Issues in Forecasting International Tourist Travel

Steven E. Moss, Jun Liu, Janet Moss

Research output: Contribution to conferencePresentation

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Abstract

In this paper two popular time series methods for modeling seasonality in tourism forecasts are compared. The first uses a decomposition methodology to estimate seasonal variation. In this method seasonal variation is estimated with a ratio-to-centered moving average approach. Three different approaches in calculating the seasonal indices are analyzed. The deseasonalized series are then forecast using an ARIMA model. The second methodology uses a multiplicative seasonal ARIMA (SARIMA) approach to simultaneously model trend and seasonal variations. The two methodologies are compared and the accuracy and managerial advantages of each are discussed.

Original languageAmerican English
StatePublished - Apr 1 2012
EventAllied Academies International Conference -
Duration: Apr 1 2012 → …

Conference

ConferenceAllied Academies International Conference
Period04/1/12 → …

Keywords

  • Forecasting
  • Tourism
  • ARIMA
  • SARIMA
  • Travel

DC Disciplines

  • Business Administration, Management, and Operations
  • Operations and Supply Chain Management

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