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Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/1042

Título: Modelling tourism demand: a comparative study between artificial neural networks and the Box-Jenkins methodology
Autor: Fernandes, Paula O.
Teixeira, João Paulo
Ferreira, João José
Azevedo, Susana Garrido
Palavras-chave: Artificial neural networks
ARIMA models
Time series forecasting
Issue Date: 2008
Editora: The Institute for Economic Forecasting
Citação: Fernandes, Paula O.; Teixeira, João Paulo; Ferreira, João José; Azevedo, Susana Garrido (2008) - Modelling tourism demand: a comparative study between artificial neural networks and the Box-Jenkins methodology. Romanian Journal of Economic Forecasting. ISSN 1582-6163. 9:3 p.30-50
Resumo: 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.
URI: http://hdl.handle.net/10198/1042
ISSN: 1582-6163
Appears in Collections:DEG - Artigos em Revistas Indexados ao ISI
DE - Artigos em Revistas Indexados ao ISI

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