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HAVAYOLU İŞLETMELERİNDE HAT BAZLI OPERASYONEL PERFORMANSIN İŞ MODELİ TEMELİNDE DEĞERLENDİRİLMESİ

Yıl 2023, Cilt: 4 Sayı: 2, 88 - 106, 15.10.2023

Öz

Bu çalışmanın amacı, farklı iş modellerine sahip havayolu işletmelerinin 2014-2018 dönemine ait pazar bazlı performanslarının veri zarflama analizi ile incelenmesi ve farklı iş modeline sahip havayolu işletmelerinin etkinlik değerleri açısından karşılaştırılmasıdır. Bu kapsamda geleneksel havayolu iş modelini temsilen Türk Hava Yolları (THY), düşük maliyetli havayolu iş modelini temsilen Pegasus havayollarının aynı anda faaliyet gösterdiği 34 uluslararası uçuş hattı (şehir çifti pazarları) analiz edilmiştir. Araştırma sonuçları hat bazında yapılan karşılaştırmalarda CCR modeline göre Pegasus havayollarının, BCC modeline göre THY’nin aynı anda uçulan pazarlarda daha iyi performans gösterdiğini ortaya koymaktadır. Araştırma sonucunda elde edilen bulguların, hat bazlı analizlerde havayolu işletmelerinin yöneticilerine yol göstereceği ve etkin olmayan hatların detaylı analizleri ile uçuş hatlarının performanslarını iyileştirme noktasında yardımcı olacağı düşünülmektedir.

