Assessment of tourist arrival from Russian to Antalya using the univariate time series methods

Abstract

With the continuous growth of Antalya tourism, the need for more accurate tourism forecasts emerge and the forecast performance is evaluated according to time series methods. Seasonal fluctuations are the most important feature of the tourism series and this feature makes it a suitable environment for comparing the forecast productivity of different models. In this study, the data of tourists coming from Russia to Antalya from 2007 to 2018 are used. The parametric and nonparametric univariate time series techniques, ARIMA, ETS, Combination (or Hybrid) and SSA, are compared in forecasting tourism demand. As a result of this paper, it is understood that the nonparametric SSA technique is more accomplished with respect to the accuracy of the obtained forecasts.