Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8743
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dc.contributor.authorAdeniran, A O-
dc.contributor.authorKanyio, O A-
dc.contributor.authorOwoeye, Adelanke Samuel-
dc.date.accessioned2021-07-12T12:13:18Z-
dc.date.available2021-07-12T12:13:18Z-
dc.date.issued2018-08-19-
dc.identifier.citationAdeniran, A.O., Kanyio, O.A., & Owoeye, A.S. (2018) Forecasting Methods for Domestic Air Passenger Demand in Nigeria. J. Appl. Res. Ind. Eng. Vol. 5, No. 2 (2018) 146– 155.en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/8743-
dc.description.abstractTwo 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. Chronicle:en_US
dc.language.isoenen_US
dc.publisherJournal of Applied Research on Industrial Engineeringen_US
dc.relation.ispartofseries;Vol. 5, No. 2 (2018) 146– 155Vol.-
dc.subjectForecasting. Domestic Air Passenger Demand. Single Moving Average. Simple Exponential Smoothing.en_US
dc.titleForecasting Methods for Domestic Air Passenger Demand in Nigeriaen_US
dc.typeArticleen_US
Appears in Collections:Logistics and Transport Technology

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