Kaynakça

  • Arjomandi, A., & ve Seufert, J. H. (2014). An evaluation of the world’s major airlines’ technical and environmental performance. Economic Modelling, 41, 133–144. https://doi.org/10.1016/J.ECONMOD.2014.05.002
  • Asker, V. (2018). Veri Zarflama Analizi ile Finansal ve Operasyonel Etkinlik Ölçümü: Geleneksel Havayolu İşletmelerinde Bir Uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 1, 153–172.
  • Asker, V. (2021a). Havayolu İşletmelerinde İki Aşamalı Veri Zarflama Analizi ile Etkinlik Ölçümü. MANAS Sosyal Araştırmalar Dergisi, 10(4), 2373–2385.
  • Asker, V. (2021b). Havayolu Stratejik İşbirliklerinde Veri Zarflama Analizi ile Finansal Performansın İncelenmesi. Journal of Aviation. https://doi.org/10.30518/jav.988297
  • Asker, V. (2022). Düşük Maliyetli Havayolu İşletmelerinde Bulanık Veri Zarflama Analizi ile Finansal ve Operasyonel Etkinlik Ölçümü. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 1–25.
  • Atik, M. (2020). Düşük Maliyet Taşımacılık İş Modelini Benimseyen Havayolu Şirketlerinin Yan Gelir Uygulamalarının Finansal Performansları Üzerindeki Etkileri: Türk Sivil Havacılık Sektöründe Bir Uygulama. Journal of Business Research- Turk, 11(4), 2622–2635. https://doi.org/10.20491/isarder.2019.763
  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078–1092. http://www.jstor.org/stable/2631725
  • Barros, C. P., & Couto, E. (2013). Productivity analysis of European airlines, 2000-2011. Journal of Air Transport Management, 31, 11–13. https://doi.org/10.1016/j.jairtraman.2012.10.006
  • Barros, C. P., & Wanke, P. (2015). An analysis of African airlines efficiency with two-stage TOPSIS and neural networks. Journal of Air Transport Management, 44–45, 90–102. https://doi.org/10.1016/j.jairtraman.2015.03.002
  • Başkaya, Z., & Avci Öztürk, B. (2012). Measuring financial efficiency of cement firms listed in Istanbul stock exchance via fuzzy data envelopment analysis. Muhasebe ve Finansman Dergisi, 54, 175–188.
  • Bilotkach, V., & Hüschelrath, K. (2012). Airline alliances and antitrust policy: The role of efficiencies. Journal of Air Transport Management, 21, 76–84. https://doi.org/10.1016/j.jairtraman.2011.12.019
  • Boussofiane, A., Dyson, R. G., & Thanassoulis, E. (1991). Applied data envelopment analysis. European Journal of Operational Research, 52(1), 1–15. https://doi.org/10.1016/0377-2217(91)90331-O
  • Chang, Y. T., Park, H. soo, Jeong, J. beom, & Lee, J. woo. (2014). Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach. Transportation Research Part D: Transport and Environment, 27, 46–50. https://doi.org/10.1016/j.trd.2013.12.013
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Chen, Z., Wanke, P., Antunes, J. J. M., & Zhang, N. (2017). Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model. Energy Economics, 68, 89–108. https://doi.org/10.1016/J.ENECO.2017.09.015
  • 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. https://doi.org/10.1016/j.tre.2005.09.005
  • Chiou, Y. C., Lan, L. W., & Yen, B. T. H. (2012). Route-based data envelopment analysis models. Transportation Research Part E: Logistics and Transportation Review, 48(2), 415–425. https://doi.org/10.1016/j.tre.2011.10.006
  • Coelli, T. (1996). A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program (CEPA Working Paper). http://www.une.edu.au/econometrics/cepa.htm
  • Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Data Envelopment Analysis: History, Models, and Interpretations. In W. W. Cooper, L. M. Seiford, & J. Zhu (Eds.), Handbook on Data Envelopment Analysis (pp. 1–39). Springer US. https://doi.org/10.1007/978-1-4419-6151-8_1
  • Cramer, C., & Thams, A. (2021). Fundamentals of Airline Revenue Management. In C. Cramer & A. Thams (Eds.), Airline Revenue Management: Current Practices and Future Directions (pp. 1–13). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-33721-6_1
  • Cui, Q., & Li, Y. (2017). Airline efficiency measures using a Dynamic Epsilon-Based Measure model. Transportation Research Part A: Policy and Practice, 100, 121–134. https://doi.org/10.1016/J.TRA.2017.04.013
  • Derici, S., & Uygur, K. (2019). Türkiye’de Faaliyet gösteren iki havayolu şirketinin Veri Zarflama Analizi ile etkinlik ölçümü. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1107–1118. https://doi.org/10.16953/deusosbil.489000
  • Eremichev, A., & Aslanov, M. (2019). Turkish Airlines Versus Aeroflot. In International Journal of Economics and Management (Vol. 1, Issue 2). https://ssrn.com/abstract=3390667
  • Foong, J. J., O'Connell, J. F., Warnock-Smith, D., & Efthymiou, M. (2023). A product and organisational architecture analysis of the performance of Southeast Asian airlines. Journal of air transport management, 107, 102358.
  • Ji, Y.-B., & Lee, C. (2010). Data envelopment analysis. In The Stata Journal (Vol. 10, Issue 2).
  • Kiracı, K., & Bakır, M. (2019). CRITIC Temelli EDAS yöntemi ile havayolu işletmelerinde performans ölçümü uygulaması. Pamukkale University Journal of Social Sciences Institute, 35, 157–174. https://doi.org/10.30794/pausbed.421992
  • Kottas, A. T., & Madas, M. A. (2018). Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants. Journal of Air Transport Management, 70, 1–17. https://doi.org/10.1016/j.jairtraman.2018.04.014
