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Havayolu İşletmelerinde Bütünleşik Critic-Mavt Yöntemleri İle Performans Ölçümü

Yıl 2025, Cilt: 14 Sayı: 1, 338 - 353, 30.06.2025
https://doi.org/10.54282/inijoss.1676914

Öz

Havayolu taşımacılığı küresel anlamda sunduğu hızlı ulaşım hizmeti ile ekonomik büyüme, ticaret ve turizmin gelişmesinde büyük öneme sahiptir. Bu hizmeti veren havayolu işletmeleri dalgalı yakıt fiyatları, değişken talep, yoğun rekabet karşısında bu hizmeti vermek durumunda kalmaktadır. Bu değişken ve zorlayıcı dış koşullar havayolu işletmelerinin kendilerinin ve rakiplerinin performansını sürekli takip etmeyi gerektirmektedir. Bu çalışmada havayolu işletmelerinin operasyonel ve finansal performansları çok kriterli karar verme yöntemleri ile analiz edilmiştir. Bu kapsamda CRITIC yöntemi ile belirlenen kriterler ağırlıklandırılmış, MAVT yöntemi ile de havayolu işletmeleri sıralanmıştır. Kriterler Arz Edilen Koltuk-Mil, Ücretli Yolcu-Mil gibi operasyonel parametreler ile Faaliyet Kar Marjı, Birim Gelir, Piyasa Değeri, Aktif Karlılığı, Toplam Borcun Toplam Sermayeye oranı gibi finansal parametrelerden oluşmaktadır. Havayolu işletmeleri ise dünya çapında faaliyet gösteren büyük ve geniş uçuş ağına sahip 12 havayolu işletmesidir. Elde edilen bulgulara göre en büyük ağırlığa sahip kriterin ortalama olarak piyasa değeri olduğu, en düşük ağırlığa sahip kriterin ise aktif karlılığı olduğu ortaya çıkmıştır. Piyasa değeri tüm yıllarda en yüksek ağırlığa sahip kriterdir ancak diğer kriterlerin göreli ağırlıkları yıllar içerisinde farklılık göstermektedir. Araştırma sonucunda Kuzey Amerika menşeili havayolu işletmelerinin 2019-2023 dönemi için en iyi performansı gösteren havayolu işletmeleri olduğu ortaya çıkmıştır. Araştırmanın karar verici ve politika yapıcılara yatırım, istihdam gibi alanlarda katkı sağlaması beklenmektedir.

