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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

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    File URL: http://eccsf.ulbsibiu.ro/RePEc/blg/journl/14208opreana.pdf
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    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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