IDEAS home Printed from https://ideas.repec.org/a/blg/journl/v14y2019i2p105-114.html
   My bibliography  Save this article

Forecasting Passenger Traffic For A Regional Airport

Author

Listed:
  • OPREANA ALIN

    (Lucian Blaga University of Sibiu, Romania)

  • ȚICHINDELEAN MIHAI

    (Lucian Blaga University of Sibiu, Romania)

  • MIHAIU DIANA MARIETA

    (Lucian Blaga University of Sibiu, Romania)

  • TILEAGĂ COSMIN

    (Lucian Blaga University of Sibiu, Romania)

Abstract

The purpose of the present research is estimating the potential traffic for SIA (Sibiu International Airport, SBZ) for the year 2017. Predicting as accurate as possible the passenger traffic for a certain airport is an aspect of major importance for both the airport management and the airline companies. The theoretical quality of the forecasting models for air traffic of passengers is fundamental for obtaining the most accurate predictions. In this regard, a two-step process was used in developing the traffic forecasting model: (1) Identifying the proper regression model for traffic estimation based on the number of aircraft departures, and (2) Forecasting the number of aircraft departures for the current routes operated SIA. The predicted total passenger traffic overestimates the actual total traffic with only 2.4% and the actual total traffic without the transit traffic with only 1.42%.

Suggested Citation

  • Opreana Alin & Țichindelean Mihai & Mihaiu Diana Marieta & Tileagă Cosmin, 2019. "Forecasting Passenger Traffic For A Regional Airport," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(2), pages 105-114, August.
  • Handle: RePEc:blg:journl:v:14:y:2019:i:2:p:105-114
    as

