Clavería González, ÓscarMonte Moreno, EnricTorra Porras, Salvador2015-09-102015-09-1020152211-9736https://hdl.handle.net/2445/66855This 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.7 p.application/pdfeng(c) Elsevier Ltd, 2015Previsió econòmicaTurismeDesenvolupament econòmicXarxes neuronals (Informàtica)Economic forecastingTourismEconomic developmentNeural networks (Computer science)info:eu-repo/semantics/article6539802015-09-10info:eu-repo/semantics/openAccess