  • Lang, P., Yolalan, O. R., & Kettani, O. (1995). Controlled Envelopment by Face Extension in DEA. The Journal of the Operational Research Society, 46(4), 473–491. https://doi.org/10.2307/2584595
  • Ling, Y. H., Kokkiang, T., Gharleghi, B., & Fah, B. C. Y. (2018). Productivity and efficiency modeling amongst ASEAN-5 airline industries. International Journal of Advanced and Applied Sciences, 5(8), 47–57. https://doi.org/10.21833/ijaas.2018.08.007
  • Mahmoudi, R., & Emrouznejad, A. (2023). A multi-period performance analysis of airlines: A game-SBM-NDEA and Malmquist Index approach. Research in Transportation Business & Management, 46, 100801.
  • 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: Policy and Practice, 45(7), 686–695. https://doi.org/10.1016/j.tra.2011.04.015
  • Merkert, R., & Williams, G. (2013). Determinants of European PSO airline efficiency – Evidence from a semi-parametric approach. Journal of Air Transport Management, 29, 11–16. https://doi.org/10.1016/J.JAIRTRAMAN.2012.12.002
  • Mhlanga, O., Steyn, J., & Spencer, J. (2018). The airline industry in South Africa: drivers of operational efficiency and impacts. Tourism Review, 73(3), 389–400. https://doi.org/10.1108/TR-07-2017-0111
  • Min, H., & Joo, S. J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52, 99–110. https://doi.org/10.1016/j.jairtraman.2015.12.003
  • Öncü, M. A., Çömlekçi, İ & Coşkun, E. (2013). Yolcu Taşıma İşletmelerinin Finansal Etkinliklerinin Ölçümüne İlişkin Bir Araştırma. Uluslararası Alanya İşletme Fakültesi Dergisi. 5(2), 77-86.
  • Özdağoğlu, A., Kemal Keleş, M., & Işildak, B. (2020). Isparta Süleyman Demirel Havalimanını kullanan havayolu firmaları Performanslarının BWM, MAIRCA ve MABAC ile Değerlendirilmesi. International Journal of Economic and Administrative Studies, 29, 175–194. https://orcid.org/0000-0001-5299-0622.
  • Rai, A. (2013). Measurement of efficiency in the airline industry using data envelopment analysis. Investment Management and Financial Innovations, 10(1), 38–45. http://orcid.org/0000-0001-7813-6117 Ramanathan, R. (2003). An introduction to data envelopment analysis: a tool for performance measurement. Sage.
  • Saranga, H., & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165–176. https://doi.org/10.1016/J.JAIRTRAMAN.2016.03.001
  • Sümerli Sarıgül, S., Ünlü, M. & Yaşar, E. Financial Performance Analysis of Airlines Operating in Europe: CRITIC Based MAUT and MARCOS Methods. International Journal of Business and Economic Studies, 5(2), 76-97.
  • Scheraga, C. A. (2004). Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis. Transportation Research Part A: Policy and Practice, 38(5), 383-404.
  • Shao, Y., & Sun, C. (2016). Performance evaluation of China’s air routes based on network data envelopment analysis approach. Journal of Air Transport Management, 55, 67–75. https://doi.org/10.1016/j.jairtraman.2016.01.006
  • Singh, A. K. (2011). Performance Evaluation of Indian Airline Industry: An Application of DEA. Asia Pacific Business Review, 7(2), 92–103.
  • Soltanzadeh, E., & Omrani, H. (2018). Dynamic network data envelopment analysis model with fuzzy inputs and outputs: An application for Iranian Airlines. Applied Soft Computing Journal, 63, 268–288. https://doi.org/10.1016/j.asoc.2017.11.031
  • Tavassoli, M., Faramarzi, G. R., & Farzipoor Saen, R. (2014). Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input. Journal of Air Transport Management, 34, 146–153. https://doi.org/10.1016/j.jairtraman.2013.09.001
  • Wang, C.-N., Dang, D.-C., Thanh, N. Van, & Tran, T.-T. (2018). Grey model and DEA to form virtual strategic alliance: The application for ASEAN aviation industry. International Journal of Advanced and Applied Sciences, 5(6), 25–34. https://doi.org/10.21833/ijaas.2018.06.004
  • Wanke, P., & Barros, C. P. (2016). Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression. Journal of Air Transport Management, 54, 93–103. https://doi.org/10.1016/J.JAIRTRAMAN.2016.04.001
  • Wanke, P., Pestana Barros, C., & Chen, Z. (2015). An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models. International Journal of Production Economics, 169, 110–126. https://doi.org/10.1016/J.IJPE.2015.07.028
  • Wing Chow, C. K. (2010). Measuring the productivity changes of Chinese airlines: The impact of the entries of non-state-owned carriers. Journal of Air Transport Management, 16(6), 320–324. https://doi.org/10.1016/J.JAIRTRAMAN.2010.04.001
  • Wu, W.-Y., & Liao, Y.-K. (2014). A balanced scorecard envelopment approach to assess airlines’ performance. Industrial Management & Data Systems, 114(1), 123–143. https://doi.org/10.1108/IMDS-03-2013-0135
  • Xu, Y., Park, Y. S., Park, J. D., & Cho, W. (2021). Evaluating the environmental efficiency of the U.S. airline industry using a directional distance function DEA approach. Journal of Management Analytics, 8(1), 1–18. https://doi.org/10.1080/23270012.2020.1832925
  • Yen, B. T. H., & Li, J. S. (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach. Transportation Research Part E: Logistics and Transportation Review, 162. https://doi.org/10.1016/j.tre.2022.102748

