Abstract
Tourism is one of the major contributors to foreign exchange earnings to Zambia and world economy. Annual International tourist arrivals in Zambia from 1995 to 2014 are considered in this paper. In this study we evaluated the model performance of Auto-Regressive Integrated Moving Average (ARIMA) and Holt Winters exponential smoothing (HWES). The error indicators: Mean percentage error (MPE), Mean absolute error (MAE), Mean absolute scaled error (MASE), Root-mean-square error (RMSE) and Mean absolute percentage error (MAPE) showed that HWES is an appropriate model with reasonable forecast accuracy. The HWES (α = 1, β = 0.1246865) showed smallest error than those of the ARIMA (0, 1, 2) models. Hence, the HWES (α = 1, β = 0.1246865) can be used to model annual international tourist arrivals in Zambia. Further, forecasting results give a gradual increase in annual international tourist arrivals of about 42% by 2024. Accurate forecasts are key to new investors and Policymakers. The Zambian government should use such forecasts in formulating policies and making strategies that will promote the tourism industry.
Highlights
Tourism is one of the major contributors to foreign exchange earnings for Zambia and other countries worldwide
In this study we evaluated the model performance of Auto-Regressive Integrated Moving Average (ARIMA) and Holt Winters exponential smoothing (HWES)
The error indicators: Mean percentage error (MPE), Mean absolute error (MAE), Mean absolute scaled error (MASE), Root-mean-square error (RMSE) and Mean absolute percentage error (MAPE) showed that HWES is an appropriate model with reasonable forecast accuracy
Summary
Tourism is one of the major contributors to foreign exchange earnings for Zambia and other countries worldwide. According to [1] an international tourist. Data collection methods for arrivals vary from one country to another. In some countries data are from border statistics. In other countries data are from tourism accommodation establishments. Tourist data refer to the number of arrivals, not to the number of people traveling. A person who makes several travels to a country during a given period is counted each time as a new arrival. Tourism contributes highly to GDP, increasing the employment rate, source of revenue for local people, private sector, public sectors and government [2]. The significance of tourism has encouraged the authors to study the number of international tourist arrivals and attempt to make more accurate forecasting for future planning
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