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Title: Common trends in international tourism demand: Are they useful to forecast tourism predictions?
Author: Clavería González, Óscar
Monte Moreno, Enric
Torra Porras, Salvador
Keywords: Previsió econòmica
Desenvolupament econòmic
Xarxes neuronals (Informàtica)
Economic forecasting
Economic development
Neural networks (Computer science)
Issue Date: 2015
Publisher: Elsevier Ltd
Abstract: This study evaluates whether modelling the existing commont trends in tourism arrivals from all visitor markets to a specific destination can improve tourism predictions. While most tourism forecasting research focuses on univariate methods, we compare the performance of three different Artificial Neural Networks in a multivariate setting that takes into account the correlations in the evolution of inbound international tourism demand to Catalonia (Spain). We find that the multivariate multiple-output approach does not outperform the forecasting performance of the networks when applied country by country, but it significantly outperforms the forecasting performance for total tourist arrivals.
Note: Versió postprint del document publicat a:
It is part of: Tourism Management Perspectives , 2015, vol. 16, p. 116-122
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ISSN: 2211-9736
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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