| dc.description |
<p>The European Capital of Culture in 2010, Istanbul, is one of the richest tourist destinations in terms of historical, cultural and natural tourism values. Istanbul, the capital city of the empires, where traces of different historical and cultural civilizations can be seen from the past; Topkapi Palace, Sultanahmet Mosque, Süleymaniye Mosque, Yerebatan Cistern, Cemberlitas, Haghia Sophia, Bosphorus and Islands attract a large number of tourists every year with its cultural and natural riches. Tourism demand forecasts are one of the basic indicators that guide the planning activities of the tourism industry, the related public institutions and the tourism destination managers. Reliable and accurate demand forecasts are needed in order to efficiently plan all activities related to the tourism sector such as accommodation, transport and travel, infrastructure services and tourist investment projects. In this study, appropriate models were constructed for the structure of data from Exponential Smoothing and Box-Jenkins methods and prediction results of the models obtained were compared and it was aimed to make monthly foreign tourism demand estimates for Istanbul province for 2018 and 2019 with the help of the model providing the highest accuracy. The number of tourists entering the border gates was taken as a measure of tourism demand in the study and the number of foreign visitors entering from Atatürk Airport, Sabiha Gökçen Airport, Haydarpaşa Port, Pendik Port, Tuzla Port, Zeytinburnu Port, Ambarlı Port and Karaköy Port in the period of January 2010 - April 2018 has been utilized. In order to determine appropriate methods, the time series characteristics of the data were analysed and the basic components affecting the data were examined and the monthly expost number of the tourists were estimated from the Exponential Smoothing and Box-Jenkins methods and models appropriate for the structure of the data. Monthly inbound tourism demand forecasts for the provinces of Istanbul for the years of 2018 and 2019 were made with the aid of the model providing the highest estimation accuracy, as a result of evaluating the estimation results obtained from the applied methods. In the study, the forecasting accuracy of the used models was evaluated by the "Mean Absolute Percentage Error (MAPE)" statistic. By producing forecasts it is aimed to create a basis for tourism development plans prepared by the managers from private and public sector and to provide support for administrators’ future planning decisions.</p> |
|