıl 2017, Cilt: 22 Sayı: 4, 1049 - 1064, 30.10.2017

Fatma Gul Altin , Meltem Karaatlı , İbrahim Budak

Öz

Bu çalışmada, Avrupa’nın yolcu sayısı bakımından en büyük 20 havalimanının performansları Çok Kriterli Karar Verme Yöntemleri ile sıralanmış ve Veri Zarflama Analizi yöntemiyle de etkinlikleri değerlendirilmiştir. 2010-2015 yılları esas alınarak, 20 havalimanına ilişkin kriterlerin öncelikle ENTROPI yöntemi ile ağırlıkları hesaplanmış, daha sonra COPRAS ve Gri İlişkisel Analiz yöntemleri ile de performans sıralaması yapılmıştır. Çalışmada, performansı etkileyen kriterler; yolcu sayısı, terminal sayısı, otopark kapasitesi, pist sayısı, havalimanının şehir merkezine uzaklığı, çıkış kapı sayısı ve uçak stand sayısı olarak belirlenmiştir. Veri Zarflama Analizinde ise terminal sayısı, otopark kapasitesi, pist sayısı, havalimanının şehir merkezine uzaklığı, çıkış kapı sayısı ve uçak stand sayısı girdi değişkeni olarak, yolcu sayısı çıktı değişkeni olarak kullanılmıştır.

Çalışma sonucunda, COPRAS yönteminde ilk üç sırada “Madrid Barajas International Airport”, “Frankfurt am Main International Airport” ve “Charles de Gaulle International Airport” havalimanları yer alırken, “Uluslararası Atatürk Havalimanı” on birinci sırada yer almıştır. Gri İlişkisel Analiz yönteminde ilk üç sırada “Madrid Barajas International Airport”, “Frankfurt am Main International Airport” ve “London Gatwick Airport” havalimanları yer alırken, “Uluslararası Atatürk Havalimanı” on dördüncü sırada yer almıştır. Her iki sıralama yönteminde son sırada “Uluslararası Sabiha Gökçen Havalimanı” yer almaktadır. Veri Zarflama Analizinde Charnes, Cooper ve Rhodes (CCR) modeline göre 10 havalimanının etkin olduğu sonucuna ulaşılmıştır.

Anahtar Kelimeler

Çok Kriterli Karar Verme Gri İlişkisel Analiz ENTROPI COPRAS Veri Zarflama Analizi Havalimanı

