Abstract:
This study has two purposes. Firstly, it aims to identify models that best estimate tourism demand. Secondly, it also aims to estimate the demand of Spanish tourists who visit Cappadocia, by using the identified proper models. As international tourism demand continually grows, the importance and magnitude of the tourism sector for the economies of the countries increase. In order to take into account the tourism demand, countries need to be prepared and therefore they want to know about the future demand. However, it is not always possible to know 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 visits in Cappadocia region of Turkey. In accordance with this aim, eight forecasting models are used. The results of the analyses for each model are obtained and the forecasting accuracy examined. It is seen that the Artificial Neural Networks and the Multiple Regression Model outperforms the other models. Finally, limitations of the study and future resarch directions are discussed.