FORECASTING TOURISM DEMAND WITH ARTIFICIAL NEURAL NETWORKS

Authors

  • Paula Odete Fernandes Polytechnic Institute of Bragança
  • João Paulo Teixeira Polytechnic Institute of Bragança
  • João Matos Ferreira University of Beira Interior (UBI)
  • Susana Garrido Azevedo University of Beira Interior (UBI)

Keywords:

Artificial Neural Networks, Nonlinear Time Series, Modelling, Tourism Forecasting

Abstract

Tourism has been viewed as an important player for the economic redevelopment of certain rural regions because of the attraction of landscapes, mountain, and the interest in second-home or investment opportunities at lower prices (Jackson & Murphy, 2002). Even with tourism?s potential for development at all levels, there have been very few studies regarding models for estimating the local impact of tourism (Jackson & Murphy, 2006). To enhance understanding of the nature of forecasting in tourism destinations it is valuable to study systematically the possible estimative of influence that tourism destination has on an area.

 

 

The main objective of this study is to present a set of models for tourism destinations competitiveness, using the Artificial Neural Networks methodology. This study focuses on two Portuguese regions - North and Centre - as tourism destinations offering a large range of tourist products, that goes beyond the beach, the mountains, the thermals not forgetting the rural tourism that has growing in the last years. These tourism destinations offer an interesting alternative to the „mass tourism? and have become more competitive, since the last one is normally associated with negative environmental impacts.

Author Biographies

  • Paula Odete Fernandes, Polytechnic Institute of Bragança
    PhD, Professor of the Economics and Management Department
  • João Paulo Teixeira, Polytechnic Institute of Bragança
    PhD, Professor of the Electrical Department
  • João Matos Ferreira, University of Beira Interior (UBI)
    PhD, Assistant Professor of the Management and Economics Department
  • Susana Garrido Azevedo, University of Beira Interior (UBI)
    PhD, Assistant Professor of the Management and Economics Department

Published

25.01.2012

How to Cite

FORECASTING TOURISM DEMAND WITH ARTIFICIAL NEURAL NETWORKS. (2012). Tourism & Management Studies, 1017-1019. https://tmstudies.net/index.php/ectms/article/view/269