EVALUATION OF ROUTE-BASED OPERATIONAL PERFORMANCE IN AIRLINES ON THE BASIS OF BUSINESS MODEL

Yıl 2023, Cilt: 4 Sayı: 2, 88 - 106, 15.10.2023

Öz

The purpose of this study is to examine the market-based performances of airlines with different business models for the period 2014-2018 using data envelopment analysis and to compare airlines with different business models in terms of efficiency values. In this context, 34 international flight routes (city-pair markets) where Turkish Airlines, representing the traditional airline business model, and Pegasus, representing the low-cost airline business model, operate simultaneously were analyzed. The results of the study reveal that Pegasus airlines perform better according to the CCR model and Turkish Airlines performs better according to the BCC model in the common markets. It is thought that the findings obtained as a result of the research will guide the managers of airline companies in route-based analysis and will help to improve the performance of flight routes with detailed analysis of inefficient routes.

Kaynakça

  • Arjomandi, A., & ve Seufert, J. H. (2014). An evaluation of the world’s major airlines’ technical and environmental performance. Economic Modelling, 41, 133–144. https://doi.org/10.1016/J.ECONMOD.2014.05.002
  • Asker, V. (2018). Veri Zarflama Analizi ile Finansal ve Operasyonel Etkinlik Ölçümü: Geleneksel Havayolu İşletmelerinde Bir Uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 1, 153–172.
  • Asker, V. (2021a). Havayolu İşletmelerinde İki Aşamalı Veri Zarflama Analizi ile Etkinlik Ölçümü. MANAS Sosyal Araştırmalar Dergisi, 10(4), 2373–2385.
  • Asker, V. (2021b). Havayolu Stratejik İşbirliklerinde Veri Zarflama Analizi ile Finansal Performansın İncelenmesi. Journal of Aviation. https://doi.org/10.30518/jav.988297
  • Asker, V. (2022). Düşük Maliyetli Havayolu İşletmelerinde Bulanık Veri Zarflama Analizi ile Finansal ve Operasyonel Etkinlik Ölçümü. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 1–25.
  • Atik, M. (2020). Düşük Maliyet Taşımacılık İş Modelini Benimseyen Havayolu Şirketlerinin Yan Gelir Uygulamalarının Finansal Performansları Üzerindeki Etkileri: Türk Sivil Havacılık Sektöründe Bir Uygulama. Journal of Business Research- Turk, 11(4), 2622–2635. https://doi.org/10.20491/isarder.2019.763
  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078–1092. http://www.jstor.org/stable/2631725
  • Barros, C. P., & Couto, E. (2013). Productivity analysis of European airlines, 2000-2011. Journal of Air Transport Management, 31, 11–13. https://doi.org/10.1016/j.jairtraman.2012.10.006
  • Barros, C. P., & Wanke, P. (2015). An analysis of African airlines efficiency with two-stage TOPSIS and neural networks. Journal of Air Transport Management, 44–45, 90–102. https://doi.org/10.1016/j.jairtraman.2015.03.002
  • Başkaya, Z., & Avci Öztürk, B. (2012). Measuring financial efficiency of cement firms listed in Istanbul stock exchance via fuzzy data envelopment analysis. Muhasebe ve Finansman Dergisi, 54, 175–188.
  • Bilotkach, V., & Hüschelrath, K. (2012). Airline alliances and antitrust policy: The role of efficiencies. Journal of Air Transport Management, 21, 76–84. https://doi.org/10.1016/j.jairtraman.2011.12.019
  • Boussofiane, A., Dyson, R. G., & Thanassoulis, E. (1991). Applied data envelopment analysis. European Journal of Operational Research, 52(1), 1–15. https://doi.org/10.1016/0377-2217(91)90331-O
  • Chang, Y. T., Park, H. soo, Jeong, J. beom, & Lee, J. woo. (2014). Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach. Transportation Research Part D: Transport and Environment, 27, 46–50. https://doi.org/10.1016/j.trd.2013.12.013
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
  • Chen, Z., Wanke, P., Antunes, J. J. M., & Zhang, N. (2017). Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model. Energy Economics, 68, 89–108. https://doi.org/10.1016/J.ENECO.2017.09.015
  • 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. https://doi.org/10.1016/j.tre.2005.09.005
