Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2023, Cilt: 17 Sayı: 1, 236 - 237, 30.07.2023
https://doi.org/10.17261/Pressacademia.2023.1799

Öz

Kaynakça

  • Akbaba, A. (2022). Düzensiz operasyonların havayolu ücret politikalarına ve gelir yönetimine etkisi üzerine modelleme. İşletme Araştırmaları Dergisi, 14(4), 2833–2847.
  • Angelos T. Kottas and Michael A. Madas, (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,
  • Barbara T.H. Yen and Jun-Sheng Li, (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach. Transportation Research Part E: Logistics and Transportation Review, 162, 102748.
  • Erwin T.J. Lin, Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis: A comment, Transportation Research Part E: Logistics and Transportation Review, 44 (5), 894-899.
  • Hokey Min and Seong-Jong Joo, (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52, 99-110.
  • Madhavan, M., vd., (2020). Short-term forecasting for airline industry: the case of Indian air passenger and air cargo. Global Business Review, 1(2), 89-97.
  • Okursoy ve Tezsürücü, (2014). Veri zarflama analizi ile göreli etkinliklerin karşılaştırılması: Türkiye’deki illerin kültürel göstergelerine ilişkin bir uygulama. European Journal of Operational Research, 21(2), 1-18.
  • Özçelik H. ve Kandemir B., (2017). Veri zarflama analizi ve imalat sektöründe bir uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22 (1), 43-53.
  • Özden, Ü., H., (2008). Veri zarflama analizi (VZA) ile Türkiye’deki vakıf üniversitelerinin etkinliğinin ölçülmesi. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 37 (2), 167-185.
  • Qin, Peng, (2018). The revenue and cost of the airline company. Research in Economics and Management, 3(2),134-138.
  • Süzer, A. S. (2023). Dispeç kaynaklı aksaklıkların diğer operasyon birimlerine etkisi . Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 6(1), 123-138.
  • Ulrich Gunter and Bozana Zekan, (2021). Forecasting air passenger numbers with a GVAR model. Annals of Tourism Research, 89, 103252.
  • Unal Y, Z vd., (2021). A new approach to fleet assignment and aircraft routing problems. Transportation Research Procedia, 59, 67-75,
  • URL 1, Simpe Flying, (2023). How Do Airlines Plan New Routes? https://simpleflying.com/how-airlines-plan-new-routes/
  • URL 2, AN Aviaion Service, (2023). Phase of Flight, How Do Airlines Plan New Routes? https://an.aero/how-airlines-plan-for-new-route/
  • URL 3 Airways (2023). How Airlines Launch New Routes. https://airwaysmag.com/how-airlines-launch-new-routes/
  • URL 4 Sabre (2023). 4 Considerations Airlines Must Make When Planning New Routes. https://www.sabre.com/insights/4-considerations-airlines-must-make-when-planning-new-routes/
  • URL 5 International Airport Review (2023). The practice of airport and airline route development. https://www.internationalairportreview.com/article/111407/route-development-risks-limitations-flaws-results/
  • URL 6 SKYbrary (2023). Flight Operations Risk Assessment Checklist - New Destination.
  • URL 7 SKYbrary (2023). https://skybrary.aero/articles/flight-operations-risk-assessment-checklist-new-destination
  • URL 8 Aviation for Aviators (2023). Flight Operations Risk Assessment Checklist - New Destination. https://aviationforaviators.com/2021/03/23/which-planes-are-used-for-short-medium-and-long-haul-flights/
  • Wenliang Ma vd., (2019). An analysis of price competition and price wars in Australia's domestic airline market. Transport Policy, 81, 163-172.

DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS

Yıl 2023, Cilt: 17 Sayı: 1, 236 - 237, 30.07.2023
https://doi.org/10.17261/Pressacademia.2023.1799

Öz

Purpose- For airline companies to continue their operations, their growth is of critical importance. Increasing the number of passengers transported and/or cargo volume compared to the previous period is one way to gain a larger share of the market. At this point, selecting the most profitable potential flight routes is crucial in optimizing resource utilization. The aim of this study can be reported as selecting the most effective flight route through data envelopment analysis (DEA) from potential flight routes for evaluating aircraft resources in the airline industry.
Methodology- The study consists of two phases. In the first phase, effective flight routes are determined in three stages using the DEA method. In the second phase, the flight route to be flown was decided by evaluating factors such as transit passenger numbers and flight hours among the most effective routes determined in the first phase using the DEA method.
Findings- Despite having a flight time of more than 25 minutes longer than DMU 9, DMU 6 is forecasted to have an additional 26 transit passenger revenue. Therefore, it can be reported that DMU 6 is a more effective route than DMU 9. DMU 6 is executed with an average of 02:35 hours less flight time, despite the prediction of 8 transit passenger revenue less than DMU 7. Therefore, as using the aircraft resource for an additional flight would result in more revenue, DMU 6 may be a more effective route for the airline. These data indicate that DMU 6 is the optimal DMU for scheduling flights.
Conclusion- The aim of this study is to measure the efficiency of airline flight route selection using the DEA method. The results of the study reveal that the DEA method is not suitable for determining the most efficient flight route, but it can be used to eliminate inefficient flight routes and narrow down potential flight routes. To determine the most efficient route, it is critical to eliminate inefficient flight routes using the DEA method and evaluate other flight-related factors. This will help in identifying the optimal flight route

