Araştırma Makalesi
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Havayolu Bilet Fiyatı, Talep ve İş Modeli İlişkisi: Dünya Geneli Analizi

Yıl 2023, Cilt: 15 Sayı: 3, 211 - 218, 29.09.2023

Selçuk Kayhan Kasım Kiracı Mehmet Yaşar

https://doi.org/10.52791/aksarayiibd.1234849

Öz

Bu çalışmanın amacı, havayollarının yolcu başına ortalama bilet fiyatı ile yolcu sayısı arasındaki ilişkiyi ortaya koymaktır. Çalışmada 2013-2022 dönemi için havayollarının yolcu başına ortalama bilet fiyatı ve yolcu sayısı verileri panel veri analizi ile incelenmiştir. Tüm havayolları örneğinde bir panel regresyon modeli uygulanmıştır. Bu nedenle, analiz tüm havayolları örnekleminde 4194 gözlem kullanarak gerçekleştirilmiştir. Ayrıca çalışmada havayolları iş modellerine göre farklı gruplara ayrılmıştır. Bu kapsamda havayolları Geleneksel taşıyıcılar, Düşük maliyetli taşıyıcılar, Charter taşıyıcılar ve Bölgesel taşıyıcılar olarak 4 farklı grupta sınıflandırılmıştır. Çalışmanın bulguları, yolcu başına ortalama fiyattaki değişime karşı yolcu sayısında bir tepki olduğunu göstermektedir. Analiz sonuçları, bilet fiyatı ile havayolu talebi arasında anlamlı ve negatif bir ilişki olduğunu ancak iş modeline göre esneklik farklılıkları olduğunu ortaya koymuştur.

