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INVESTIGATION OF AIRLINES' MARKETING AND FINANCIAL EFFICIENCY BY USING STOCHASTIC FRONTIER ANALYSIS

Year 2021, Issue: 42, 304 - 315, 08.01.2021
https://doi.org/10.30794/pausbed.689916

Abstract

In this study, it is aimed to use the financial and marketing indicators of 42 airline companies for the year 2016 by using stochastic frontier analysis (SSA) method. Multiple regression analysis on revenue per kilometer showed that the liquidity component, which is one of the financial indicators of the airlines, the Skytrax rankings from the marketing indicators and fleet numbers have significant impacts on it. According to the analysis, as the liquidity of the companies increase, the revenue per kilometer decreases. As the number of Skytrax ranking increases, revenue per kilometer decreases. Lastly, as the number of fleet of companies increases, the revenue per kilometer, which is an indicator of seats sold by airlines, increased. According to the results of the stochastic frontier analysis (SSA), using the marketing and financial variables in the revenue per kilometer, the companies of Hawaiian Airlines, Korean Air, Singapore Airlines and United Airlines are found relative efficient.

References

  • Afriat, S. (1972). “Efficiency Estimation of Production Functions”, International Economic Review: 568-598.
  • Aigner, D. J. ve CHU, S.F. (1968). “On Estimating The İndustry Production Function”, The American Economic Review, 1968, 58.4: 826-839.
  • Aigner, D.; Lovell, Ca K. ve Schmidt, P. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6.1: 21-37.
  • Atılgan, E. (2012). Hastane Etkinliğinin Stokastik Sınır Analizi Yöntemiyle Değerlendirilmesi: Sağlık Bakanlığı Hastaneleri İçin Bir Uygulama. Sosyal Bilimler Enstitüsü.
  • Baltagi, B. H., Griffin, J. M. ve Rich, D. P. (1995). “Airline Deregulation: The Cost Pieces of the Puzzle”, International Economic Review, 245-258.
  • Capobianco, H. M. P. ve Fernandes, E. (2004). “Capital Structure in The World Airline İndustry”, Transportation Research Part A: Policy and Practice, 38.6: 421-434.
  • Chen, Z., Wanke, P., Antunes J. ve Zhanga Ning. (2017). “Chinese Airline Efficiency Under CO2 Emissions and Flight Delays: A Stochastic Network DEA Model”, Energy Economics, 68: 89-108.
  • 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.
  • Cui, Q. ve Li, Y. (2015). “The Change Trend and İnfluencing Factors of Civil Aviation Safety Efficiency: The Case of Chinese Airline Companies”, Safety Science, 75: 56-63.
  • Cui, Q., Li, Y., Yu, C.L. ve Wei, Y.M. (2016) “Evaluating Energy Efficiency for Airlines: An Application of Virtual Frontier Dynamic Slacks Based Measure”, Energy, 113: 1231-1240.
  • Drucker, P. F.(1995). Management: An Abridged and Revised Version of Management, Butterworth-Heinemann.
  • Evgallıoğlu, A.E. (2017). Türkiye’deki Doğal Gaz Dağıtım Şirketlerinin Stokastik Sınır Analizi Yöntemi ile Etkinlik Analizi. Gazi Üniversitesi Bilişim Enstitüsü, Ankara.
  • Farrell, M.J. (1957). “The Measurement of Productive Efficiency”, Journal of the Royal Statistical Society: Series A (General), 120.3: 253-281.
  • Fethi, M.D., Jackson, P.M. ve WEYMAN-JONES, T.G. (2000). “Measuring The Efficiency of European Airlines: An Application of DEA and Tobit Analysis”, Annual Meeting of the European Public Choice Society, Siena, Italy.
  • Good, D.H., Röller, L.H. ve Sickles, R.C. (1995). “Airline Efficiency Differences Between Europe and The US: İmplications for The Pace of EC İntegration and Domestic Regulation”, European Journal of Operational Research, 80.3: 508-518.
  • Gülcü, A., Çoşkun, A., Yeşilyurt, C., Çoşkun, S. ve Esener, T. (2004). Cumhuriyet Üniversitesi Diş Hekimliği Fakültesi’nin Veri Zarflama Analizi Yöntemiyle Göreceli Etkinlik Analizi; C.Ü. İktisadi ve İdari Bilimler Dergisi, Cilt.5, Sayı. 2.
  • Heshmati, A. ve Kim, J. (2016). “Efficiency and Competitiveness of International Airlines”, Springer.
  • Mahesh, R. ve Prasad, D. (2012). “Post Merger and Acquisition Financial Performance Analysis: A Case Study of Select Indian Airline Companies”, International Journal of Engineering, Management & Sciences, 3.3: 362-369.
  • Meeusen, W. ve Van Den Broeck, J. (1977). “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error”, International Economic Review, 435-444.
  • Pires, H. M. ve Fernandes, E. (2012). “Malmquist Financial Efficiency Analysis for Airlines”, Transportation Research Part E: Logistics and Transportation Review, 48.5: 1049-1055.
  • Prokopenko, J. (2003). Verimlilik Yöntemi, (Çeviri Baykal, O. ve diğerleri). Milli Prodüktivite Merkezi Yayınları, Ankara.
  • Richmond, J. (1974). “Estimating The Efficiency of Production”, International Economic Review, 515-521.
  • Sarafidis, V. (2002). “An Assessment of Comparative Efficiency Measurement Techniques”, Europe Economics, Occasional Paper, 2.
  • Schefczyk, M. (1993). “Operational Performance of Airlines: An Extension of Traditional Measurement Paradigms”, Strategic Management Journal, 14.4: 301-317.
  • Tsionas, M.G., Chen, Z. ve Wanke, P. (2017). “A Structural Vector Autoregressive Model of Technical Efficiency and Delays with an Application to Chinese Airlines”, Transportation Research Part A: Policy and Practice, 101: 1-10.
  • Hotel, S., Columbus, O. ve Winsten, CB. (1957). “Discussion On Mr. Farrells Paper”, Journal of The Royal Statistical.
  • Yaghi H. (2015). Comparing The Performances of Major Airlines Companies by Traditional and Airline-Spesific Ratios and Measure. Sakarya University Institute of Social Sciences, Sakarya.
  • Yu, C. (2016). “Airline Productivity and Efficiency: Concept, Measurement, And Applications”, In: Airline Efficiency. Emerald Group Publishing Limited, 2016. p. 11-53.

HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ

Year 2021, Issue: 42, 304 - 315, 08.01.2021
https://doi.org/10.30794/pausbed.689916

Abstract

Bu çalışmada 2016 yılı için 42 havayolu firmasına ait finansal ve pazarlama göstergeleri kullanılarak havayollarının ücretli yolcu mesafesi üzerinden etkinlikleri stokastik sınır analizi (SSA) yöntemi kullanılarak bulunması amaçlanmıştır. Ücretli yolcu mesafesi üzerinde çoklu regresyon analizi ile havayollarının finansal göstergelerinden olan likidite bileşeninin, pazarlama göstergelerinden olan Skytrax sıralamalarının ve filo sayılarının etkili olduğu görülmüştür. Analiz sonucuna göre şirketlerin likiditeleri arttıkça ücretli yolcu mesafesi azalmaktadır. Skytrax sıralaması arttıkça yani sıralamada şirketlerin memnuniyet/kalite sıralaması düştükçe ücretli yolcu mesafesinin ise azaldığı, son olarak şirketlerin filo sayısı arttıkça şirketlerin sattığı koltukların göstergesi olan ücretli yolcu mesafesi değişkeninin arttığı görülmüştür. Stokastik sınır analizi (SSA) sonuçlarına göre ücretli yolcu mesafesinde pazarlama ve finansal değişkenler kullanılarak Hawaiian Airlines, Korean Air, Singapore Airlines, United Airlines şirketleri diğer 38 şirkete göre göreli olarak etkin bulunmuştur.

