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Forecasting tourism demand with Google trends: Accuracy comparison of countries versus cities
Author(s) -
Önder Irem
Publication year - 2017
Publication title -
international journal of tourism research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.155
H-Index - 58
eISSN - 1522-1970
pISSN - 1099-2340
DOI - 10.1002/jtr.2137
Subject(s) - tourism , destinations , autoregressive model , regional science , baseline (sea) , index (typography) , econometrics , geography , computer science , economics , political science , world wide web , archaeology , law
Previously, Google Trends indices have been found to be useful in improving the tourism demand forecast accuracy relative to a purely autoregressive baseline model. The purpose of this study is to extend previous research in terms of comparing the forecasting accuracy of cities and countries using Google Trends Web and image indices. The study compares forecasting models with Web and/or image search indices regarding 2 cities (Vienna and Barcelona) and 2 countries (Austria and Belgium). Overall, the forecast accuracy of Vienna with the Web and/or image indices was the best among the 4 destinations, followed by Belgium, Barcelona, and Austria.