Anahtar Kelimeler

Havayolu Talebi Bilet Fiyatı Panel Veri İş Modeli

Kaynakça

  • Abdella, J. A., Zaki, N., & Shuaib, K. (2018, November). Automatic detection of airline ticket price and demand: A review. In 2018 International Conference on Innovations in Information Technology (IIT) (pp. 169-174). IEEE.
  • Baltagi, B. H. (2005). Econometric Analysis of Panel Data (Cilt 3th Ed.). England: Chichester: John Wiley& Sons.
  • Baltagi B.H. (2021) Introduction, In Econometric Analysis of Panel Data, Springer, Cham. V. 4. No. 1, pp. 1–14.
  • Beyzatlar, M. A., Karacal, M., & Yetkiner, H. (2014). Granger-causality between transportation and GDP: A panel data approach. Transportation Research Part A: Policy and Practice, 63, 43-55.
  • Bilotkach, V. (2015). Are airports engines of economic development? A dynamic panel data approach. Urban Studies, 52(9), 1577-1593.
  • Bilotkach, V., & Lakew, P. A. (2014). On sources of market power in the airline industry: Panel data evidence from the US airports. Transportation Research Part A: Policy and Practice, 59, 288-305.
  • Brons, M., Pels, E., Nijkamp, P., & Rietveld, P. (2002). Price elasticities of demand for passenger air travel: a meta-analysis. Journal of Air Transport Management, 8(3), 165-175.
  • Burger, B., & Fuchs, M. (2005). Dynamic pricing—A future airline business model. Journal of Revenue and Pricing Management, 4(1), 39-53.
  • Chen, X., Mao, S., Lv, S., & Fang, Z. (2022). A study on the non-linear impact of digital technology innovation on carbon emissions in the transportation industry. International Journal of Environmental Research and Public Health, 19(19), 12432.
  • Chen, Z. (2017). Impacts of high-speed rail on domestic air transportation in China. Journal of Transport Geography, 62, 184-196.
  • Chrisnawan, L., Onibala, M., Octora, Y., Setiawan, E. B., & Anthony, D. (2019). The Effect of Price And Perceived Quality on Ticket Purchase Intention at Lion Air Airline. Advances in Transportation and Logistics Research, 2, 187-195.
  • Doganis, R. (2005). Flying off course: The economics of international airlines. Routledge.
  • Duran, A., & Gungor, M. S. (2017). Aviation fuel hedging and firm value analysis using dynamic panel data methodology: Evidence from the US major passenger airlines. International Journal of Business and Economic Sciences Applied Research (IJBESAR), 10(3), 67-72.
  • Etzioni, O., Tuchinda, R., Knoblock, C. A., & Yates, A. (2003, August). To buy or not to buy: mining airfare data to minimize ticket purchase price. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 119-128).
  • Gao, J., Le, M., & Fang, Y. (2022). Dynamic air ticket pricing using reinforcement learning method. RAIRO-Operations Research, 56(4), 2475-2493.
  • Greenee, William. H. (2003), Econometric Analysis, 5th Ed., New York: Prentice Hall. Gujarati, D. N. (2003). Basic Econometrics, 4. Baskı, McGraw-Hill Comp., New York.
  • Hill, T. D., Davis, A. P., Roos, J. M., & French, M. T. (2020). Limitations of fixed-effects models for panel data. Sociological Perspectives, 63(3), 357-369.
  • Hsiao, C. (1985). Benefits and limitations of panel data. Econometric Reviews, 4(1), 121-174.
  • Hsiao, C. (2003), Analysis of Panel Data, Second Edition, Cambridge University Press.
  • Hsiao, C. (2007). Panel data analysis—advantages and challenges. Test, 16(1), 1-22.
  • Hsiao, C. (2022). Analysis of panel data (No. 64). Cambridge University Press. Jallat, F., & Ancarani, F. (2008). Yield management, dynamic pricing and CRM in telecommunications. Journal of Services Marketing, 22(6), 465-478
  • Jin, L., Mott, J., Yang, C., & Lu, C. (2022). A panel study of outsourced maintenance ımpact on major u.s. passenger airlines' profitability (1995-2019). Journal of Aviation/Aerospace Education & Research, 31(2). https://doi.org/10.15394/jaaer.2022.1917
  • Kim, J. Y., Natter, M., & Spann, M. (2009). Pay what you want: A new participative pricing mechanism. Journal of Marketing, 73(1), 44-58.
  • Kiracı, K. (2021). Covıd-19, financial risk and the airline industry. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 8(3), 1557-1581.
  • Kiracı, K. (2021). Determinants of dividend payout policies: evidence from airline industry. Journal of Aviation, 5(2), 210-218.
  • Li, H., Li, J., Zhao, X., & Kuang, X. (2022). The morphological structure and influence factors analysis of China's domestic civil aviation freight transport network. Transport Policy, 125, 207-217.
  • Li, Y., Yang, B., & Cui, Q. (2019). The effects of high-speed rail on air passenger transport in China. Applied Economics Letters, 26(9), 745-749.
  • Mathur, S. (2020). Pricing of airline tickets on India's busiest aviation route (New Delhi-Mumbai). International Journal of Indian Culture and Business Management, 20(1), 93-108.
  • Martínez, M. E. A., Navarro, J. L. A., & Trinquecoste, J. F. (2017). The effect of destination type and travel period on the behavior of the price of airline tickets. Research in Transportation Economics, 62, 37-43.
  • McConnachie, D., Wollersheim, C., & Hansman, R. J. (2013). The impact of fuel price on airline fuel efficiency and operations. In 2013 Aviation Technology, Integration, and Operations Conference (p. 4291).
  • Medina-Muñoz, D. R., Medina-Muñoz, R. D., & Suárez-Cabrera, M. Á. (2018). Determining important attributes for assessing the attractiveness of airlines. Journal of Air Transport Management, 70, 45-56.
  • Monroe, K.B. (2003), Pricing. Making Profitable Decisions, McGraw-Hill, New York, NY.
  • Moschovou, T. P., & Giannopoulos, A. G. (2021). Road freight transportation in a period of economic instability: A panel data study in four EU Mediterranean countries. Research in Transportation Business & Management, 41, 100622.
  • Narangajavana, Y., Garrigos-Simon, F. J., García, J. S., & Forgas-Coll, S. (2014). Prices, prices and prices: A study in the airline sector. Tourism Management, 41, 28-42.
  • Rey, B., Myro, R. L., & Galera, A. (2011). Effect of low-cost airlines on tourism in Spain. A dynamic panel data model. Journal of Air Transport Management, 17(3), 163-167.
  • Shen, C., & Yahya, Y. (2021). The impact of service quality and price on passengers' loyalty towards low-cost airlines: The Southeast Asia perspective. Journal of Air Transport Management, 91, 101966.
  • Surovitskikh, S. (2012). The relationship between South African aviation policy in Africa and air passenger traffic flows. 1st International Aviation Management Conference, IAMC – 2012, Dubai, UAE, 18 – 20 November 2012.
  • Szabo, S., Mako, S., Tobisova, A., Hanak, P., & Pilat, M. (2018). Effect of the load factor on the ticket price. Transport Problems, 13(3), 41-49.
  • Takebayashi, M., & Ishikura, T. (2013). Impact of low cost carriers and multiple airport system. Asian Transport Studies, 2(3), 309-322.
  • Tellis, G. J. (1986). Beyond the many faces of price: an integration of pricing strategies. Journal of Marketing, 50(4), 146-160.
  • Thakare, V. P., Murraya, A. S., Gawade, R. B., Sawarkar, M. M., Shende, T. K., & Badole, U. K. (2022). Flight ticket price predictor using python. Advancement and Research in Instrumentation Engineering, 5(1).
  • Tsui,K.W.H.(2017). Does a low-cost carrier lead the domestic tourism demand and growth of New Zealand? Tourism Management, 60, 390–403. https://doi.org/10.1016/j.tourman. 2016.10.013
  • Ventura, R. V., Fernandes, E., Fernandes, V. A., Cabo, M., Fadel, A. C., & Caixeta, R. (2022). Consumer behaviour analysis based on income and price elasticities: The case of the air transportation in Brazil. Case Studies on Transport Policy, 10(2), 1262-1272.
  • Ventura, R. V., Cabo, M., Caixeta, R., Fernandes, E., & Aprigliano Fernandes, V. (2020). Air transportation income and price elasticities in remote areas: The case of the Brazilian Amazon region. Sustainability, 12(15), 6039.
  • Yaşar, M. (2019). Düşük maliyetli havayolu işletmelerinde bilet fiyatlarına etki eden rekabetçi unsurların değerlendirilmesi. İşletme Bilimi Dergisi, 7(3), 595-610.
  • Whalen, W. T. (2007). A panel data analysis of code-sharing, antitrust immunity, and open skies treaties in international aviation markets. Review of Industrial Organization, 30(1), 39-61.

Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis

Yıl 2023, Cilt: 15 Sayı: 3, 211 - 218, 29.09.2023

Selçuk Kayhan Kasım Kiracı Mehmet Yaşar

https://doi.org/10.52791/aksarayiibd.1234849

Öz

The aim of this study is to reveal the relationship between the average price per passenger and the number of passenger of airlines. In the study, we analyzed the average price per passenger and number of passenger data of airlines for the period 2013-2022 using panel data analysis. We applied a panel regression model in the sample of all airlines. Therefore, we conducted the analysis using 4194 observations in the sample of all airlines. In addition, in the study, we divided the airlines into different groups according to their business model. In this context, we have classified airlines as Network carriers, Low-cost carriers, Charter carriers and Regional carriers. The findings of the study show that there is a reaction in the number of passengers against the change in the average price per passenger. The results of the analysis revealed that there is a significant and negative relationship between ticket price and airline demand but there are elasticity differences according to the business model.

Anahtar Kelimeler

Airline Demand Ticket Price Panel Data Business Model

Kaynakça

  • Abdella, J. A., Zaki, N., & Shuaib, K. (2018, November). Automatic detection of airline ticket price and demand: A review. In 2018 International Conference on Innovations in Information Technology (IIT) (pp. 169-174). IEEE.
  • Baltagi, B. H. (2005). Econometric Analysis of Panel Data (Cilt 3th Ed.). England: Chichester: John Wiley& Sons.
  • Baltagi B.H. (2021) Introduction, In Econometric Analysis of Panel Data, Springer, Cham. V. 4. No. 1, pp. 1–14.
  • Beyzatlar, M. A., Karacal, M., & Yetkiner, H. (2014). Granger-causality between transportation and GDP: A panel data approach. Transportation Research Part A: Policy and Practice, 63, 43-55.
  • Bilotkach, V. (2015). Are airports engines of economic development? A dynamic panel data approach. Urban Studies, 52(9), 1577-1593.
  • Bilotkach, V., & Lakew, P. A. (2014). On sources of market power in the airline industry: Panel data evidence from the US airports. Transportation Research Part A: Policy and Practice, 59, 288-305.
  • Brons, M., Pels, E., Nijkamp, P., & Rietveld, P. (2002). Price elasticities of demand for passenger air travel: a meta-analysis. Journal of Air Transport Management, 8(3), 165-175.
  • Burger, B., & Fuchs, M. (2005). Dynamic pricing—A future airline business model. Journal of Revenue and Pricing Management, 4(1), 39-53.
  • Chen, X., Mao, S., Lv, S., & Fang, Z. (2022). A study on the non-linear impact of digital technology innovation on carbon emissions in the transportation industry. International Journal of Environmental Research and Public Health, 19(19), 12432.
  • Chen, Z. (2017). Impacts of high-speed rail on domestic air transportation in China. Journal of Transport Geography, 62, 184-196.
  • Chrisnawan, L., Onibala, M., Octora, Y., Setiawan, E. B., & Anthony, D. (2019). The Effect of Price And Perceived Quality on Ticket Purchase Intention at Lion Air Airline. Advances in Transportation and Logistics Research, 2, 187-195.
  • Doganis, R. (2005). Flying off course: The economics of international airlines. Routledge.
  • Duran, A., & Gungor, M. S. (2017). Aviation fuel hedging and firm value analysis using dynamic panel data methodology: Evidence from the US major passenger airlines. International Journal of Business and Economic Sciences Applied Research (IJBESAR), 10(3), 67-72.
  • Etzioni, O., Tuchinda, R., Knoblock, C. A., & Yates, A. (2003, August). To buy or not to buy: mining airfare data to minimize ticket purchase price. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 119-128).
  • Gao, J., Le, M., & Fang, Y. (2022). Dynamic air ticket pricing using reinforcement learning method. RAIRO-Operations Research, 56(4), 2475-2493.
  • Greenee, William. H. (2003), Econometric Analysis, 5th Ed., New York: Prentice Hall. Gujarati, D. N. (2003). Basic Econometrics, 4. Baskı, McGraw-Hill Comp., New York.
  • Hill, T. D., Davis, A. P., Roos, J. M., & French, M. T. (2020). Limitations of fixed-effects models for panel data. Sociological Perspectives, 63(3), 357-369.
  • Hsiao, C. (1985). Benefits and limitations of panel data. Econometric Reviews, 4(1), 121-174.
  • Hsiao, C. (2003), Analysis of Panel Data, Second Edition, Cambridge University Press.
  • Hsiao, C. (2007). Panel data analysis—advantages and challenges. Test, 16(1), 1-22.
  • Hsiao, C. (2022). Analysis of panel data (No. 64). Cambridge University Press. Jallat, F., & Ancarani, F. (2008). Yield management, dynamic pricing and CRM in telecommunications. Journal of Services Marketing, 22(6), 465-478
