Document Type : Research Paper


1 Department of Transport Management Technology, Federal University of Technology, Akure, Nigeria.

2 Department of Transport Management Technology, Federal University of Technology, Minna, Nigeria.


Two years single moving average and simple exponential smoothing with smoothing constant of 0.9 were applied to forecast the 2018 demand for domestic air passenger in Nigeria. Also, the two methods of forecasting were evaluated and compared with Mean Squared Deviations (MSD) to determine which method gives the lowest deviation as it will produce best forecast for the year 2018 domestic air passenger demand in Nigeria. The study relied on data of domestic air passenger demand between the periods of the year 2010 to the year 2017. It was revealed that the MSD of two yearly single moving average gave the best year 2018 forecast as it has a lower MSD when compared to the MSD of simple exponential smoothing with the smoothing constant of 0.9. This study is useful in the planning process of an airport, airline, and other stakeholders involved in Nigeria’s air transportation. It will help to prevent problems of having excess air transport demand over air transport supply or having excess air transport supply over demand.


Main Subjects

[1]     Wensveen, J. (2018). Air transportation: A management perspective. Routledge.
[2]     Adeniran, A. O. & Adeniran, A. A. (2017). Econometric modeling of passenger demand for international air transport in nigeria airports. American journal of traffic and transportation engineering, 2(4), 39- 44.
[3]     Adeniran, A. O., Adekunle, E. A., & Oyedele, O. J. (2017). Establishing the concept of research hypothesis through the relationship between demand in Nigeria international air passenger traffic and economic variables. International journal of economic behavior and organization, 5(5), 105-113.
[4]     Adeniran, A. O. & Ben, S. O. (2017). Understanding econometric modeling: domestic air travel in nigeria and implication for planning process. Journal of applied research in industrial engineering, 4(4). 240–251.
[5]     Lucey, T. (2007). Quantitative techniques. Sixth Edition. Book Power/ELST.
[6]     Tinseth, R. (2014). Current market outlook. Retrieved from
[7]     Adeniran, A. O., & Stephens, M. S. (2018). The Dynamics for Evaluating Forecasting Methods for International Air Passenger Demand in Nigeria. Journal of tourism & hospitality, 7(4), 1-11. doi: 10.4172/2167-0269.1000366.
[8]     Poore, J. W. (1993). Forecasting the demand for air transportation services. Journal of transportation engineering19(5), 22-34.
[9]     Cacatto, C., Belfiore, P., & Vieira, J. G. V. (2012). Forecasting practices in Brazilian food industry. Journal of logistics management1(4), 24-36.
[10] Sahu, P. K., & Kumar, R. (2014). The Evaluation of Forecasting Methods for Sales of Sterilized Flavoured Milk in Chhattisgarh. International journal of engineering trends and technology (IJETT)8(2), 98-104.
[11] Ryu, K., & Sanchez, A. (2003). The evaluation of forecasting methods at an institutional foodservice dining facility. The journal of hospitality financial management11(1), 27-45.
[12] Perroux, F. (1950). Economic space: theory and applications. The quarterly journal of economics64(1), 89-104.
[13] Abed, S. Y., Ba-Fail, A. O., & Jasimuddin, S. M. (2001). An econometric analysis of international air travel demand in Saudi Arabia. Journal of air transport management7(3), 143-148.
[14] Afolayan, O. S., Asaju, A. J., & Malik, N. A. (2012). Variation in spatial trend of passengers and aircrafts movement in Nigerian international airports. International journal of humanities and social science2(10), 126-133.
[15] Federal Airports Authority of Nigeria. (2017). Retrieved from
[16] Nigeria Bureau of Statistics. (2018). Retrieved from
[17] Kazda, A., & Caves, R. E. (Eds.). (2010). Airport design and operation. Emerald Group Publishing Limited.