Logistics & Supply Chain Management: Faculty Presentations (1998-2020)
Issues in Forecasting International Tourist Travel
Document Type
Presentation
Presentation Date
4-2012
Copyright
See the publisher's copyright and reuse policies.
Abstract or Description
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.
Sponsorship/Conference/Institution
Allied Academies International Conference
Location
New Orleans, LA
Recommended Citation
Moss, Steven E., Jun Liu, Janet Moss.
2012.
"Issues in Forecasting International Tourist Travel."
Logistics & Supply Chain Management: Faculty Presentations (1998-2020).
Presentation 54.
https://digitalcommons.georgiasouthern.edu/logistics-supply-facpres/54
Additional Information
This presentation is available in the Academy of Information and Management Sciences Journal Proceeding volume 16, number 1 on page 33.