Kaynakça

  • AKSOY, E., Ömürbek, N. ve Karaatlı, M., (2015), “AHP Temelli Multımoora ve COPRAS Yöntemi İle Türkiye Kömür İşletmeleri’nin Performans Değerlendirmesi”, Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 33:4, 1-28.
  • AYDEMİR, M. Ve Demirci, m. K., (2005), “Son Dönemlerde Yaşanan Krizlerin İşletmeler Üzerindeki Olumlu Etkilerinin Analizi” Cumhuriyet Üniversitesi Sosyal Bilimler Dergisi, 29:1, 65-81.
  • BAKIRCI F., Eslamian Shiraz S. ve Sattary A., (2014), “BIST’da Demir, Çelik Metal Ana Sanayii Sektöründe Faaliyet Gösteren İşletmelerin Finansal Performans Analizi: VZA Süper Etkinlik ve TOPSIS Uygulaması” Ege Akademik Bakış, 14:1, 9-19.
  • BALTAZAR, M. E., Jardim, J., Alves, P. ve Silva, J. (2014), “Air Transport Performance and Efficiency: MCDA vs. DEA Approaches”, Procedia- Social and Behaviral Sciences, 111, 790-799.
  • BANKER R.D., Cooper W.W., Seiford L.M., Thrall R.M., Zhu J. (2004) “Returns to Scale in Different DEA Models”, European Journal of Operational Research, 154:2, 345-362.
  • BARROS, C. P., ve Dieke, P. U., (2007), “Performance Evaluation of Italian Airports: A Data Envelopment Analysis”, Journal of Air Transport Management, 13:4, 184-191.
  • CHANG, Y. H., Shao, P. C., ve Chen, H. J., (2015), “Performance Evaluation of Airport Safety Management Systems in Taiwan”, Safety Science, 75, 72-86.
  • CHARNES A., Cooper W.W., Rhodes E. (1978), “Measuring The Efficiency of Decision Making Units”, European Journal of Operational Research, 2:6, 429–444.
  • CHARNES A., Cooper W.W., Lewin A.Y., Seiford L. M. (1993) Data Envelopment Analysis, Theory, Methodology and Applications, Kluwer Academic Publishers, Boston/Dordrecht/London.
  • CHATTERJEE, P. ve Chakraborty, S., (2012), “Materials Selection Using COPRAS and COPRAS-G Methods”, International Journal of Materials and Structural Integrity, 6, S.2-4.
  • CHEN, T., Jın, Y., Qiu, X. ve Chen, X., (2014), “A Hybrid Fuzzy Evaluation Method For Safety Assessment of Food-Waste Feed Based On Entropy And The Analytic Hierarchy Process Methods”, Expert Systems with Applications, An International Journal, Science Direct, 41:16, 7328-7337.
  • COELLRI T., Rao D.S.P., O’Donnell C.J., Battese,G.E. (2005) An Introduction to Efficiency and Productivity Analysis, Second Edition, Springer Science Business Media Inc., New York.
  • DİNÇ, M., Haynes K. E. (1999) “Sources of Regional Inefficiency: An Integrated Shift-Share, Data Envelopment Analysis and Input- Output Approach”, The Analysis of Regional Science, 33:4, 469-489.
  • ERMETITA., Wardoyo, R., Hartati, S. ve Harjoko, A., (2012), “ELECTRE- Entropy Method in Group Decision Support System Model To Gene Mutation Detection”, International Journal of Advanced Research in Artificial Intelligence, Indonesia, 1:1, 58-63.
  • ERSÖZ, F., ve Kabak, M., (2010), “Savunma Sanayi Uygulamalarında Çok Kriterli Karar Verme Yöntemlerinin Literatür Araştırması”, Kara Harp Okulu, Savunma Bilimleri Enstitüsü, Savunma Bilimleri Dergisi, Ankara, 9:1, 97-125.
  • European Aviation Environmental Report (2016), https://ec.europa.eu/ transport/sites/transport/files/european- aviation-environmental-report-2016- 72dpi.pdf, 15.07.2017)
  • GOMES, L.F.A.M., Mattos Fernandes, J.E., Mello, J.C.C.B.S., (2014), “A Fuzzy Stochastic Approach to The Multicriteria Selection of An Aircraft for Regional Chartering”, Journal of Advanced Transportation, 48:3, 223- 237.
  • GÖKDALAY, M. H. ve Evren, G., (2009), “Havaalanlarının Performans Analizinde Bulanık Çok Ölçütlü Karar Verme Yaklaşımı”, İstanbul Teknik Üniversitesi Dergisi, İstanbul, 8:6, 157-168.