References

  • Afriat, S. (1972). “Efficiency Estimation of Production Functions”, International Economic Review: 568-598.
  • Aigner, D. J. ve CHU, S.F. (1968). “On Estimating The İndustry Production Function”, The American Economic Review, 1968, 58.4: 826-839.
  • Aigner, D.; Lovell, Ca K. ve Schmidt, P. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6.1: 21-37.
  • Atılgan, E. (2012). Hastane Etkinliğinin Stokastik Sınır Analizi Yöntemiyle Değerlendirilmesi: Sağlık Bakanlığı Hastaneleri İçin Bir Uygulama. Sosyal Bilimler Enstitüsü.
  • Baltagi, B. H., Griffin, J. M. ve Rich, D. P. (1995). “Airline Deregulation: The Cost Pieces of the Puzzle”, International Economic Review, 245-258.
  • Capobianco, H. M. P. ve Fernandes, E. (2004). “Capital Structure in The World Airline İndustry”, Transportation Research Part A: Policy and Practice, 38.6: 421-434.
  • Chen, Z., Wanke, P., Antunes J. ve Zhanga Ning. (2017). “Chinese Airline Efficiency Under CO2 Emissions and Flight Delays: A Stochastic Network DEA Model”, Energy Economics, 68: 89-108.
  • 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.
  • Cui, Q. ve Li, Y. (2015). “The Change Trend and İnfluencing Factors of Civil Aviation Safety Efficiency: The Case of Chinese Airline Companies”, Safety Science, 75: 56-63.
  • Cui, Q., Li, Y., Yu, C.L. ve Wei, Y.M. (2016) “Evaluating Energy Efficiency for Airlines: An Application of Virtual Frontier Dynamic Slacks Based Measure”, Energy, 113: 1231-1240.
  • Drucker, P. F.(1995). Management: An Abridged and Revised Version of Management, Butterworth-Heinemann.
  • Evgallıoğlu, A.E. (2017). Türkiye’deki Doğal Gaz Dağıtım Şirketlerinin Stokastik Sınır Analizi Yöntemi ile Etkinlik Analizi. Gazi Üniversitesi Bilişim Enstitüsü, Ankara.
  • Farrell, M.J. (1957). “The Measurement of Productive Efficiency”, Journal of the Royal Statistical Society: Series A (General), 120.3: 253-281.
  • Fethi, M.D., Jackson, P.M. ve WEYMAN-JONES, T.G. (2000). “Measuring The Efficiency of European Airlines: An Application of DEA and Tobit Analysis”, Annual Meeting of the European Public Choice Society, Siena, Italy.
  • Good, D.H., Röller, L.H. ve Sickles, R.C. (1995). “Airline Efficiency Differences Between Europe and The US: İmplications for The Pace of EC İntegration and Domestic Regulation”, European Journal of Operational Research, 80.3: 508-518.
  • Gülcü, A., Çoşkun, A., Yeşilyurt, C., Çoşkun, S. ve Esener, T. (2004). Cumhuriyet Üniversitesi Diş Hekimliği Fakültesi’nin Veri Zarflama Analizi Yöntemiyle Göreceli Etkinlik Analizi; C.Ü. İktisadi ve İdari Bilimler Dergisi, Cilt.5, Sayı. 2.
  • Heshmati, A. ve Kim, J. (2016). “Efficiency and Competitiveness of International Airlines”, Springer.
  • Mahesh, R. ve Prasad, D. (2012). “Post Merger and Acquisition Financial Performance Analysis: A Case Study of Select Indian Airline Companies”, International Journal of Engineering, Management & Sciences, 3.3: 362-369.
  • Meeusen, W. ve Van Den Broeck, J. (1977). “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error”, International Economic Review, 435-444.
  • Pires, H. M. ve Fernandes, E. (2012). “Malmquist Financial Efficiency Analysis for Airlines”, Transportation Research Part E: Logistics and Transportation Review, 48.5: 1049-1055.
  • Prokopenko, J. (2003). Verimlilik Yöntemi, (Çeviri Baykal, O. ve diğerleri). Milli Prodüktivite Merkezi Yayınları, Ankara.
  • Richmond, J. (1974). “Estimating The Efficiency of Production”, International Economic Review, 515-521.
  • Sarafidis, V. (2002). “An Assessment of Comparative Efficiency Measurement Techniques”, Europe Economics, Occasional Paper, 2.
  • Schefczyk, M. (1993). “Operational Performance of Airlines: An Extension of Traditional Measurement Paradigms”, Strategic Management Journal, 14.4: 301-317.
  • Tsionas, M.G., Chen, Z. ve Wanke, P. (2017). “A Structural Vector Autoregressive Model of Technical Efficiency and Delays with an Application to Chinese Airlines”, Transportation Research Part A: Policy and Practice, 101: 1-10.
  • Hotel, S., Columbus, O. ve Winsten, CB. (1957). “Discussion On Mr. Farrells Paper”, Journal of The Royal Statistical.
  • Yaghi H. (2015). Comparing The Performances of Major Airlines Companies by Traditional and Airline-Spesific Ratios and Measure. Sakarya University Institute of Social Sciences, Sakarya.
  • Yu, C. (2016). “Airline Productivity and Efficiency: Concept, Measurement, And Applications”, In: Airline Efficiency. Emerald Group Publishing Limited, 2016. p. 11-53.
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Finance
Journal Section Articles
Authors

Umut Aydın 0000-0003-4802-8793

Gizem Kaya 0000-0002-6870-7219

Publication Date January 8, 2021
Acceptance Date July 1, 2020
Published in Issue Year 2021 Issue: 42

Cite

APA Aydın, U., & Kaya, G. (2021). HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(42), 304-315. https://doi.org/10.30794/pausbed.689916
AMA Aydın U, Kaya G. HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ. PAUSBED. January 2021;(42):304-315. doi:10.30794/pausbed.689916
Chicago Aydın, Umut, and Gizem Kaya. “HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, no. 42 (January 2021): 304-15. https://doi.org/10.30794/pausbed.689916.
EndNote Aydın U, Kaya G (January 1, 2021) HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 42 304–315.
IEEE U. Aydın and G. Kaya, “HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ”, PAUSBED, no. 42, pp. 304–315, January 2021, doi: 10.30794/pausbed.689916.
ISNAD Aydın, Umut - Kaya, Gizem. “HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 42 (January 2021), 304-315. https://doi.org/10.30794/pausbed.689916.
JAMA Aydın U, Kaya G. HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ. PAUSBED. 2021;:304–315.
MLA Aydın, Umut and Gizem Kaya. “HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, no. 42, 2021, pp. 304-15, doi:10.30794/pausbed.689916.
Vancouver Aydın U, Kaya G. HAVAYOLLARININ PAZARLAMA VE FİNANSAL ETKİNLİKLERİNİN STOKASTİK SINIR ANALİZİ YÖNTEMİ İLE İNCELENMESİ. PAUSBED. 2021(42):304-15.