Araştırma Makalesi
BibTex RIS Kaynak Göster

HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ

Yıl 2019, Cilt: 9 Sayı: 1, 144 - 149, 30.07.2019
https://doi.org/10.17261/Pressacademia.2019.1082

Öz

Amaç-
Bu çalışmanın temel amacı, 1990’lı yılların
başından itibaren büyük bir yükseliş trendine giren ve globalleşen Dünyada
mevcut değişimlerden en fazla etkilenen sektörlerden olan Sivil Havacılık
büyüme oranı olarak son yirmi beş yıla damgasını vurmuştur. Bu yirmi beş yıllık
büyümede havayolları farklı stratejilerle birbirleri ile büyük bir rekabet
içerisine girmişlerdir. Bu rekabet ortamında havayollarını en çok etkileyen
konuların başında filo planlaması gelmektedir. Bir diğer büyük gider kalemi
olan yakıt fiyatlarının özel anlaşmalar dışında değişiklik göstermediğini
varsaydığımız zaman, havayollarının misyon ve vizyonlarına uygun uçakların
bünyeye katılması ve bu doğrultuda bünyeye katılan uçakların en optimal şekilde
kullanılmasıdır.

Yöntem-
Bu amaca ulaşmak için, sivil havacılık
sektöründe son yirmi beş yıldaki önemli gelişmelerin literatür taraması
yapılmış olup, tüm bu literatür taraması aşama aşama incelenerek okuyucuya
sunulmuştur.





Sonuç-
Yapılan analizler sonucunda, sivil havacılık
sektörünün son yirmi beş yılda hem teknolojik, hem de müşteri memnuniyetine
yönelik büyük oranda farklılaştığı ortaya çıkmıştır. Bu farklılaşmanın en
önemli unsurunu se 90’lı yılların başında uygulamaya geçen ve 2000’li yılların
başında gitgide yaygınlaşmaya başlayan düşük maliyetli taşımacılık
stratejisinin bu büyüme ve farklılaşmayı büyük oranda etkilemesidir.

Kaynakça

  • Bharda, D. (2003). Choice of Aircraft Fleets in the US NAS: Findings from a Multinomial Logit Analysis. https://www.mitre.org/sites/default/files/pdf/bhadra_ analysis.pdf. Erişim Tarihi 01.01.2018
  • Clark, P. (2001). “Buying the Big Jets, Fleet Planning for Airlines”, Aldershot: Asqate.
  • Dozic, S., Kalic, M. (2015). Three-stage airline fleet planning model. Journal of Air Transportation Management, 46, p. 30-39.
  • Givoni, M., Reitveld, P. (2009). Choice of aircraft size e explanations and implications. J. Air Transp. Manag., 16, p. 159-167.
  • Givoni, M., Reitveld, P. (2010). The environmental implications of airlines' choice of aircraft size. Transp. Res. A Policy Pract., 43, p. 500-510.
  • Gomes, L.F.A.M., Fernandes, J.E.M., Soares de Mello, J.C.C.B., 2014. A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. J. Adv. Transp., 48, p. 223-237.
  • Hammond, J.S., Keeney, R.L., Raifa, H. (1998). Even swaps: a rational method for making trade-offs. Harv. Bus. Rev., 76, p. 137-150.
  • Hammond, J.S., Keeney, R.L. (1999a). Smart Choices: a Practical Guide to Making Better Decisions. Harvard Business School Press, Boston.
  • Hammond, J.S., Keeney, R.L. (1999b). Making smart choices in engineering. IEEE Spectr., 36, p. 71-76.
  • Harasani, W.I. (2006). Evaluation and Selection of a Fleet of Aircraft for a Local Airline Aeronautical Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia JKAU: Eng. Sci., 17(2), p. 3-16.
  • Kalic, M., Kuljanin, J., Dozic, S. (2013). Air travel demand fuzzy modelling: trip generation and trip distribution. In: Snasel, V., Kromer, P., Koppen, M., Schaefer, G. (Eds.), Soft Computing in Industrial Applications. Springer, New York, p. 279-290. http://dx.doi.org/10.1007/978-3-319-00930-8. Erişim Tarihi 02.01.2018
  • Kilipi, J. (2007). Fleet composition of commercial jet aircraft 1952-2005: developments in uniformity and scale. J. Air Transp. Manag., 13, p. 81-89.
  • Listes, O., Dekker, R. (2005). A scenario aggregation-based approach for determining a robust airline fleet composition for dynamic capacity allocation. Transp. Sci., 39, p. 367-382.
  • Oum, T.H., Zhang, A., Zhang, Y. (2000). Optimal demand for operating lease of aircraft. Transp. Res. B Methodol., 34, p. 17-29.
  • Ozdemir, Y., Basligil, H., Karaca, M. (2011). Aircraft Selection Using Analytic Network Process: a Case for Turkish Airlines. http://www.iaeng.org/publication/ WCE2011/WCE2011, 1155-1159.pdf. Erişim Tarihi 03.01.2018.
  • Pai, V. (2010). On the factors that affect airline flight frequencies and aircraft size. J. Air Transp. Manag., 16, p. 169-177.
  • Snow, J. (2004). Fleet Planning Workshop June, Cranfield University.
  • Taylor, J.W.R. (2005). “Jane’s All the World Aircraft”, Jane’s Publishing Company. (2004-2005).
  • Teodorovic, D. (1999). Fuzzy logic systems for transportation engineering: the state of the art. Transp. Res. A Policy Pract., 33, p. 337-364.
  • Wei, W., Hansen, M., (2005). Impact of aircraft size and seat availability on airlines' demand and market share in duopoly markets. Transp. Res. E Logist. Transp. Rev., 41, p. 315-327.

