HAVA KARGO TAŞIYICILARININ KARGO UÇAĞI TİPİ SEÇİMİNDE STRATEJIK KARAR VERME

Yıl 2022, Cilt: 18 Sayı: 4, 1329 - 1354, 28.12.2022

Gökhan Tanrıverdi , Şenay Lezki , Ümit Doğan

https://doi.org/10.17130/ijmeb.1122066

Öz

Kargo uçağı tipi seçimi, özellikle bir kargo uçağının satın alınması halinde ciddi bir mali yük oluşturduğundan hava kargo taşıyıcılarının ekonomik sürdürülebilirliğini etkileyen stratejik kararlardan biridir. Bu bağlamda çalışmanın amacı, hava kargo taşıyıcılarının iş modellerine göre en iyi kargo uçağı tipini belirlemelerine yardımcı olacak bir metodoloji ortaya koymaktır. Çalışmada, literatürden ve uzmanlardan toplanan nitel ve nicel kriterler kullanılmaktadır. Kriter ağırlıklarını belirlemek için AHP tekniği kullanılmıştır. En iyi alternatif kargo uçağı tipini seçmek için ise TOPSIS ve VIKOR tekniklerinden faydalanılmıştır. Bulgular, sektör geneli için A330-200F ve B777F kargo uçağı tiplerinin en iyi iki kargo uçağı tipi olduğunu göstermektedir.

Anahtar Kelimeler

Kargo Uçağı Tipi Seçimi, Hava Kargo, Çok Kriterli Yaklaşım, AHP Tabanlı TOPSIS-VIKOR, Borda Sayım Yöntemi

STRATEGIC DECISION MAKING FOR AIR CARGO CARRIERS ON FREIGHTER TYPE SELECTION

Öz

The selection of freighter type is one of the strategic decisions that influence the economic sustainability of air cargo carriers, as it creates a serious financial burden, especially in case of purchasing a freighter. In this context, the aim of this study is to provide a methodology for air cargo carriers to help them determine the best freighter type in terms of their business models. The study is applied criteria including qualitative and quantitative drawn from the related literature and experts. AHP technique is used to determine criterion weights. TOPSIS and VIKOR techniques are utilized to select the best alternative freighter type. Findings show that A330-200F and B777F freighter types as the top two freighters for sector-wide results.

Anahtar Kelimeler

Freighter Type Selection, Air Cargo, Multi-Criteria Approach, AHP-Based TOPSIS-VIKOR, Borda Count Method

