The Effect of Location Selection on Operational Costs and Fleet Management in the Airline Industry

Year 2022, , 110 - 117, 24.07.2022

Serhan Zeybel

https://doi.org/10.30518/jav.933948

Cited By: 1

Abstract

The aim of this study is to reveal the effect of location selection in the airline industry on airline operational costs and fleet management. The effect of location selection on airline operational costs and fleet management in the airline industry is seen as a multi-criteria decision-making problem. For this purpose, the TOPSIS model, a multi-criteria decision-making method, was used. The data used in the research are handled in two stages as alternatives and criteria. The alternatives of the research are 5 different types of aircraft, 8 different locations and 10 different hubs. The alternatives to the multi-criteria decision-making process are operational costs. The main starting point of the study is where the airline's location should be and which aircraft should be used in order to reach 10 different main transfer centers with the lowest operational cost. The weighting has been made according to the average costs in the industry. In addition, in order to fully measure the effect of the location on operational costs, an index was developed with the average of the GDP, HDI and SDI values of the countries where the transfer centers are located, and it is ensured that it affects the decision-making process as 30%. According to the results of the research, it has been seen that the operational costs of the airlines to be established in locations such as Istanbul, London and Delhi are lower and the fleet management is more optimal. This study is important in terms of helping airline companies in the selection process of their establishment location. In addition, unlike the studies in the literature, three different indices such as GDP, HDI and SDI were included in the study, resulting in more realistic results.

Keywords

Location Selection, Operational Costs, Fleet Management, Multi-Criteria Decision Making, Airline Industry

References

• Anaz, N. and Akman, E. (2017). Turkey's Soft Power Capacity: Geopolitics of Aviation and the Turkish Airlines, The Arab World Geographer, 20 (4), 303-316.
• Butler, R. V., & Huston, J. H. (1989). Merger mania and airline fares, Eastern economic journal, 15(1), 7-16.
• Çakmak, A. U. (2016). Havacılık Jeopolitiği, Potansiyel Bölgenin Tespiti ve Tespit Edilen Bölgedeki Bir Uçak Bakım Merkezinin Ekonomik Modellemesinin Yapılması, İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü.
• Debbage, K. G. (2016). The geopolitics of air transport, The geographies of air transport, 41-5.
• Doganis, R. (2006). The airline business. Psychology Press.
• Gelareh, S., & Pisinger, D. (2011). Fleet deployment, network design and hub location of liner shipping companies, Transportation Research Part E: Logistics and Transportation Review, 47 (6), 947-964.
• Givoni, M. and Rietveld, P. (2009). Airline’s choice of aircraft size–Explanations and implications, Transportation Research Part A: Policy and Practice, 43(5), 500-510.
• Huston, J. H. and Butler, R. V. (1991). The location of airline hubs,” Southern Economic Journal, 975-981.
• Ilgın, M. A. (2019). Aircraft selection using linear physical programming,” Journal of Aeronautics and Space Technologies, 12(2), 121-128.
• Kiraci K. and Bakir, 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.
• Lacoste, Y. (2004). Aviation and Geopolitics: Projections of Military Power,” Hérodote, 3, 5-16.
• O’Kelly, M. E., & Bryan, D. L. (1998). Hub location with flow economies of scale,” Transportation Research Part B: Methodological, 32 (8), 605-616.
• Oum, T. H. a C. Yu, T. H. (2012). Winning airlines: Productivity and cost competitiveness of the world’s major airlines. Springer Science & Business Media.
• Polmar, N. (2006). Aircraft Carriers: A History of Carrier Aviation and Its Influence on World Events. Potomac Books.
• Şengür, Y. (2004). Havayolu Taşımacılığında Düşük Maliyetli Taşıyıcılar ve Türkiye'deki Uygulamalarının Araştırılması, Anadolu Üniversitesi, Sosyal Bilimler Enstitüsü.
• Uludağ, A. S., & Deveci, M. (2013). Kuruluş Yeri Seçim Problemlerinde Çok Kriterli Karar Verme Yöntemlerinin Kullanılması ve Bir Uygulama, Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 13(1), 257-287.
• Uslu, S. and Cavcar, A. (2003). Havayolu İşletmelerinde Bir Maliyet Unsuru: Avrupa Hava Sahası’nda Hava Trafik Yol Ücretleri, Sosyal Bilimler Dergisi, 81- 94.
• Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods, International journal of operations research, 10(2), 56-66.
• Wang, T. C. and Chang, T. H. (2007). Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications, 33(4), 870-880.
• Wei, W. (2006). Impact of landing fees on airlines’ choice of aircraft size and service frequency in duopoly markets, Journal of Air Transport Management, 12(6), 288-292.
• Yükçü, S. and Fidancı, N. (2018). Havayolu İşletmeciliğinde Maliyet ve Fiyatlandırma Önerileri, Muhasebe ve Vergi Uygulamaları Dergisi, 394-407.
• Żak, J., Redmer, A., & Sawicki, P. (2011). Multiple objective optimization of the fleet sizing problem for road freight transportation, Journal of advanced transportation, 45 (4), 321-347.
• Zuidberg, J. (2014). Identifying airline cost economies: An econometric analysis of the factors affecting aircraft operating costs, Journal of Air Transport Management, 40, 86-95.