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Forecasting the Number of Tourists Visiting Turkey: Artificial Neural Networks versus Error Correction Model

S. Selim, Ç. Demir


Tourism is important particularly in terms of providing the foreign currency required by the developing countries in order to accelerate their progress. By force of tourism investments especially in recent years, Turkey has achieved to take a place near the top in the world tourism. In determining the policies related to tourism and performing the planning, tourism demand should accurately be forecasted by using appropriate methods. In this study, the tourism demand model of Turkey was discussed with Wickens-Breusch (W-B) model, for the period 1980-2007. Besides, utilizing the long-term relationship acquired from the W-B model of the period 1980-2002 and artificial neural networks (ANN), the number of the tourists visiting Turkey was forecasted for the years 2003-2007 and performances of both models were compared. ANN was determined to be a better alternative method in forecasting the total numbers of the tourists visiting Turkey.


Forecasting tourism demand, artificial neural networks, error correction model, Turkey

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