  • Jin, L., Mott, J., Yang, C., & Lu, C. (2022). A panel study of outsourced maintenance ımpact on major u.s. passenger airlines' profitability (1995-2019). Journal of Aviation/Aerospace Education & Research, 31(2). https://doi.org/10.15394/jaaer.2022.1917
  • Kim, J. Y., Natter, M., & Spann, M. (2009). Pay what you want: A new participative pricing mechanism. Journal of Marketing, 73(1), 44-58.
  • Kiracı, K. (2021). Covıd-19, financial risk and the airline industry. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 8(3), 1557-1581.
  • Kiracı, K. (2021). Determinants of dividend payout policies: evidence from airline industry. Journal of Aviation, 5(2), 210-218.
  • Li, H., Li, J., Zhao, X., & Kuang, X. (2022). The morphological structure and influence factors analysis of China's domestic civil aviation freight transport network. Transport Policy, 125, 207-217.
  • Li, Y., Yang, B., & Cui, Q. (2019). The effects of high-speed rail on air passenger transport in China. Applied Economics Letters, 26(9), 745-749.
  • Mathur, S. (2020). Pricing of airline tickets on India's busiest aviation route (New Delhi-Mumbai). International Journal of Indian Culture and Business Management, 20(1), 93-108.
  • Martínez, M. E. A., Navarro, J. L. A., & Trinquecoste, J. F. (2017). The effect of destination type and travel period on the behavior of the price of airline tickets. Research in Transportation Economics, 62, 37-43.
  • McConnachie, D., Wollersheim, C., & Hansman, R. J. (2013). The impact of fuel price on airline fuel efficiency and operations. In 2013 Aviation Technology, Integration, and Operations Conference (p. 4291).
  • Medina-Muñoz, D. R., Medina-Muñoz, R. D., & Suárez-Cabrera, M. Á. (2018). Determining important attributes for assessing the attractiveness of airlines. Journal of Air Transport Management, 70, 45-56.
  • Monroe, K.B. (2003), Pricing. Making Profitable Decisions, McGraw-Hill, New York, NY.
  • Moschovou, T. P., & Giannopoulos, A. G. (2021). Road freight transportation in a period of economic instability: A panel data study in four EU Mediterranean countries. Research in Transportation Business & Management, 41, 100622.
  • Narangajavana, Y., Garrigos-Simon, F. J., García, J. S., & Forgas-Coll, S. (2014). Prices, prices and prices: A study in the airline sector. Tourism Management, 41, 28-42.
  • Rey, B., Myro, R. L., & Galera, A. (2011). Effect of low-cost airlines on tourism in Spain. A dynamic panel data model. Journal of Air Transport Management, 17(3), 163-167.
  • Shen, C., & Yahya, Y. (2021). The impact of service quality and price on passengers' loyalty towards low-cost airlines: The Southeast Asia perspective. Journal of Air Transport Management, 91, 101966.
  • Surovitskikh, S. (2012). The relationship between South African aviation policy in Africa and air passenger traffic flows. 1st International Aviation Management Conference, IAMC – 2012, Dubai, UAE, 18 – 20 November 2012.
  • Szabo, S., Mako, S., Tobisova, A., Hanak, P., & Pilat, M. (2018). Effect of the load factor on the ticket price. Transport Problems, 13(3), 41-49.
  • Takebayashi, M., & Ishikura, T. (2013). Impact of low cost carriers and multiple airport system. Asian Transport Studies, 2(3), 309-322.
  • Tellis, G. J. (1986). Beyond the many faces of price: an integration of pricing strategies. Journal of Marketing, 50(4), 146-160.
  • Thakare, V. P., Murraya, A. S., Gawade, R. B., Sawarkar, M. M., Shende, T. K., & Badole, U. K. (2022). Flight ticket price predictor using python. Advancement and Research in Instrumentation Engineering, 5(1).
  • Tsui,K.W.H.(2017). Does a low-cost carrier lead the domestic tourism demand and growth of New Zealand? Tourism Management, 60, 390–403. https://doi.org/10.1016/j.tourman. 2016.10.013
  • Ventura, R. V., Fernandes, E., Fernandes, V. A., Cabo, M., Fadel, A. C., & Caixeta, R. (2022). Consumer behaviour analysis based on income and price elasticities: The case of the air transportation in Brazil. Case Studies on Transport Policy, 10(2), 1262-1272.
  • Ventura, R. V., Cabo, M., Caixeta, R., Fernandes, E., & Aprigliano Fernandes, V. (2020). Air transportation income and price elasticities in remote areas: The case of the Brazilian Amazon region. Sustainability, 12(15), 6039.
  • Yaşar, M. (2019). Düşük maliyetli havayolu işletmelerinde bilet fiyatlarına etki eden rekabetçi unsurların değerlendirilmesi. İşletme Bilimi Dergisi, 7(3), 595-610.
  • Whalen, W. T. (2007). A panel data analysis of code-sharing, antitrust immunity, and open skies treaties in international aviation markets. Review of Industrial Organization, 30(1), 39-61.
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Araştırma Makalesi
Yazarlar