Kaynakça

  • Abdi, Y., Li, X., & Càmara-Turull, X. (2020). Impact of sustainability on firm value and financial performance in the air transport industry. Sustainability, 12(23), 9957.
  • Alemayehu, W., & vom Brocke, J. (2010, September). Sustainability performance measurement–the case of Ethiopian airlines. In International Conference on Business Process Management (pp. 467-478). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Andoko, A., & Angeline, A. (2023). The Influence Of Debt To Equity Ratio, Operating Profit Margin Ratio And Operating Expense Toward Entity Income Tax Of Infrastructure, Utility And Transportation Companies Listed On The Indonesia Stock Exchange. International Journal of Sociıal, Policy and Law, 4(1), 58-68. https://doi.org/10.8888/ijospl.v4i1.115
  • Asatryan, R., & Březinová, O. (2014). Corporate social responsibility and financial performance in the airline industry in central and eastern Europe. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 62(4), 633-639.
  • Asker, V. (2024). Financial Performance Analysis Using the Merec-Based Cobra Method: An Application to Traditional and Low-Cost Airlines. Gospodarka Narodowa. The Polish Journal of Economics, 318(2), 35-52.
  • Bakir, M., Akan, Ş., Kiraci, K., Karabasevic, D., Stanujkic, D., & Popovic, G. (2020). Multiple-criteria approach of the operational performance evaluation in the airline industry: Evidence from the emerging markets. Romanian Journal of Economic Forecasting, 23(2), 149-172.
  • Bassanini, F., & Reviglio, E. (2011). Financial stability, fiscal consolidation and long-term investment after the crisis. OECD Journal: Financial Market Trends, 1, 1-45.
  • Batrancea, L. M., Nichita, A., & Cocis, A. D. (2022). Financial performance and sustainable corporate reputation: Empirical evidence from the airline business. Sustainability, 14(20), 13567.
  • Bhadra, D. (2009). Race to the bottom or swimming upstream: performance analysis of US airlines. Journal of Air Transport Management, 15(5), 227-235.
  • Cento, A. (2009). The airline industry: challenges in the 21st century, Verlag-Heidelberg, Heidelberg. doi:10.1007/978-3-7908-2088-1.
  • Chairunisa, S. S., Digdowiseiso, K., & Karyatun, S. (2023). The Effect of Total Assets Turnover, Debt to Assets Ratio, Cash Ratio and Current Ratio on Financial Performance of Companies The Hotel, Restaurant and Tourism Subsector in IDX for The Period 2016-2020. Jurnal Syntax Admiration, 4(3), 548-558.
  • Davila, A., Venkatachalam, M. (2004). The Relevance of Non-financial Performance Measures for CEO Compensation: Evidence from the Airline Industry. Rev Acc Stud 9, 443–464. https://doi.org/10.1007/s11142-004-7792-8
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763-770.
  • Dike, S. E., Davis, Z., Abrahams, A., Anjomshoae, A., & Ractham, P. (2024). Evaluation of passengers' expectations and satisfaction in the airline industry: an empirical performance analysis of online reviews. Benchmarking: An International Journal, 31(2), 611-639.
  • Donovan, A. W. (2005). Yield Management in the Airline Industry. Journal of Aviation/Aerospace Education & Research, 14(3). DOI: https://doi.org/10.58940/2329-258X.1522
  • Ferretti, V., Bottero, M., & Mondini, G. (2014). Decision making and cultural heritage: An application of the Multi-Attribute Value Theory for the reuse of historical buildings. Journal of cultural heritage, 15(6), 644-655.
  • Fishburn, P. C. (1967). Methods of Estimating Additive Utilities, Manage. Sci. 13 435–453.
  • Francis, G., Humphreys, I., & Fry, J. (2005). The nature and prevalence of the use of performance measurement techniques by airlines. Journal of Air Transport Management, 11(4), 207-217.
  • Gerede, E. (2015), “Havayolu İşletmeciliğine İlişkin Temel Kavramlar”, in: Havayolu Taşımacılığı ve Ekonomik Düzenlemeler Teori ve Türkiye Uygulaması, 1-46.
  • Kao, F. C., Ting, I. W. K., Chou, H. C., & Liu, Y. S. (2022). Exploring the influence of corporate social responsibility on efficiency: An extended dynamic data envelopment analysis of the global airline industry. Sustainability, 14(19), 12712.
  • Kaur, G., Dhara, A., Majumder, A., Sandhu, B. S., Puhan, A., & Adhikari, M. S. (2023). A CRITIC-TOPSIS MCDM technique under the neutrosophic environment with application on aircraft selection. Contemporary Mathematics, 1180-1203.
  • Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.
  • Kiracı, K., & Yaşar, M. (2020). The Determinants of Airline Operational Performance: An Empirical Study on Major World Airlines. Sosyoekonomi, 28(43), 107-117. https://doi.org/10.17233/sosyoekonomi.2020.01.06
