Artigo em revista científica Q2
Forecasting tomorrow’s tourist
Sérgio Moro (Moro, S.); Paulo Rita (Rita, P.);
Título Revista
Worldwide Hospitality and Tourism Themes
Ano (publicação definitiva)
2016
Língua
Inglês
País
Reino Unido
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Abstract/Resumo
Purpose: This study aims to present a very recent literature review on tourism demand forecasting based on 50 relevant articles published between 2013 and June 2016. Design/methodology/approach: For searching the literature, the 50 most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles were scrutinized according to three main dimensions: the method or technique used for analyzing data; the location of the study; and the covered timeframe. Findings: The most widely used modeling technique continues to be time series, confirming a trend identified prior to 2011. Nevertheless, artificial intelligence techniques, and most notably neural networks, are clearly becoming more used in recent years for tourism forecasting. This is a relevant subject for journals related to other social sciences, such as Economics, and also tourism data constitute an excellent source for developing novel modeling techniques. Originality/value: The present literature review offers recent insights on tourism forecasting scientific literature, providing evidences on current trends and revealing interesting research gaps.
Agradecimentos/Acknowledgements
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Palavras-chave
Tourism forecasting,Tourism demand,Tourists’ behavior,Modeling,Tourism prediction
  • Ciências da Terra e do Ambiente - Ciências Naturais
  • Psicologia - Ciências Sociais
  • Economia e Gestão - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UID/GES/00315/2013 Fundação para a Ciência e a Tecnologia