Forecasting tomorrow's tourist

Sérgio Moro, Paulo Rita
2016 Worldwide Hospitality and Tourism Themes  
Purpose -This study presents a very recent literature review on tourism demand forecasting, based on fifty relevant articles published between 2013 and June 2016. Design/methodology/approach -For searching the literature, the fifty most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles was scrutinized according to three main dimensions: the method or technique used for analyzing data; the location of the study, and the covered
more » ... he 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 constitutes 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.
doi:10.1108/whatt-09-2016-0046 fatcat:kd7rhmj6uzae5lx5tx23cqy52q