  • JANIC, M., (2015), “A Multi-Criteria Evaluation of Solutions and Alternatives For Matching Capacity to Demand In An Airport System: The Case of London”, Transportation Planning and Technology, 38:7, 709- 737.
  • KADZINSKI, M., Labijak, A., Napieraj, M., (2017), “Integrated Framework for Robustness Analysis Using Ratio-Based Efficiency Model With Application to Evaluation of Polish Airports”, Omega, 67, 1-18.
  • KARAATLI, M., Ömürbek, N., Budak, İ. ve Dağ, O., (2015), “Çok Kriterli Karar Verme Yöntemleri İle Yaşanabilir İllerin Sıralanması”, Selçuk Üniversitesi, Sosyal Bilimler Enstitüsü Dergisi, 33, 215-228.
  • KARAMI, A, Johansson, R., (2014), “Utilization Of Multi Attribute Decision Making Techniques To Integrate Automatic And Manual Ranking Of Options”, Journal of Informatıon Science And Engineering, 30, 519-534.
  • KAKLAUSKAS, A., Zavadskas, E. K., Raslanas, S., Ginevicius, R., Komka, A. ve Malinauskas, P., (2006), “Selection of Low-e Windows In Retrofit of Public Buildings By Applying Multiple Criteria Method COPRAS: A Lithuanian Case”, Energy and Buildings, Lithuania, 38:5, 454-462.
  • KAKLAUSKAS, A., Zavadskas, E. K. ve Trinkunas, V., (2007), “A Multiple Criteria Decision Support On-Line System For Construction”, Engineering Applications Of Artificial Intelligence, 20, 163-175.
  • KUO, M. S., ve Liang, G. S., (2011), “Combining VIKOR with GRA Techniques to Evaluate Service Quality of Airports Under Fuzzy Environment”, Expert Systems With Applications, 38:3, 1304-1312.
  • LEE, W. ve Lin, Y., (2011), “Evaluating and Ranking Energy Performance of Office Buildings Using Grey Relational Analysis”, Science Direct, 36:5, 2551-2556.
  • LIMA, M. G. ve Belderrain, M. C. N., (2016), “Structuring Multicriteria Model for Airports Selection for Cargo Airlines Exclusively”, Ingeniare. Revista Chilena de Ingenieria, 24:3, 465-479.
  • LIN, J. L. ve Lin, C. L., (2002), “The Use Ofthe Orthogonal Array With Grey Relational Analysis To Optimize The Electrical Discharge Machining Process With Multiple Performance Characteristics”, International Journal Of Machine Tool And Manufacturing, 42:2, 237-244.
  • LU, H. S., Chang, C. K., Hwang, N. C. ve Chung, C. T., (2009), “Grey Relational Analysis Coupled with Principal Component Analysis For Optimization Design of The Cutting Parameters In High-Speed End Milling”, Journal of Materials Processing Technology, 209:8, 3808- 3817.
  • MARTÍN, J. C., ve Román, C., (2006), “A Benchmarking Analysis of Spanish Commercial Airports. A Comparison Between SMOP and DEA Ranking Methods”, Networks and Spatial Economics, 6:2, 111-134.
  • NORESE, M.F. ve Carbone, V., (2014), “An Application of ELECTRE Tri to Support Innovation”, Journal of Multi-Criteria Decision Analysis, 21:1-2, 77-93.
  • ORUÇ, K.O., (2008), Veri Zarflama Analizi ile Bulanık Ortamda Etkinlik Ölçümleri ve Üniversitelerde Bir Uygulama, Yayınlanmamış Doktora Tezi, Süleyman Demirel Üniversitesi, Sosyal Bilimler Enstitüsü, Isparta.
  • ÖMÜRBEK, N., Demirgubuz Öksüz, M., Tunca, M. Z., (2013), “Hizmet Sektöründe performans Ölçümünde Veri Zarflama Analizinin Kullanımı: Havalimanları Üzerine Bir Uygulama”, Süleyman Demiral Üniversitesi Vizyoner Dergisi, 4:9, 21-43.
  • PALANIKUMAR, K., Karunamoorthy, L. ve Karthikeyan, R., (2006), “Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool”, Materials and Manufacturing Processes, 21:8, 846–852.
  • ROCHA, P.M., Barros, A.P., Silva, G.B. ve Costa, H.G., (2016), “Analysis of The Operational Performance of Brazilian Airport Terminals: A Multicriteria Approach with De Borda- AHP Integraation”, Journal of Air Transport Management, 51, 19-26.
