Title:
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Common trends in international tourism demand: Are they useful to forecast tourism predictions?
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Author:
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Clavería González, Óscar; Monte Moreno, Enric; Torra Porras, Salvador
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Other authors:
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Universitat de Barcelona |
Abstract:
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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. |
Subject(s):
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-Previsió econòmica -Turisme -Desenvolupament econòmic -Xarxes neuronals (Informàtica) -Economic forecasting -Tourism -Economic development -Neural networks (Computer science) |
Rights:
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(c) Elsevier Ltd, 2015
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Document type:
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Article Article - Accepted version |
Published by:
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Elsevier Ltd
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