Forecasting, production planning, and control
Adeniran Adetayo Olaniyi; Kanyio Olufunto Adedotun; Owoeye Adelanke Samuel
Abstract
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 ...
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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.
Transportation
Adetayo Olaniyi Adeniran; Sidiq Okwudili Ben
Abstract
For planning process, this study examined the econometric model of domestic air travel in Nigeria vis-à-vis some selected economic variables. Furthermore, quantitative (inferential) statistics has used which relies on data obtained from relevant government institutions in Nigeria. Also the model ...
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For planning process, this study examined the econometric model of domestic air travel in Nigeria vis-à-vis some selected economic variables. Furthermore, quantitative (inferential) statistics has used which relies on data obtained from relevant government institutions in Nigeria. Also the model was estimated using Ordinary Least Square (OLS) regression. From the estimate; the predictor variables constant revealed that Domestic Passenger demand is a negative value which signifies that the predictors (economic variables) cannot give true estimate of the domestic airline forecast regardless of the positive regression coefficient for the predictors. On the other side, Domestic Passenger demand positively contributes to economic indicators. When validating the model estimate, test of significance revealed that there is no statistically significant relationship between the variables. Based on the insignificance, the model estimate cannot give a good forecast. Test for multicollinearity revealed that the coefficient of determination (R2) is 0.805 which is greater than 0.8. This signifies that there is a problem of multicollinearity. Based on this problem, the model estimate cannot give a good forecast. Goodness of fit test revealed that 80.5% of the dependent variable (Domestic Passenger demand) can be explained by the independent variables. The regression value signifies that the model can give a true forecast. Finally, based on the issues of validation, it is therefore concluded that the model cannot give a true forecast, hence economic indicators contributes little or no to air transport demand but rather air transport demand contributes significantly to economic indicators.