STRATEGIES TO BE IMPLEMENTED ABOUT FLEET PLANNING IN AIRLINES AND THE EXAMINATION OF TRIPLE FLEET PLANNING MODEL

Yıl 2019, Cilt: 9 Sayı: 1, 144 - 149, 30.07.2019
https://doi.org/10.17261/Pressacademia.2019.1082

Öz

Purpose-
The main aim of this study is to determine
civil aviation sector which mostly affected by current changes in the world and
has entered a great upward trend since the beginning of the 1990s with
globalized and marked at the last twenty five years as a growth rate. In this
twenty five years old growth, airlines have competed each other with a wide
range of strategies. In this competitive environment, fleet planning is one of
the forefront issues which affect airlines. Another major expense item fuel
prices are not changed except by special agreements and the most optimal use of
aircrafts about participated aircrafts appropriate with the missions and
visions of airlines.

Methodology-
In order to achieve this aim, the literature
review of the important developments in the civil aviation sector in the last
twentyfive years has been carried out and all these literature surveys have
been examined and presented to the reader.





Conclusion- As a result of the
analyzes, it has been revealed that the civil aviation sector has diversified
greatly in terms of both technological and customer satisfaction in the last
twenty-five years. The most important element of this differentiation is the
low-cost transport strategy that started to be implemented in the early 90s and
started to become more widespread in the early 2000s.

Kaynakça

  • Bharda, D. (2003). Choice of Aircraft Fleets in the US NAS: Findings from a Multinomial Logit Analysis. https://www.mitre.org/sites/default/files/pdf/bhadra_ analysis.pdf. Erişim Tarihi 01.01.2018
  • Clark, P. (2001). “Buying the Big Jets, Fleet Planning for Airlines”, Aldershot: Asqate.
  • Dozic, S., Kalic, M. (2015). Three-stage airline fleet planning model. Journal of Air Transportation Management, 46, p. 30-39.
  • Givoni, M., Reitveld, P. (2009). Choice of aircraft size e explanations and implications. J. Air Transp. Manag., 16, p. 159-167.
  • Givoni, M., Reitveld, P. (2010). The environmental implications of airlines' choice of aircraft size. Transp. Res. A Policy Pract., 43, p. 500-510.
  • Gomes, L.F.A.M., Fernandes, J.E.M., Soares de Mello, J.C.C.B., 2014. A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. J. Adv. Transp., 48, p. 223-237.
  • Hammond, J.S., Keeney, R.L., Raifa, H. (1998). Even swaps: a rational method for making trade-offs. Harv. Bus. Rev., 76, p. 137-150.
  • Hammond, J.S., Keeney, R.L. (1999a). Smart Choices: a Practical Guide to Making Better Decisions. Harvard Business School Press, Boston.
  • Hammond, J.S., Keeney, R.L. (1999b). Making smart choices in engineering. IEEE Spectr., 36, p. 71-76.
  • Harasani, W.I. (2006). Evaluation and Selection of a Fleet of Aircraft for a Local Airline Aeronautical Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia JKAU: Eng. Sci., 17(2), p. 3-16.
  • Kalic, M., Kuljanin, J., Dozic, S. (2013). Air travel demand fuzzy modelling: trip generation and trip distribution. In: Snasel, V., Kromer, P., Koppen, M., Schaefer, G. (Eds.), Soft Computing in Industrial Applications. Springer, New York, p. 279-290. http://dx.doi.org/10.1007/978-3-319-00930-8. Erişim Tarihi 02.01.2018
  • Kilipi, J. (2007). Fleet composition of commercial jet aircraft 1952-2005: developments in uniformity and scale. J. Air Transp. Manag., 13, p. 81-89.
  • Listes, O., Dekker, R. (2005). A scenario aggregation-based approach for determining a robust airline fleet composition for dynamic capacity allocation. Transp. Sci., 39, p. 367-382.
  • Oum, T.H., Zhang, A., Zhang, Y. (2000). Optimal demand for operating lease of aircraft. Transp. Res. B Methodol., 34, p. 17-29.
  • Ozdemir, Y., Basligil, H., Karaca, M. (2011). Aircraft Selection Using Analytic Network Process: a Case for Turkish Airlines. http://www.iaeng.org/publication/ WCE2011/WCE2011, 1155-1159.pdf. Erişim Tarihi 03.01.2018.
  • Pai, V. (2010). On the factors that affect airline flight frequencies and aircraft size. J. Air Transp. Manag., 16, p. 169-177.
  • Snow, J. (2004). Fleet Planning Workshop June, Cranfield University.
  • Taylor, J.W.R. (2005). “Jane’s All the World Aircraft”, Jane’s Publishing Company. (2004-2005).
  • Teodorovic, D. (1999). Fuzzy logic systems for transportation engineering: the state of the art. Transp. Res. A Policy Pract., 33, p. 337-364.
  • Wei, W., Hansen, M., (2005). Impact of aircraft size and seat availability on airlines' demand and market share in duopoly markets. Transp. Res. E Logist. Transp. Rev., 41, p. 315-327.
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Finans, İşletme
Bölüm Makaleler
Yazarlar

