DEVELOPMENT OF A REGRESSION MODEL TO FORECAST AIR TRAVEL DEMAND AT BAGHDAD INTERNATIONAL AIRPORT

Authors

  • Rawaa S. Albayati Highway and Transportation Engineering Department, Mustansiriyah University, Baghdad, Iraq Author
  • Raquim N. Zehawi Highway and Airport Engineering Department, Diyala University, Diyala, Iraq Author

DOI:

https://doi.org/10.31272/jeasd.27.2.10

Keywords:

Iraqi hub airport, socio-economic variables, SPSS software, statistical analysis

Abstract

The civil aviation demand forecast is a carefully formed perspective for airport system activities. Its main use is to predict possible needs for the planning and financial management processes for air carriers and civil aviation authorities. It is vital to conduct frequent analyses and projections of demand in order to meet their customers' expectations by balancing supply and demand and staying abreast of the ever-changing aviation industry. The purpose of this paper is to establish a mathematical relationship between the socioeconomic explanatory factors such as (population, Gross Domestic Product (GDP), consumption expenditure, rate of exchange, industry, imports, and exports) and activities (passenger movements and aircraft operations) at Baghdad International Airport in order to develop an econometric model. The required data had been collected for the past ten years. Eight models were developed depending on one or more of the explanatory variables using SPSS software, and they were then subjected to cross-comparison to see which model was more robust. According to the findings of the statistics, the gross domestic product, population size, and consumption expenditure are the most appropriate explanatory variables that have a significant impact on these activities, where they had a high R2 and F-statistics value equal to 90% and 73.442, respectively, for the model of air passengers and GDP and 90% and 48.737 for the model of flight operations and GDP.

References

Endrizalová, E. and Vladimír, N. (2014). “Demand for Air Travel”. MAD - Magazine of Aviation Development, Vol. 2, Issue, 12. DOI: 10.14311/MAD.2014.12.03.

Secilmis, N. and Koc, A. (2016). “Economic factors affecting aviation demand: Practice of EU countries”. Actual Probl Econ, Vol.179, Issue 5, pp. 412–20.

Štimac, I., Vidović, A., Mihetec, T. and Drljača, M. (2020). “Optimization of Airport Capacity Efficiency by Selecting Optimal Aircraft and Airline Business Model”. Sustainability, Vol. 12, p. 3988. DOI: 10.3390/su12103988.

Cook, A.J., Kluge, U., Paul, A. and Cristobal, S. (2017). “Factors influencing European passenger demand for air transport”. Air Transport Research Society World Conference. University of Antwerp Stadscampus, Belgium 05 - 08 Jul Air Transport Research Society.

Erraitab, E. (2016). “An Econometric Analysis Of Air Travel Demand: The Moroccan Case”. Eur Sci Journal, ESJ, Vol. 12, Issue 7, pp. 367-380. DOI: 10.19044/esj.2016.v12n7p367.

Tascón, D. and Olariaga, D.O. (2020). “Air traffic forecast and its impact on runway capacity”. A System Dynamics approach. Journal of Air Transport Management, Vol. 90. DOI:10.1016/j.jairtraman.2020.101946.

Olaniyi, A.A. and Adedotun, K.O. (2018). “Long Term Forecasting of International Air Travel Demand in Nigeria (2018-2028)”. Am Int J Multidiscip Sci Res., Vol. 1, Issue 2, pp. 16–24. DOI:10.46281/aijmsr.v1i2.184.

Ashford, N.J., Mumayiz, S. and Wright, P.H. (2011). “Airport Engineering: Planning, Design, and Development of 21st Century Airports”. 4th ed.,John Wiley & Sons, Inc..

Rodriguez, Y., Pineda, W., Olariaga D.O. (2020). “Air traffic forecast in post-liberalization context: A dynamic linear models approach”. Aviation, Vol. 24, Issue 1, pp. 10-19. DOI: 10.3846/aviation.2020.12273.

