Abstract:

Planning of tourism investment and tourist activities across the country are of great importance for tourist areas. The forecasting of tourism demand to region or country should be forecasted primarily for planning. Because, planning not based on demand forecasting cannot be placed on a realistic basis. Demand forecasting is necessary both guiding infrastructure and superstructure investments compatible to this demand and determination of capacity of tourist areas thus eliminating the negative effects of tourism economically and environmentally. As the demand for tourism goods and services are extremely sensitive against effective factors in the tourism sector, the estimate of this sector and the analysis of the factors effecting on this demand are gaining importance. In recent years, it is observed that artificial neural network methods are widely used in demand forecasting and this method has higher forecast performance than the other methods. In this study, artificial neural network forecasting performance is evaluated using six independent variables and it is forecasted monthly demand for tourism in the future. So, with this study it is presented that artificial neural network method can be used easily as an alternative to traditional forecasting methods for practitioners in tourism sector and managers in the position of decision-making through planning for future

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