  • Krishnan, A. R., Kasim, M. M., Hamid, R., & Ghazali, M. F. (2021). A modified CRITIC method to estimate the objective weights of decision criteria. Symmetry, 13(6), 973.
  • Krišto, J., Stojanović, A., & Pavković, A. (2014). Impact of institutional investors on financial market stability: lessons from financial crisis. International Journal of Diplomacy and Economy 1, 2(1-2), 102-117.
  • Lee, J. (2019). Effects of operational performance on financial performance. Management Science Letters, 9(1), 25-32.
  • Liedtka, S. L. (2002). The information content of nonfinancial performance measures in the airline industry. Journal of Business Finance & Accounting, 29(7‐8), 1105-1121.
  • Madic, M., & Radovanovic, M. (2015). Ranking of some most commonly used non-traditional machining processes using ROV and CRITIC methods. UPB Scientific Bulletin, Series D, 77(2), 193–204.
  • Mahesh, R., & Prasad, D. (2012). Post-merger and acquisition financial performance analysis: A case study of select Indian airline companies. International journal of engineering and management sciences, 3(3), 362-369.
  • 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.
  • Montibeller, G., Yoshizaki, H. (2011). A Framework for Locating Logistic Facilities with Multi-Criteria Decision Analysis. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_35
  • Nasir, A. M., Ahmed, A., & Barkat, W. (2017). Operational performance and financial performance of Malaysia Airlines. Paradigms, 11(1), 34.
  • Nguyen, M. A. T., Yu, M. M., & Lirn, T. C. (2022). Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach. Transport Policy, 117, 108-117.
  • Özdağoğlu, A., Ustaömer, T. C., & Keleş, M. K. (2022). Performance Evaluation in Airline Industry with Critic and Merec Based Maut and Psi Methods. Transport & Logistics, 22(52).
  • Pineda, P. J. G., Liou, J. J., Hsu, C. C., & Chuang, Y. C. (2018). An integrated MCDM model for improving airline operational and financial performance. Journal of Air Transport Management, 68, 103-117.
  • Raiffa, H. (1969). Preference for multi-attributed alternatives, RM-5868-DOT/RC, The RAND Corporation, Santa Monica, CA.
  • Sarıgül, S. S., Ünlü, M., & Yaşar, E. (2023). 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.
  • Schefczyk, M. (1993). Operational performance of airlines: an extension of traditional measurement paradigms. Strategic management journal, 14(4), 301-317.
  • Tanrıverdi, G., Merkert, R., Karamaşa, Ç., & Asker, V. (2023). Using multi-criteria performance measurement models to evaluate the financial, operational and environmental sustainability of airlines. Journal of Air Transport Management, 112, 102456.
  • Teker, S., Teker, D., & Güner, A. (2016). Financial performance of top 20 airlines. Procedía-Social and behavioral sciences, 235, 603-610.
  • Xie, Y., & Li Z. J., Xu, Z. (2014). Evaluation on spontaneous combustion trend of sulfide ores based on the method of CRITIC and TOPSIS testing method. Journal of Safety and Environment, 14(1), 122–125.
  • Yasar, M., Asker, V., & Ozdemir, E. (2018). Havayolu şehir çifti pazarlarinda veri zarflama analizi ve malmquist toplam faktör verimliliği endeksi yöntemleriyle etkinlik ölçümü. PressAcademia Procedia, 7(1), 228-232. https://doi.org/10.17261/Pressacademia.2018.886
  • Yaşar, M. (2023). Havayolu Işletmelerinde Hat Bazli Operasyonel Performansin Iş Modeli Temelinde Değerlendirilmesi. Malatya Turgut Özal Üniversitesi İşletme ve Yönetim Bilimleri Dergisi, 4(2), 88-106.
  • Yaşar, M. (2024). Investigating the Air Travel-Tourism Relationship Using Granger Causality Analysis: The Case of Turkish Destinations. Studies in Business and Economics, 19(1), 301-316.
  • Yaşar, M., & Gerede, E. (2023). Examination of the factors determining the operational and financial performance of airlines: The case of the Turkish international airline market. Journal of Entrepreneurship, Management & Innovation, 19(4), 111-145.
  • Yu, C. (2016). Airline productivity and efficiency: concept, measurement, and applications. In Airline Efficiency (pp. 11-53). Emerald Group Publishing Limited.
  • Zafar, S., Alamgir, Z., & Rehman, M. H. (2021). An effective blockchain evaluation system based on entropy-CRITIC weight method and MCDM techniques. Peer-to-Peer Networking and Applications, 14(5), 3110-3123. Zhang, Q., Koutmos, D., Chen, K., & Zhu, J. (2021). Using operational and stock analytics to measure airline performance: A network DEA approach. Decision Sciences, 52(3), 720-748.