Shen, N. (2006). “Prediction of International Flight Operations”. M.Sc. Thesis, Civil and Environmental Engineering; Blacksburg, Virginia.

Zehawi, R.N., Hameed, A.H., Kareem, Y.N.A. (2016). “FORECASTING FUTURE DEMAND IN TWO OF THE BUSIEST US AIRPORTS USING SIMPLIFIED MODELS”. Diyala J Eng Sci., Vol. 9, Issue 4, pp. 93–103. DOI: 10.24237/djes.2016.09409

Suryani, E., Chou. S.Y. and Chen, C.H. (2010). “Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework”. Expert Systems With Applications, Vol. 37, Issue 3, pp. 2324-2339. DOI:10.1016/j.eswa.2009.07.041.

Abed, S.Y., Ba-Fail AO, Jasimuddin, S.M. (2001). “An econometric analysis of international air travel demand in Saudi Arabia”. Journal of Air Transport Management, Vol. 7, Issue 3, pp.143–148. DOI: 10.1016/S0969-6997(00)00043-0.

Abate, M. (2016). “Economic effects of air transport market liberalization in Africa”. Transportation Research Part A: Policy and Practice, Vol. 92, pp. 326–337. DOI: 10.1016/j.tra.2016.06.014.

Solvoll, G., Mathisen, T.A. and Welde, M. (2020). “Forecasting air traffic demand for major infrastructure changes”. Research in Transportation Economics, Vol. 82. 100873. DOI: 10.1016/j.retrec.2020.100873.

Guo, X., Grushka-Cockayne, Y. and De Reyck, B. (2018). “Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning”. SSRN Electron Journal. DOI: 10.2139/ssrn.3245609.

Danesi, A., Mantecchini, L. and Paganelli, F. (2017). “Long-term and short-term forecasting techniques for regional airport planning”. ARPN Journal of Engineering and Applied Sciences, Vol. 12, Issue 3, pp. 739-745.

Chudy-Laskowska, K. (2017). “Seasonal Forecasting for Air Passenger Trafic”. 4th Int Multidiscip Sci Conf Soc Sci Arts SGEM, Mod Sci. Bulgaria. Vol. 17, Issue 4, pp. 681-692. DOI: 10.5593/sgemsocial2017/14/S04.089

Albayrak, M.B.K., Özcan, I.Ç., Can, R. and Dobruszkesd, F. (2020). “The determinants of air passenger traffic at Turkish airports”. Journal of Air Transport Management, Elsevier, Vol. 86. DOI: 10.1016/j.jairtraman.2020.101818.

De Neufville, R., Odoni, A.R., Belobaba, P. and Reynolds, T. (2013). “Airport Systems: Planning, Design, and Management”. 2nd ed., McGraw-Hill.

Morgan, G.A., Barrett, K.C., Leech N.L. and Gloeckner, G.W. (2011). “IBM SPSS for introductory statistics: Use and interpretation”. 4th ed., Taylor & Francis Group.

Gelman, A., Goodrich, B., Gabry, J. and Vehtari, A. (2019). “R-squared for Bayesian Regression Models”. The American Statistician, Vol. 73, Issue 3, pp. 307-309. DOI:/10.1080/00031305.2018.1549100

Sedgwick, P. (2014). “Understanding P values”. BMJ.11;349:g4550. DOI: 10.1136/bmj.g4550. PMID: 25015369.

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Published

2023-03-01

Issue

Vol. 27 No. 2 (2023): Journal of Engineering and Sustainable Development

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Articles

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Copyright (c) 2023 Rawaa S. Albayati, Raquim N. Zehawi

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How to Cite

DEVELOPMENT OF A REGRESSION MODEL TO FORECAST AIR TRAVEL DEMAND AT BAGHDAD INTERNATIONAL AIRPORT. (2023). Journal of Engineering and Sustainable Development, 27(2), 272-281. https://doi.org/10.31272/jeasd.27.2.10

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