Logistics & Supply Chain Management: Faculty Presentations (1998-2020)

Issues in Forecasting International Tourist Travel

Document Type

Presentation

Presentation Date

4-2012

Copyright

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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.

Additional Information

This presentation is available in the Academy of Information and Management Sciences Journal Proceeding volume 16, number 1 on page 33.

Sponsorship/Conference/Institution

Allied Academies International Conference

Location

New Orleans, LA

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