Performance Measurement in Airlines With Integrated Critic-Mavt Method

Yıl 2025, Cilt: 14 Sayı: 1, 338 - 353, 30.06.2025
https://doi.org/10.54282/inijoss.1676914

Öz

Airline transportation has a great importance in promoting economic growth, trade, and tourism through the fast and efficient services it offers globally. Airlines have to provide this service in the face of fluctuating fuel prices, volatile demand and intense competition. These volatile and challenging external conditions require airlines to constantly monitor their own and their competitors' performance. This study analyzes the operational and financial performance of global airline companies using multi-criteria decision-making (MCDM) methods. In this context, the criteria determined by CRITIC method are weighted and the airlines are ranked by MAVT method. The criteria consist of operational parameters such as Available Seat-Miles, Revenue Passenger-Miles and financial parameters such as Operating Profit Margin, Yield, Market Value, Return on Assets, Total Debt to Total Capitalization ratio. The analysis covers 12 major international airlines with large and extensive flight networks. According to the findings, the criterion with the highest weight is market value on average, while the criterion with the lowest weight is return on assets. Market value is the criterion with the highest weight in all years, but the relative weights of other criteria vary over the years. Overall, the results reveal that North American airlines exhibited the strongest performance during the 2019–2023 period. The study is expected to provide valuable insights for decision-makers and policy-makers in areas such as investment and employment strategies.

