NEGATIVE VALUES IN DEA: EXAMINATION OF THE RELATIONSHIP BETWEEN ECONOMIC GROWTH RATES AND AIRLINE PERFORMANCES

Yıl 2018, , 399 - 412, 01.03.2018

Burak Keskin Efehan Ulaş Günal Bilek

https://doi.org/10.17130/ijmeb.2018239939

Cited By: 1

Öz

The main goal of this study is to determine whether there is a relationship between the economic growth rates and the performances of airline companies. From this point of view, Data Envelopment Analysis DEA is applied to star alliance member airlines for a period of 2012-2014. Firstly, the technical, pure technical and scale efficiency scores were calculated. Then, airlines are divided into four regional groups as America, Europe, Asia and Africa in order to determine the most efficient region. Further, countries economic growth rates which the airline is located are analyzed to support DEA results. Finally, Asia group is found as the most efficient airline group

Anahtar Kelimeler

Technical Efficiency, Data Envelopment Analysis, Airline Industry

DEA’DA NEGATİF DEĞERLER: HAVAYOLU PERFORMANSLARI VE EKONOMİK BÜYÜME ORANLARI ARASINDAKİ İLİŞKİNİN İNCELENMESİ

Öz

Bu çalışmanın genel amacı, ülkelerin ekonomik büyüme oranları ile o ülkede yer alan havayolu şirketlerinin performansları arasında bir ilişki olup olmadığını belirlemektir. Buradan hareketle, Star Alliance üyesi havayolu şirketlerinin 2012-2014 yılları arasındaki verileri üzerinde bir Veri Zarflama Analizi gerçekleştirilmiştir. Öncelikle, her bir havayolu şirketinin teknik ve ölçek etkinlikleri hesaplanmıştır. Daha sonra, havayolu şirketlerinin yer aldığı ülkeler, en verimli bölgeyi belirlemek amacıyla Amerika, Avrupa, Asya ve Afrika olmak üzere dört grup altında toplanmıştır. Veri Zarflama Analizi sonuçlarını destekleyebilmek ve verimlilik ile büyüme oranları arasında bir ilişki bulabilmek adına her bir ülkenin ekonomik büyüme oranları hesaplanmış ve sonuç olarak en verimli ve en yüksek büyüme oranına sahip bölge Asya bölgesi olmuştur.

Anahtar Kelimeler

Teknik Etkinlik, Veri Zarflama Analizi, Havayolu Endüstrisi

Kaynakça

• Avkiran, N. K. (2001). Investigating technical and scale efficiencies of Australian universities through data envelopment analysis. Socio-Economic Planning Sciences, 35, 57- 80.
• Barros, C., & Dieke, B. (2007). Performance evaluation of Italian airports: A data envelopment analysis. Journal of Air Transport Management, 13,184-191.
• Bowlin, W. F. (1998). Measuring performance: An introduction to data envelopment analysis (DEA). The Journal of Cost Analysis, 15(2), 3-27.
• Brueckner, J. K. (2003). Airline traffic and urban economic development. Urban Studies, 40 (8), 1455-1469.
• Button, K., & Taylor, S. (2000). International air transportation and economic development. Journal of Air Transport Management, 6 (4), 209-222.
• Charnes, A. et al. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 429-444.
• Feng, C. M., & Wang, R. T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6 (3), 133-142.
• Fleming, K., & Ghobrial, A. (1994). An analysis of the determinants of regional air travel demand. Transportation Planning and Technology, 18 (1), 37-44.
• Gladovic, P. et al. (2012). Quantification of Airlines Business Efficiency Using DEA, African Journal of Business Management, 6 (25), 7423-7430.
• IATA (2015). The international air transport association 2015 mid-year report.
• Lai, P. (2013). A study on the relationship between airport privatization and airport efficiency. Cardiff: Cardiff University.
• Lin, L. C., & Hong, C. H. (2006). Operational performance evaluation of international major airports: An application of data envelopment analysis. Journal of Air Transport Management, 12, 342-351.
• OECD, Retrieved December 31, 2015 from www.oecd.org
• Rai, A. (2013). Measurement of efficiency in the airline industry using DEA, Investment Management and Financial Innovation, 10 (1), 38-45.
• Scheraga, C. (2004). Operational efficiency versus financial mobility in the global airline industry: A data envelopment and TOBIT analysis. Transportation Research Part A, 38, 383-404.
• Ulas, E., & Keskin, B. (2017). Is there a relation between HDI and economic performances?. In New trends in finance and accounting (pp. 61-70). Springer, Cham.
• Keskin, B., & Ulas, E. (2017). Does privatization affect airports performance? A comparative analysis with AHP-TOPSIS and DEA. In New trends in finance and accounting (pp. 335-345). Springer, Cham.
• Kopsch, F. (2012). A demand model for domestic air travel in Sweden. Journal of Air Transport Management, 20, 46-48.
• Mukkala, K., & Tervo, H. (2013). Air transportation and regional growth: Which way does the causality run?. Environment and Planning A, 45 (6), 1508-1520.
• UsaToday, Retrieved January 21, 2015 from http://www.usatoday.com/story/ todayinthesky/2014/06/05/global-airline-industry-competition-low-cost-carrier- middle-east/10028127/
• World Bank, Retrieved December 31, 2015 from www.worldbank.org
• Yao, S., & Yang, X. (2012). Air transport and regional economic growth in China. Asia-Pacific Journal of Accounting & Economics, 19 (3), 318-329.