  • SARSIN Kaya, D., (2016), Havayolu Yolcu Taşımacılığı Sektörü, Türkiye İş Bankası Yayınları.
  • SOFYALIOĞLU, Ç., (2011), “Süreç Hata Modu Etki Analizini Gri Değerlendirme Modeli”, Ege Üniversitesi, Ekonomi, İşletme, Uluslararası İlişkiler ve Siyaset Bilimi Dergisi, Ege Akademik Bakış, 11:1, 155-164.
  • ŞİŞMAN, B. ve Eleren, A., (2013),” En Uygun Otomobilin Gri İlişkisel Analiz ve ELECTRE Yöntemleri ile Seçimi”, Süleyman Demirel Üniversitesi, İ.İ.B.F. Dergisi, 18:3, 411-429.
  • TARNG, T. S., Juang, S. C. ve Chang C. H., (2002), “The Use of Grey Based Taguchi Methods To Determine Submerged Arc Welding Process Parameters In Hardfacing”, Journal of Materials Processing Technology, 128, 1-6.
  • ÖZDAĞOĞLU, A., (2013), “Çok Ölçütlü Karar Verme Modellerinde Normalizasyon Tekniklerinin Sonuçlara Etkisi: COPRAS Örneği”, Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 8:2, 229-252.
  • ÜLKÜ, T., (2015), “A Comparative Efficiency Analysis of Spanish and Turkish Airports”, Journal of Air Transport Management, 46, 56-68.
  • WU, Z., Sun, J., Liang, L. ve Zha, Y., (2011), "Determination Of Weights For Ultimate Cross Efficiency Using Shannon Entropy", Expert Systems With Applications, 38, 5162-5165.
  • YUN Y.B., Nakayama H., Tanino T. (2004) “A Generalized Model For Data Envelopment Analysis”, European Journal of Operational Research, 157:1, 87-105.
  • ZAVADSKAS, E. K., Kaklauskas, A., Turskıs, Z. ve Tamosaitiene, J., (2008), “Contractor Selectıon Multı- Attrıbute Model Applynıg COPRAS Method with Grey Interval Numbers”, 20th EURO Mini Conference, ‘Continuous Optimization and Knowledge-Based Technologies’, Neringa, Lithuania, 241-247.
  • ZHAI, L., Khoo, L. ve Zhong, Z., (2009), “Design Concept Evaluation In Product Development Using Rough Sets and Grey Relation Analysis”, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 7072-7079.
  • ZHANG, H., Gu, C., Gu, L. ve Zhang, Y. (2011), "The Evaluation Of Tourism Destination Competitiveness By TOPSIS & Information Entropy E A Case In The Yangtze River Delta Of China", Tourism Management, 32, 443-451.
  • ZHOU, H., You, J. ve Lıu, H., (2016), “Failure Mode and Effect Analysis Using MULTIMOORA Method with Continuous Weighted Entropy Under Interval-Valued Intuitionistic Fuzzy Environment”, Springer, Berlin, s.1- 13.
  • Zolfani, S. H. ve Bahrami, M., (2014), “Investment Prioritizing In High Tech Industries Based On SWARA- COPRAS Approach”, Technological and Economic Development of Economy, Iran, 20:3, 534-553.
  • ZHU J. (2015) Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets, Third Edition, Springer Science Business Media Inc., New York/Dordrecht/London.
  • (http://airportdatabase.net/all- airports.html, 14.05.2017).
  • (https://www.aci- europe.org/policy/position- papers.html?view=group&group=1&id=11, 15.07.2017).
  • (http://www.iata.org/pressroom/pr/Pag es/2016-12-08-01.aspx, 15.07.2017).
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Fatma Gul Altin 0000-0001-9236-0502

Meltem Karaatlı

İbrahim Budak 0000-0001-7762-6114

Yayımlanma Tarihi 30 Ekim 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 22 Sayı: 4

Kaynak Göster

APA Altin, F. G., Karaatlı, M., & Budak, İ. (2017). AVRUPA’NIN EN BÜYÜK 20 HAVALİMANININ ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİ VE VERİ ZARFLAMA ANALİZİ İLE DEĞERLENDİRİLMESİ. Süleyman Demirel Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 22(4), 1049-1064.
 Kapak Resmi İndir