Kaynakça

• Airbus (2015). Global market forecast: Flying on demand 2014-2033 [WWW Document]. URL http://i2.cdn.turner.com/cnn/2014/images/10/30/airbus_gmf_book_2014-2033.pdf (accessed 07.25.2019)
• Azar, A., Olfat, L., Khosravani, F., & Jalali, R. (2011). A BSC method for supplier selection strategy using TOPSIS and VIKOR: A case study of part maker industry. Management Science Letters, 1, 559–568.
• Azimifard, A., Moosavirad, S. H., & Ariafar, S. (2018). Selecting sustainable supplier countries for Iran's steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30-44.
• Bai, C., & Sarkis, J. (2018). Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection. Computers and Operations Research, 1-20.
• Berrittella, M., Franca, L., & Zito, P. (2009). An Analytic Hierarchy Process for ranking operating costs of low cost and full service airlines. Journal of Air Transport Management, 15(5), 249-255.
• Bhadra, D. (2003). Choice of aircraft fleets in the US NAS: Findings from a multinomial logit analysis. Center for Advanced System Development (CAASD): The MITRE Corporation.
• Brunelli, M. (2014). Introduction to the Analytic Hierarchy Process. SpringerBriefs.
• Bruno, G., Esposito, E., & Genovese, A. (2015). A model for aircraft evaluation to support strategic decisions. Expert Systems with Applications, 42(13), 5580-5590.
• Chao, C.-C., & Kao, K.-T. (2015). Selection of strategic cargo alliance by airlines. Journal of Air Transport Management, 43, 29-36.
• Chao, C.-C., & Li, R.-G. (2017). Effects of cargo types and load efficiency on airline cargo revenues. Journal of Air Transport Management, 61, 26-33.
• DHMİ. Statistics. [WWW Document]. URL https://www.dhmi.gov.tr/sayfalar/istatistik.aspx (accessed 25.07.2019)
• Dožić , S., Lutovac , T., & Kalić, M. (2018). Fuzzy AHP approach to passenger aircraft type selection. Journal of Air Transport Management, 68, 165-175.
• Dožić, S. Z., & Kalić, M. Đ. (2013). Two-stage airlıne fleet planning model. 1st Logistics International Conference (s. 60-65). Belgrade: Logic.
• Dožić, S., & Kalić, M. (2014). An AHP approach to aircraft selection process. Transportation Research Procedia, 165-174.
• Dozic, S., & Kalic, M. (2015). Three-stage airline fleet planning model. Journal of Air Transport Management, 46, 30-39.
• Fancello, G., Carta, M., & Fadda, P. (2019). Road intersections ranking for road safety improvement: Comparative analysis of multi-criteria decision making methods. Transport Policy, 80 (2019), 188-196.
• Gardziejczyk, W., & Zabicki, P. (2014). The influence of the scenario and assessment method on the choiceof road alignment variants. Transport Policy, 36 (2014), 294-305.
• Givoni, M., & Rietveld, P. (2009). Airline’s choice of aircraft size – Explanations and implications. Transportation Research Part A, 43, 500-510.
• Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J. (2018). A new hybrid Fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering, 18(1), 32-49.
• Gomes, L. A., Fernandes, J., & Mello, J. (2012). A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. Journal of Advanced Transportation, 48, 223–237.
• Harasani, W. I. (2006). Evaluation and selection of a fleet of aircraft for a local airline. JKAU: Eng. Sci., 17(2), 3-16.
• Hwang, C., & Yoon, K. (1981). Multiple attributes decision making methods and applications. Berlin Heidelberg: Springer.
• Khoo, H. L., & Teoh, L. E. (2014). An optimal aircraft fleet management decision model under uncertainty. Journal of Advanced Transportation, 48, 798-820.
• Kiracı, K., & Akan, E. (2020). Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89 (101924)
• Kiracı, K., & Bakır, M. (2018). Application of commercial aircraft selection in aviation industry through multi-crıteria decision making methods. Manisa Celal Bayar University Social Studies Journal, 16(4), 307-332.
• Kiracı, K., & Bakır, M. (2018). Using the Multi criteria decision making methods in aircraft selection problems and an application. Journal of Transportation and Logistics, 3(1), 13 - 24.
• Kumar, R., Padhi, S. S., & Sarkar, A. (2018). Supplier selection of an Indian heavy locomotive manufacturer: An integrated approach using taguchi loss function, TOPSIS, and AHP. IIMB Management Review.
• Ma, Q., Song, H., & Zhu, W. (2018). Low-carbon airline fleet assignment: A compromise approach. Journal of Air Transport Management, 68, 86-102.
• Mardani, A., Zavadskas, E. K., Khalifah, Z., & Jusoh, A. (2016). Multiple criteria decision-making techniques in transportation systems: A systematic review of the state of the art literature. Transport, 31(3), 359-385.
• Merkert, R., & Hensher, D. A. (2011). The impact of strategic management and fleet planning on airline efficiency – A random effects tobit model based on DEA efficiency scores. Transportation Research Part A, 45, 686–695.
• Mukanbay, R. G., Öztürk, E., Küçük, Ö., & Erol, S. (2016). Aircraft selection model for an air cargo company for transportation of hazardous materials. International Journal of Economics and Administrative Sciences, 37-51.
• Opricovic, S., 1998. Multicriteria optimization of civil engineering systems, Faculty of Civil Engineering, Belgrade
• Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
• Ozdemir, Y., Basligil, H., & Karaca , M. (2011). Aircraft selection using analytic network process: A case for Turkish Airlines. Proceedings of the World Congress on Engineering 2011 (WCE 2011) (p. 1-5). London: World Congress on Engineering.
• Ozdemir, Y., & Basligil, H. (2016). Aircraft selection using fuzzy ANP and the Generalized Choquet Integral Method: The Turkish Airlines Case. Journal of Intelligent & Fuzzy Systems, 31(1), 589-600.
• Qiu, Z., Dosskey, M. G., & Kang, Y. (2016). Choosing between alternative placement strategies for conservation buffers using Borda Count. Landscape and Urban Planning, 153, 66-73.
• Rosskopf, M., Lehner, S., & Gollnick, V. (2014). Economic-environmental trade-offs in long-term airline fleet planning. Journal of Air Transport Management, 34, 109-115.
• Saaty, T. L. (1986). Axiomatic foundation of the Analytic Hierarchy Process. Management Science, 32(7), 841-855.
• Sennaroglu, B., & Varlik Celebi, G. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D, 59, 160–173.
• Sherali, H. D., Bish, E. K., & Zhu, X. (2006). Airline fleet assignment concepts, models, and algorithms. European Journal of Operational Research, 172, 1-30.
• Soner, O., Celik, E., & Akyuz, E. (2017). Application of AHP and VIKOR methods under interval type 2 fuzzy environment in maritime transportation. Ocean Engineering, 129, 107–116.
• Sun, X., Gollnick, V., & Stumpf, E. (2011). Robustness consideration in multi-criteria decision making to an aircraft selection problem. Journal of Multi-Criteria Decision Analysis, 18, 55-64.
• Tzeng, G.-H., & Huang, J.-J. (2011). Multiple attribute decision making: methods and applications. New York: Chapman and Hall/CRC
• UTIKAD. İstanbul Yeni Havalimanı Hava Kargoda Çarpan Etkisi Yaratacak (Istanbul New Airport Will Create a Multiplier Effect in Air Cargo) [WWW Document]. URL https://www.utikad.org.tr/Detay/Sektor-Haberleri/21240/istanbul-yeni-havalimani-hava-kargoda-carpan-etkisi-yaratacak (accessed 25.07.2019)
• Yeh, C.-H., & Chang, Y.-H. (2009). Modeling subjective evaluation for fuzzy group multicriteria decision making. European Journal of Operational Research, 194(2), 464-473.
• Zhu, G.-N., Hu, J., Qi, J., Gu, C.-C., & Peng, Y.-H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29, 408–418.