Kaynakça

  • Akbaba, A. (2022). Düzensiz operasyonların havayolu ücret politikalarına ve gelir yönetimine etkisi üzerine modelleme. İşletme Araştırmaları Dergisi, 14(4), 2833–2847.
  • Angelos T. Kottas and Michael A. Madas, (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,
  • Barbara T.H. Yen and Jun-Sheng Li, (2022). Route-based performance evaluation for airlines – A metafrontier data envelopment analysis approach. Transportation Research Part E: Logistics and Transportation Review, 162, 102748.
  • Erwin T.J. Lin, Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis: A comment, Transportation Research Part E: Logistics and Transportation Review, 44 (5), 894-899.
  • Hokey Min and Seong-Jong Joo, (2016). A comparative performance analysis of airline strategic alliances using data envelopment analysis. Journal of Air Transport Management, 52, 99-110.
  • Madhavan, M., vd., (2020). Short-term forecasting for airline industry: the case of Indian air passenger and air cargo. Global Business Review, 1(2), 89-97.
  • Okursoy ve Tezsürücü, (2014). Veri zarflama analizi ile göreli etkinliklerin karşılaştırılması: Türkiye’deki illerin kültürel göstergelerine ilişkin bir uygulama. European Journal of Operational Research, 21(2), 1-18.
  • Özçelik H. ve Kandemir B., (2017). Veri zarflama analizi ve imalat sektöründe bir uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22 (1), 43-53.
  • Özden, Ü., H., (2008). Veri zarflama analizi (VZA) ile Türkiye’deki vakıf üniversitelerinin etkinliğinin ölçülmesi. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 37 (2), 167-185.
  • Qin, Peng, (2018). The revenue and cost of the airline company. Research in Economics and Management, 3(2),134-138.
  • Süzer, A. S. (2023). Dispeç kaynaklı aksaklıkların diğer operasyon birimlerine etkisi . Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 6(1), 123-138.
  • Ulrich Gunter and Bozana Zekan, (2021). Forecasting air passenger numbers with a GVAR model. Annals of Tourism Research, 89, 103252.
  • Unal Y, Z vd., (2021). A new approach to fleet assignment and aircraft routing problems. Transportation Research Procedia, 59, 67-75,
  • URL 1, Simpe Flying, (2023). How Do Airlines Plan New Routes? https://simpleflying.com/how-airlines-plan-new-routes/
  • URL 2, AN Aviaion Service, (2023). Phase of Flight, How Do Airlines Plan New Routes? https://an.aero/how-airlines-plan-for-new-route/
  • URL 3 Airways (2023). How Airlines Launch New Routes. https://airwaysmag.com/how-airlines-launch-new-routes/
  • URL 4 Sabre (2023). 4 Considerations Airlines Must Make When Planning New Routes. https://www.sabre.com/insights/4-considerations-airlines-must-make-when-planning-new-routes/
  • URL 5 International Airport Review (2023). The practice of airport and airline route development. https://www.internationalairportreview.com/article/111407/route-development-risks-limitations-flaws-results/
  • URL 6 SKYbrary (2023). Flight Operations Risk Assessment Checklist - New Destination.
  • URL 7 SKYbrary (2023). https://skybrary.aero/articles/flight-operations-risk-assessment-checklist-new-destination
  • URL 8 Aviation for Aviators (2023). Flight Operations Risk Assessment Checklist - New Destination. https://aviationforaviators.com/2021/03/23/which-planes-are-used-for-short-medium-and-long-haul-flights/
  • Wenliang Ma vd., (2019). An analysis of price competition and price wars in Australia's domestic airline market. Transport Policy, 81, 163-172.
Toplam 22 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Makaleler
Yazarlar

Ali Akbaba Bu kişi benim 0000-0003-1745-8029

Yayımlanma Tarihi 30 Temmuz 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 17 Sayı: 1

Kaynak Göster

APA Akbaba, A. (2023). DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS. PressAcademia Procedia, 17(1), 236-237. https://doi.org/10.17261/Pressacademia.2023.1799
AMA Akbaba A. DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS. PAP. Temmuz 2023;17(1):236-237. doi:10.17261/Pressacademia.2023.1799
Chicago Akbaba, Ali. “DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS”. PressAcademia Procedia 17, sy. 1 (Temmuz 2023): 236-37. https://doi.org/10.17261/Pressacademia.2023.1799.
EndNote Akbaba A (01 Temmuz 2023) DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS. PressAcademia Procedia 17 1 236–237.
IEEE A. Akbaba, “DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS”, PAP, c. 17, sy. 1, ss. 236–237, 2023, doi: 10.17261/Pressacademia.2023.1799.
ISNAD Akbaba, Ali. “DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS”. PressAcademia Procedia 17/1 (Temmuz 2023), 236-237. https://doi.org/10.17261/Pressacademia.2023.1799.
JAMA Akbaba A. DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS. PAP. 2023;17:236–237.
MLA Akbaba, Ali. “DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS”. PressAcademia Procedia, c. 17, sy. 1, 2023, ss. 236-7, doi:10.17261/Pressacademia.2023.1799.
Vancouver Akbaba A. DETERMINATION OF NEW FLIGHT ROUTE WITH DEA METHOD IN AIRLINE OPERATIONS. PAP. 2023;17(1):236-7.

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