Kaynakça

  • Abdi, Y., Li, X., & Càmara-Turull, X. (2020). Impact of sustainability on firm value and financial performance in the air transport industry. Sustainability, 12(23), 9957.
  • Alemayehu, W., & vom Brocke, J. (2010, September). Sustainability performance measurement–the case of Ethiopian airlines. In International Conference on Business Process Management (pp. 467-478). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Andoko, A., & Angeline, A. (2023). The Influence Of Debt To Equity Ratio, Operating Profit Margin Ratio And Operating Expense Toward Entity Income Tax Of Infrastructure, Utility And Transportation Companies Listed On The Indonesia Stock Exchange. International Journal of Sociıal, Policy and Law, 4(1), 58-68. https://doi.org/10.8888/ijospl.v4i1.115
  • Asatryan, R., & Březinová, O. (2014). Corporate social responsibility and financial performance in the airline industry in central and eastern Europe. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 62(4), 633-639.
  • Asker, V. (2024). Financial Performance Analysis Using the Merec-Based Cobra Method: An Application to Traditional and Low-Cost Airlines. Gospodarka Narodowa. The Polish Journal of Economics, 318(2), 35-52.
  • Bakir, M., Akan, Ş., Kiraci, K., Karabasevic, D., Stanujkic, D., & Popovic, G. (2020). Multiple-criteria approach of the operational performance evaluation in the airline industry: Evidence from the emerging markets. Romanian Journal of Economic Forecasting, 23(2), 149-172.
  • Bassanini, F., & Reviglio, E. (2011). Financial stability, fiscal consolidation and long-term investment after the crisis. OECD Journal: Financial Market Trends, 1, 1-45.
  • Batrancea, L. M., Nichita, A., & Cocis, A. D. (2022). Financial performance and sustainable corporate reputation: Empirical evidence from the airline business. Sustainability, 14(20), 13567.
  • Bhadra, D. (2009). Race to the bottom or swimming upstream: performance analysis of US airlines. Journal of Air Transport Management, 15(5), 227-235.
  • Cento, A. (2009). The airline industry: challenges in the 21st century, Verlag-Heidelberg, Heidelberg. doi:10.1007/978-3-7908-2088-1.
  • Chairunisa, S. S., Digdowiseiso, K., & Karyatun, S. (2023). The Effect of Total Assets Turnover, Debt to Assets Ratio, Cash Ratio and Current Ratio on Financial Performance of Companies The Hotel, Restaurant and Tourism Subsector in IDX for The Period 2016-2020. Jurnal Syntax Admiration, 4(3), 548-558.
  • Davila, A., Venkatachalam, M. (2004). The Relevance of Non-financial Performance Measures for CEO Compensation: Evidence from the Airline Industry. Rev Acc Stud 9, 443–464. https://doi.org/10.1007/s11142-004-7792-8
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763-770.
  • Dike, S. E., Davis, Z., Abrahams, A., Anjomshoae, A., & Ractham, P. (2024). Evaluation of passengers' expectations and satisfaction in the airline industry: an empirical performance analysis of online reviews. Benchmarking: An International Journal, 31(2), 611-639.
  • Donovan, A. W. (2005). Yield Management in the Airline Industry. Journal of Aviation/Aerospace Education & Research, 14(3). DOI: https://doi.org/10.58940/2329-258X.1522
  • Ferretti, V., Bottero, M., & Mondini, G. (2014). Decision making and cultural heritage: An application of the Multi-Attribute Value Theory for the reuse of historical buildings. Journal of cultural heritage, 15(6), 644-655.
  • Fishburn, P. C. (1967). Methods of Estimating Additive Utilities, Manage. Sci. 13 435–453.
  • Francis, G., Humphreys, I., & Fry, J. (2005). The nature and prevalence of the use of performance measurement techniques by airlines. Journal of Air Transport Management, 11(4), 207-217.
  • Gerede, E. (2015), “Havayolu İşletmeciliğine İlişkin Temel Kavramlar”, in: Havayolu Taşımacılığı ve Ekonomik Düzenlemeler Teori ve Türkiye Uygulaması, 1-46.
  • Kao, F. C., Ting, I. W. K., Chou, H. C., & Liu, Y. S. (2022). Exploring the influence of corporate social responsibility on efficiency: An extended dynamic data envelopment analysis of the global airline industry. Sustainability, 14(19), 12712.
  • Kaur, G., Dhara, A., Majumder, A., Sandhu, B. S., Puhan, A., & Adhikari, M. S. (2023). A CRITIC-TOPSIS MCDM technique under the neutrosophic environment with application on aircraft selection. Contemporary Mathematics, 1180-1203.
  • Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.
  • Kiracı, K., & Yaşar, M. (2020). The Determinants of Airline Operational Performance: An Empirical Study on Major World Airlines. Sosyoekonomi, 28(43), 107-117. https://doi.org/10.17233/sosyoekonomi.2020.01.06
  • Krishnan, A. R., Kasim, M. M., Hamid, R., & Ghazali, M. F. (2021). A modified CRITIC method to estimate the objective weights of decision criteria. Symmetry, 13(6), 973.
