Abstract:

In this study, the forecasting method which is an interdisciplinary tool, was taken from the point of view of production and operations management and a demand forecasting application has been undertaken in the Turkish tourism industry. The data set consists of the total number of tourists (domestic and foreign) who stayed in tourism resorts licensed by the Ministry of Culture and Tourism between the period of 2000 and 2007 in Turkey. The purpose of this study is to find the most appropriate time series forecasting method for the data set in hand and to forecast the number of tourists who stayed in those resorts licensed by the Ministry for six months in 2008. To fulfill this goal, four types of time series forecasting method named as Moving Average, Exponential Smoothing, and Holf's and Winter's Methods' performance are compared with each other by using the monthly data set. As a result of the analyses, Winter's Method has been found to be the best method among the others due to its feature of containing seasonality and trend using this method, the total number of tourists (domestic and foreign) who stayed in those resorts licensed by the Ministry in Turkey for the first six months of 2008 has been forecasted.

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