  • Chiou, Y. C., Lan, L. W., & Yen, B. T. H. (2012). Route-based data envelopment analysis models. Transportation Research Part E: Logistics and Transportation Review, 48(2), 415–425. https://doi.org/10.1016/j.tre.2011.10.006
  • Coelli, T. (1996). A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer) Program (CEPA Working Paper). http://www.une.edu.au/econometrics/cepa.htm
  • Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Data Envelopment Analysis: History, Models, and Interpretations. In W. W. Cooper, L. M. Seiford, & J. Zhu (Eds.), Handbook on Data Envelopment Analysis (pp. 1–39). Springer US. https://doi.org/10.1007/978-1-4419-6151-8_1
  • Cramer, C., & Thams, A. (2021). Fundamentals of Airline Revenue Management. In C. Cramer & A. Thams (Eds.), Airline Revenue Management: Current Practices and Future Directions (pp. 1–13). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-33721-6_1
  • Cui, Q., & Li, Y. (2017). Airline efficiency measures using a Dynamic Epsilon-Based Measure model. Transportation Research Part A: Policy and Practice, 100, 121–134. https://doi.org/10.1016/J.TRA.2017.04.013
  • Derici, S., & Uygur, K. (2019). Türkiye’de Faaliyet gösteren iki havayolu şirketinin Veri Zarflama Analizi ile etkinlik ölçümü. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1107–1118. https://doi.org/10.16953/deusosbil.489000
  • Eremichev, A., & Aslanov, M. (2019). Turkish Airlines Versus Aeroflot. In International Journal of Economics and Management (Vol. 1, Issue 2). https://ssrn.com/abstract=3390667
  • Foong, J. J., O'Connell, J. F., Warnock-Smith, D., & Efthymiou, M. (2023). A product and organisational architecture analysis of the performance of Southeast Asian airlines. Journal of air transport management, 107, 102358.
  • Ji, Y.-B., & Lee, C. (2010). Data envelopment analysis. In The Stata Journal (Vol. 10, Issue 2).
  • Kiracı, K., & Bakır, M. (2019). CRITIC Temelli EDAS yöntemi ile havayolu işletmelerinde performans ölçümü uygulaması. Pamukkale University Journal of Social Sciences Institute, 35, 157–174. https://doi.org/10.30794/pausbed.421992
  • Kottas, A. T., & Madas, M. A. (2018). Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants. Journal of Air Transport Management, 70, 1–17. https://doi.org/10.1016/j.jairtraman.2018.04.014
  • Lang, P., Yolalan, O. R., & Kettani, O. (1995). Controlled Envelopment by Face Extension in DEA. The Journal of the Operational Research Society, 46(4), 473–491. https://doi.org/10.2307/2584595
  • Ling, Y. H., Kokkiang, T., Gharleghi, B., & Fah, B. C. Y. (2018). Productivity and efficiency modeling amongst ASEAN-5 airline industries. International Journal of Advanced and Applied Sciences, 5(8), 47–57. https://doi.org/10.21833/ijaas.2018.08.007
  • Mahmoudi, R., & Emrouznejad, A. (2023). A multi-period performance analysis of airlines: A game-SBM-NDEA and Malmquist Index approach. Research in Transportation Business & Management, 46, 100801.
  • 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: Policy and Practice, 45(7), 686–695. https://doi.org/10.1016/j.tra.2011.04.015
  • Merkert, R., & Williams, G. (2013). Determinants of European PSO airline efficiency – Evidence from a semi-parametric approach. Journal of Air Transport Management, 29, 11–16. https://doi.org/10.1016/J.JAIRTRAMAN.2012.12.002
  • Mhlanga, O., Steyn, J., & Spencer, J. (2018). The airline industry in South Africa: drivers of operational efficiency and impacts. Tourism Review, 73(3), 389–400. https://doi.org/10.1108/TR-07-2017-0111
  • Min, H., & Joo, S. J. (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52, 99–110. https://doi.org/10.1016/j.jairtraman.2015.12.003
  • Öncü, M. A., Çömlekçi, İ & Coşkun, E. (2013). Yolcu Taşıma İşletmelerinin Finansal Etkinliklerinin Ölçümüne İlişkin Bir Araştırma. Uluslararası Alanya İşletme Fakültesi Dergisi. 5(2), 77-86.
  • Özdağoğlu, A., Kemal Keleş, M., & Işildak, B. (2020). Isparta Süleyman Demirel Havalimanını kullanan havayolu firmaları Performanslarının BWM, MAIRCA ve MABAC ile Değerlendirilmesi. International Journal of Economic and Administrative Studies, 29, 175–194. https://orcid.org/0000-0001-5299-0622.