Tuzun Tolga Inan 0000-0002-5937-9217

Yayımlanma Tarihi 30 Temmuz 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 9 Sayı: 1

Kaynak Göster

APA Inan, T. T. (2019). HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ. PressAcademia Procedia, 9(1), 144-149. https://doi.org/10.17261/Pressacademia.2019.1082
AMA Inan TT. HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ. PAP. Temmuz 2019;9(1):144-149. doi:10.17261/Pressacademia.2019.1082
Chicago Inan, Tuzun Tolga. “HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ”. PressAcademia Procedia 9, sy. 1 (Temmuz 2019): 144-49. https://doi.org/10.17261/Pressacademia.2019.1082.
EndNote Inan TT (01 Temmuz 2019) HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ. PressAcademia Procedia 9 1 144–149.
IEEE T. T. Inan, “HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ”, PAP, c. 9, sy. 1, ss. 144–149, 2019, doi: 10.17261/Pressacademia.2019.1082.
ISNAD Inan, Tuzun Tolga. “HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ”. PressAcademia Procedia 9/1 (Temmuz 2019), 144-149. https://doi.org/10.17261/Pressacademia.2019.1082.
JAMA Inan TT. HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ. PAP. 2019;9:144–149.
MLA Inan, Tuzun Tolga. “HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ”. PressAcademia Procedia, c. 9, sy. 1, 2019, ss. 144-9, doi:10.17261/Pressacademia.2019.1082.
Vancouver Inan TT. HAVAYOLLARINDA FİLO PLANLAMASI DOĞRULTUSUNDA UYGULANAN STRATEJİLER VE ÜÇLÜ FİLO PLANLAMA MODELİNİN İNCELENMESİ. PAP. 2019;9(1):144-9.

PressAcademia Procedia (PAP) publishes proceedings of conferences, seminars and symposiums. PressAcademia Procedia aims to provide a source for academic researchers, practitioners and policy makers in the area of social and behavioral sciences, and engineering.

PressAcademia Procedia invites academic conferences for publishing their proceedings with a review of editorial board. Since PressAcademia Procedia is an double blind peer-reviewed open-access book, the manuscripts presented in the conferences can easily be reached by numerous researchers. Hence, PressAcademia Procedia increases the value of your conference for your participants. 

PressAcademia Procedia provides an ISBN for each Conference Proceeding Book and a DOI number for each manuscript published in this book.

PressAcademia Procedia is currently indexed by DRJI, J-Gate, International Scientific Indexing, ISRA, Root Indexing, SOBIAD, Scope, EuroPub, Journal Factor Indexing and InfoBase Indexing. 

Please contact to procedia@pressacademia.org for your conference proceedings.