MODELLING TOURISM DEMAND: A COMPARATIVE STUDY BETWEEN ARTIFICIAL NEURAL NETWORKS AND THE BOX-JENKINS METHODOLOGY

Paula Fernandez (), Joao Teixeira (), Joao Matos Ferreira and Susana Garrido Azevedo ()
Additional contact information
Paula Fernandez: Department of Economics and Management, Polytechnic Institute of Braganca (IPB), Portugal
Joao Teixeira: Department of Electrical Engineering, Polytechnic Institute of Bragança (IPB), Portugal
Authors registered in the RePEc Author Service: Paula Odete Fernandes ()

Journal for Economic Forecasting, 2008, vol. 5, issue 3, pages 30-50

Abstract: 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.

Keywords: Artificial Neural Networks; ARIMA Models; Time Series Forecasting (search for similar items in EconPapers)
JEL-codes: C01 C02 C22 C45 L83 (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.ipe.ro/rjef/rjef3_08/rjef3_08_2.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:rjr:romjef:v:5:y:2008:i:3:p:30-50

Access Statistics for this article

Journal for Economic Forecasting is edited by Lucian Liviu Albu, Corina Saman and Cornelia Scutaru

More articles in Journal for Economic Forecasting from Institute for Economic Forecasting
Contact information at EDIRC.
Series data maintained by Corina Saman ().