  • Rai, A. (2013). Measurement of efficiency in the airline industry using data envelopment analysis. Investment Management and Financial Innovations, 10(1), 38–45. http://orcid.org/0000-0001-7813-6117 Ramanathan, R. (2003). An introduction to data envelopment analysis: a tool for performance measurement. Sage.
  • Saranga, H., & Nagpal, R. (2016). Drivers of operational efficiency and its impact on market performance in the Indian Airline industry. Journal of Air Transport Management, 53, 165–176. https://doi.org/10.1016/J.JAIRTRAMAN.2016.03.001
  • Sümerli Sarıgül, S., Ünlü, M. & Yaşar, E. Financial Performance Analysis of Airlines Operating in Europe: CRITIC Based MAUT and MARCOS Methods. International Journal of Business and Economic Studies, 5(2), 76-97.
  • Scheraga, C. A. (2004). Operational efficiency versus financial mobility in the global airline industry: a data envelopment and Tobit analysis. Transportation Research Part A: Policy and Practice, 38(5), 383-404.
  • Shao, Y., & Sun, C. (2016). Performance evaluation of China’s air routes based on network data envelopment analysis approach. Journal of Air Transport Management, 55, 67–75. https://doi.org/10.1016/j.jairtraman.2016.01.006
  • Singh, A. K. (2011). Performance Evaluation of Indian Airline Industry: An Application of DEA. Asia Pacific Business Review, 7(2), 92–103.
  • Soltanzadeh, E., & Omrani, H. (2018). Dynamic network data envelopment analysis model with fuzzy inputs and outputs: An application for Iranian Airlines. Applied Soft Computing Journal, 63, 268–288. https://doi.org/10.1016/j.asoc.2017.11.031
  • Tavassoli, M., Faramarzi, G. R., & Farzipoor Saen, R. (2014). Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input. Journal of Air Transport Management, 34, 146–153. https://doi.org/10.1016/j.jairtraman.2013.09.001
  • Wang, C.-N., Dang, D.-C., Thanh, N. Van, & Tran, T.-T. (2018). Grey model and DEA to form virtual strategic alliance: The application for ASEAN aviation industry. International Journal of Advanced and Applied Sciences, 5(6), 25–34. https://doi.org/10.21833/ijaas.2018.06.004
  • Wanke, P., & Barros, C. P. (2016). Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression. Journal of Air Transport Management, 54, 93–103. https://doi.org/10.1016/J.JAIRTRAMAN.2016.04.001
  • Wanke, P., Pestana Barros, C., & Chen, Z. (2015). An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models. International Journal of Production Economics, 169, 110–126. https://doi.org/10.1016/J.IJPE.2015.07.028
  • Wing Chow, C. K. (2010). Measuring the productivity changes of Chinese airlines: The impact of the entries of non-state-owned carriers. Journal of Air Transport Management, 16(6), 320–324. https://doi.org/10.1016/J.JAIRTRAMAN.2010.04.001
  • Wu, W.-Y., & Liao, Y.-K. (2014). A balanced scorecard envelopment approach to assess airlines’ performance. Industrial Management & Data Systems, 114(1), 123–143. https://doi.org/10.1108/IMDS-03-2013-0135
  • Xu, Y., Park, Y. S., Park, J. D., & Cho, W. (2021). Evaluating the environmental efficiency of the U.S. airline industry using a directional distance function DEA approach. Journal of Management Analytics, 8(1), 1–18. https://doi.org/10.1080/23270012.2020.1832925
  • Yen, B. T. H., & Li, J. S. (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach. Transportation Research Part E: Logistics and Transportation Review, 162. https://doi.org/10.1016/j.tre.2022.102748
Toplam 51 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Etkinlik Yönetimi
Bölüm Makaleler
Yazarlar

Mehmet Yaşar 0000-0001-7237-4069

Erken Görünüm Tarihi 14 Ekim 2023
Yayımlanma Tarihi 15 Ekim 2023
Kabul Tarihi 12 Eylül 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 4 Sayı: 2

Kaynak Göster

APA Yaşar, M. (2023). HAVAYOLU İŞLETMELERİNDE HAT BAZLI OPERASYONEL PERFORMANSIN İŞ MODELİ TEMELİNDE DEĞERLENDİRİLMESİ. Malatya Turgut Özal Üniversitesi İşletme Ve Yönetim Bilimleri Dergisi, 4(2), 88-106.