  • Krišto, J., Stojanović, A., & Pavković, A. (2014). Impact of institutional investors on financial market stability: lessons from financial crisis. International Journal of Diplomacy and Economy 1, 2(1-2), 102-117.
  • Lee, J. (2019). Effects of operational performance on financial performance. Management Science Letters, 9(1), 25-32.
  • Liedtka, S. L. (2002). The information content of nonfinancial performance measures in the airline industry. Journal of Business Finance & Accounting, 29(7‐8), 1105-1121.
  • Madic, M., & Radovanovic, M. (2015). Ranking of some most commonly used non-traditional machining processes using ROV and CRITIC methods. UPB Scientific Bulletin, Series D, 77(2), 193–204.
  • Mahesh, R., & Prasad, D. (2012). Post-merger and acquisition financial performance analysis: A case study of select Indian airline companies. International journal of engineering and management sciences, 3(3), 362-369.
  • 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.
  • Montibeller, G., Yoshizaki, H. (2011). A Framework for Locating Logistic Facilities with Multi-Criteria Decision Analysis. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_35
  • Nasir, A. M., Ahmed, A., & Barkat, W. (2017). Operational performance and financial performance of Malaysia Airlines. Paradigms, 11(1), 34.
  • Nguyen, M. A. T., Yu, M. M., & Lirn, T. C. (2022). Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach. Transport Policy, 117, 108-117.
  • Özdağoğlu, A., Ustaömer, T. C., & Keleş, M. K. (2022). Performance Evaluation in Airline Industry with Critic and Merec Based Maut and Psi Methods. Transport & Logistics, 22(52).
  • Pineda, P. J. G., Liou, J. J., Hsu, C. C., & Chuang, Y. C. (2018). An integrated MCDM model for improving airline operational and financial performance. Journal of Air Transport Management, 68, 103-117.
  • Raiffa, H. (1969). Preference for multi-attributed alternatives, RM-5868-DOT/RC, The RAND Corporation, Santa Monica, CA.
  • Sarıgül, S. S., Ünlü, M., & Yaşar, E. (2023). 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.
  • Schefczyk, M. (1993). Operational performance of airlines: an extension of traditional measurement paradigms. Strategic management journal, 14(4), 301-317.
  • Tanrıverdi, G., Merkert, R., Karamaşa, Ç., & Asker, V. (2023). Using multi-criteria performance measurement models to evaluate the financial, operational and environmental sustainability of airlines. Journal of Air Transport Management, 112, 102456.
  • Teker, S., Teker, D., & Güner, A. (2016). Financial performance of top 20 airlines. Procedía-Social and behavioral sciences, 235, 603-610.
  • Xie, Y., & Li Z. J., Xu, Z. (2014). Evaluation on spontaneous combustion trend of sulfide ores based on the method of CRITIC and TOPSIS testing method. Journal of Safety and Environment, 14(1), 122–125.
  • Yasar, M., Asker, V., & Ozdemir, E. (2018). Havayolu şehir çifti pazarlarinda veri zarflama analizi ve malmquist toplam faktör verimliliği endeksi yöntemleriyle etkinlik ölçümü. PressAcademia Procedia, 7(1), 228-232. https://doi.org/10.17261/Pressacademia.2018.886
  • Yaşar, M. (2023). Havayolu Işletmelerinde Hat Bazli Operasyonel Performansin Iş Modeli Temelinde Değerlendirilmesi. Malatya Turgut Özal Üniversitesi İşletme ve Yönetim Bilimleri Dergisi, 4(2), 88-106.
  • Yaşar, M. (2024). Investigating the Air Travel-Tourism Relationship Using Granger Causality Analysis: The Case of Turkish Destinations. Studies in Business and Economics, 19(1), 301-316.
  • Yaşar, M., & Gerede, E. (2023). Examination of the factors determining the operational and financial performance of airlines: The case of the Turkish international airline market. Journal of Entrepreneurship, Management & Innovation, 19(4), 111-145.
  • Yu, C. (2016). Airline productivity and efficiency: concept, measurement, and applications. In Airline Efficiency (pp. 11-53). Emerald Group Publishing Limited.
  • Zafar, S., Alamgir, Z., & Rehman, M. H. (2021). An effective blockchain evaluation system based on entropy-CRITIC weight method and MCDM techniques. Peer-to-Peer Networking and Applications, 14(5), 3110-3123. Zhang, Q., Koutmos, D., Chen, K., & Zhu, J. (2021). Using operational and stock analytics to measure airline performance: A network DEA approach. Decision Sciences, 52(3), 720-748.
Toplam 47 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Uluslararası İşletme
Bölüm Makaleler
Yazarlar

Selçuk Kayhan 0000-0001-9291-4528

Erken Görünüm Tarihi 26 Haziran 2025
Yayımlanma Tarihi 30 Haziran 2025
Gönderilme Tarihi 15 Nisan 2025
Kabul Tarihi 14 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 14 Sayı: 1

Kaynak Göster

APA Kayhan, S. (2025). Performance Measurement in Airlines With Integrated Critic-Mavt Method. İnönü Üniversitesi Uluslararası Sosyal Bilimler Dergisi, 14(1), 338-353. https://doi.org/10.54282/inijoss.1676914