A comparative analysis of the application of seasonal ARIMA and exponential smoothing methods in short run Forecasting Tourist Arrivals in Tanzania
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Date
2017
Authors
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Publisher
European Open Science Publishing
Abstract
This paper compared the performance of two forecasting models (Seasonal ARIMA and
Exponential smoothing) in an attempt to identify the model that fits properly in forecasting
tourist arrivals in a dynamic tourism industry in Tanzania. A two-staged approach to
forecasting was carried out using monthly data for the period of 2000 to 2009. The models
were assessed in similarly structured setting at the outset, and then best models identified at
this level were compared in a differently structured setting. The results show that Seasonal
ARIMA(4,1,4)(3,1,4)12 and Holt-Winters multiplicative smoothing method are effective in
forecasting tourist arrivals in Tanzania in a similarly structured setting. However, when the
two models were compared under different structures, the performance of Holt-Winters
multiplicative smoothing method outstripped that of Seasonal ARIMA(4,1,4)(3,1,4)12. This
suggests that Holt-Winters multiplicative smoothing method with Alpha (0.01), Delta (0.11)
and Gamma (0.11) is more effective in forecasting tourist arrivals in Tanzania in the short run and it can be used to aid planning processes in the tourism industry. Moreover, the seasonality pattern that characterizes tourist arrivals in Tanzania highlights the need to promote more of local tourism so as to lessen the negative impacts associated with it.
Description
Full texte article. Also available at https://core.ac.uk/download/pdf/234627808.pdf
Keywords
Seasonal ARIMA, Exponential smoothing, Tourist, Holt-winters, Forecasting
Citation
Lwesya, F., & Kibambila, V. (2017). A Comparative Analysis of the Application of Seasonal ARIMA and Exponential Smoothing methods in short run Forecasting Tourist Arrivals in Tanzania. European Journal of Business and Management, 9(10), 56.