    Download full text from publisher

    File URL: http://eccsf.ulbsibiu.ro/RePEc/blg/journl/14208opreana.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Parthasarathi, Pavithra & Levinson, David, 2010. "Post-construction evaluation of traffic forecast accuracy," Transport Policy, Elsevier, vol. 17(6), pages 428-443, November.
    2. Profillidis, V.A, 2000. "Econometric and fuzzy models for the forecast of demand in the airport of Rhodes," Journal of Air Transport Management, Elsevier, vol. 6(2), pages 95-100.
    3. Ya-Ling Huang & Chin-Tsai Lin, 2011. "Developing an interval forecasting method to predict undulated demand," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 513-524, April.
    4. Hess, Stephane & Polak, John W., 2005. "Mixed logit modelling of airport choice in multi-airport regions," Journal of Air Transport Management, Elsevier, vol. 11(2), pages 59-68.
    5. Clewlow, Regina R. & Sussman, Joseph M. & Balakrishnan, Hamsa, 2014. "The impact of high-speed rail and low-cost carriers on European air passenger traffic," Transport Policy, Elsevier, vol. 33(C), pages 136-143.
    6. Tsung-Yu Chou & Gin-Shuh Liang & Tzeu-Chen Han, 2013. "Application of fuzzy regression on air cargo volume forecast," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 897-908, February.
    7. Wei, Wenbin & Hansen, Mark, 2006. "An aggregate demand model for air passenger traffic in the hub-and-spoke network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 841-851, December.
    8. Elton Fernandes & Ricardo Rodrigues Pacheco, 2010. "The causal relationship between GDP and domestic air passenger traffic in Brazil," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(7), pages 569-581, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    2. Sismanidou, Athina & Tarradellas, Joan & Bel, Germà & Fageda, Xavier, 2013. "Estimating potential long-haul air passenger traffic in national networks containing two or more dominant cities," Journal of Transport Geography, Elsevier, vol. 26(C), pages 108-116.
    3. Kağan Albayrak, Muhammed Bilge & Özcan, İsmail Çağrı & Can, Raif & Dobruszkes, Frédéric, 2020. "The determinants of air passenger traffic at Turkish airports," Journal of Air Transport Management, Elsevier, vol. 86(C).
    4. Hsiao, Chieh-Yu & Hansen, Mark, 2011. "A passenger demand model for air transportation in a hub-and-spoke network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1112-1125.
    5. Suau-Sanchez, Pere & Voltes-Dorta, Augusto & Rodríguez-Déniz, Héctor, 2016. "Measuring the potential for self-connectivity in global air transport markets: Implications for airports and airlines," Journal of Transport Geography, Elsevier, vol. 57(C), pages 70-82.
    6. Wang, Yu-Chen & Wong, Jinn-Tsai, 2019. "Exploring air network formation and development with a two-part model," Journal of Transport Geography, Elsevier, vol. 75(C), pages 122-131.
    7. Rayaprolu, Hema & Levinson, David, 2024. "Co-evolution of public transport access and ridership," Journal of Transport Geography, Elsevier, vol. 116(C).
    8. Meng, Xuechen & Lin, Shanlang & Zhu, Xiaochuan, 2018. "The resource redistribution effect of high-speed rail stations on the economic growth of neighbouring regions: Evidence from China," Transport Policy, Elsevier, vol. 68(C), pages 178-191.
    9. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    10. Beria, Paolo & Laurino, Antonio, 2016. "Determinants of daily fluctuations in air passenger volumes. The effect of events and holidays on Milan Malpensa airport," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 73-84.
    11. Fageda, Xavier, 2014. "What hurts the dominant airlines at hub airports?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 177-189.
    12. A. Azadeh & M. Saberi & A. Gitiforouz, 2013. "An integrated fuzzy mathematical model and principal component analysis algorithm for forecasting uncertain trends of electricity consumption," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2163-2176, June.
    13. Xia, Wenyi & Jiang, Changmin & Wang, Kun & Zhang, Anming, 2019. "Air-rail revenue sharing in a multi-airport system: Effects on traffic and social welfare," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 304-319.
    14. Maria Börjesson & Jonas Eliasson & Mattias Lundberg, 2014. "Is CBA Ranking of Transport Investments Robust?," Journal of Transport Economics and Policy, University of Bath, vol. 48(2), pages 189-204, May.
    15. Lu, Xiao-Yun & Gosling, Geoffrey D. & Shladover, Steven E. & Xiong, Jing & Ceder, Avi, 2006. "Development of a Modeling Framework for Analyzing Improvements in Intermodal Connectivity at California Airports," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt586755r9, Institute of Transportation Studies, UC Berkeley.
    16. Zhang, Rui & Johnson, Daniel & Zhao, Weiming & Nash, Chris, 2019. "Competition of airline and high-speed rail in terms of price and frequency: Empirical study from China," Transport Policy, Elsevier, vol. 78(C), pages 8-18.
    17. Bergantino, Angela Stefania & Madio, Leonardo, 2020. "Intermodal competition and substitution. HSR versus air transport: Understanding the socio-economic determinants of modal choice," Research in Transportation Economics, Elsevier, vol. 79(C).
    18. Tsunoda, Yushi, 2018. "Transportation policy for high-speed rail competing with airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 350-360.
    19. Walker, Joan L. & Chatman, Daniel & Daziano, Ricardo & Erhardt, Gregory & Gao, Song & Mahmassani, Hani & Ory, David & Sall, Elizabeth & Bhat, Chandra & Chim, Nicholas & Daniels, Clint & Gardner, Brian, 2019. "Advancing the Science of Travel Demand Forecasting," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0v1906ts, Institute of Transportation Studies, UC Berkeley.
    20. Carson, Richard T. & Cenesizoglu, Tolga & Parker, Roger, 2011. "Forecasting (aggregate) demand for US commercial air travel," International Journal of Forecasting, Elsevier, vol. 27(3), pages 923-941.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:blg:journl:v:14:y:2019:i:2:p:105-114. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mihaela Herciu (email available below). General contact details of provider: https://edirc.repec.org/data/feulbro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.