Selçuk Kayhan 0000-0001-9291-4528

Kasım Kiracı 0000-0002-2061-171X

Mehmet Yaşar 0000-0001-7237-4069

Yayımlanma Tarihi 29 Eylül 2023
Yayımlandığı Sayı Yıl 2023Cilt: 15 Sayı: 3

Kaynak Göster

APA Kayhan, S., Kiracı, K., & Yaşar, M. (2023). Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis. Aksaray Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 15(3), 211-218. https://doi.org/10.52791/aksarayiibd.1234849
AMA Kayhan S, Kiracı K, Yaşar M. Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis. ASÜ İİBF Dergisi. Eylül 2023;15(3):211-218. doi:10.52791/aksarayiibd.1234849
Chicago Kayhan, Selçuk, Kasım Kiracı, ve Mehmet Yaşar. “Relationship Between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis”. Aksaray Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi 15, sy. 3 (Eylül 2023): 211-18. https://doi.org/10.52791/aksarayiibd.1234849.
EndNote Kayhan S, Kiracı K, Yaşar M (01 Eylül 2023) Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 15 3 211–218.
IEEE S. Kayhan, K. Kiracı, ve M. Yaşar, “Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis”, ASÜ İİBF Dergisi, c. 15, sy. 3, ss. 211–218, 2023, doi: 10.52791/aksarayiibd.1234849.
ISNAD Kayhan, Selçuk vd. “Relationship Between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis”. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 15/3 (Eylül 2023), 211-218. https://doi.org/10.52791/aksarayiibd.1234849.
JAMA Kayhan S, Kiracı K, Yaşar M. Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis. ASÜ İİBF Dergisi. 2023;15:211–218.
MLA Kayhan, Selçuk vd. “Relationship Between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis”. Aksaray Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, c. 15, sy. 3, 2023, ss. 211-8, doi:10.52791/aksarayiibd.1234849.
Vancouver Kayhan S, Kiracı K, Yaşar M. Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis. ASÜ İİBF Dergisi. 2023;15(3):211-8.
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