FORECASTING TOURISM DEMAND: A CASE STUDY FOCUSING ON SPANISH TOURIST’ S TRAVEL TO CAPPADOCIA

As international tourism demand continually grows, the importance and magnitude of the tourism sector for the economy of the countries increases. Based on the tourism demand, countries want to be prepared and they need to know the future demand. However, it is not always possible to have the knowledge of the actual demand and one can only make forecasts in such cases. This paper deals with forecasting international tourism demand specifically focusing on the Spanish tourist arrivals in Cappadocia region of Turkey. In accordance with this aim, eight forecasting models are used. The results of the analysis for each model is attained and the forecasting accuracy examined. It is seen that Artificial Neural Networks and the Multiple Regression Model outperforms other models. Finally, administrative inferences, confines of the study and instructions for hereafter researches are given in this paper.

Anahtar Kelimeler:

Spanish Tourist Arrivals, Artificial Neural Networks, Tourism Demand Forecasting, Cappadocia, Multiple Regression

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