Modelling tourism demand: a comparative study between artificial neural network...

• Author(s): Fernandes, Paula O. ; Teixeira, João Paulo ; Ferreira, João José ; Azevedo, Susana Garrido
• Date: 2008
• Persistent ID: http://hdl.handle.net/10198/1042
• Origin: Biblioteca Digital do IPB
• Subject(s): Artificial neural networks; ARIMA models; Time series forecasting
• Document Type: Article
• Language: English

Description

This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN) methodology as an alternative to the Box-Jenkins methodology in analysing tourism demand. To this end, each of the above-mentioned methodologies is centred on the treatment, analysis and modelling of the tourism time series: “Nights Spent in Hotel Accommodation per Month”, recorded in the period from January 1987 to December 2006, since this is one of the variables that best expresses effective demand. The study was undertaken for the North and Centre regions of Portugal. The results showed that the model produced by using the ANN methodology presented satisfactory statistical and adjustment qualities, suggesting that it is suitable for modelling and forecasting the reference series, when compared with the model produced by using the Box-Jenkins methodology.