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Title: Google Trends and tourists' arrivals: Emerging biases and proposed corrections
Authors: Dergiades, Theologos
Mavragani, Eleni
Pan, Bing
Type: Article
Subjects: FRASCATI::Social sciences::Economics and Business::Economics
FRASCATI::Social sciences::Economics and Business::Econometrics
Keywords: Web search intensity
Google Trends
Tourists' arrivals
Issue Date: Jun-2018
Publisher: Elsevier
Source: Tourism Management
Volume: 66
First Page: 108
Last Page: 120
Abstract: As search engines constitute a leading tool in planning vacations, researchers have adopted search engine query data to predict the consumption of tourism products. However, when the prevailing shares of visitors come from countries in different languages and with different dominating search engine platforms, the identification of the aggregate search intensity index to forecast overall international arrivals, becomes challenging since two critical sources of bias are involved. After defining the language bias and the platform bias, this study focuses on a destination with a multilingual set of source markets along with different dominating search engine platforms. We analyze monthly data (2004–2015) for Cyprus with two non-causality testing procedures. We find that the corrected aggregate search engine volume index, adjusted for different search languages and different search platforms, is preferable in forecasting international visitor volumes compared to the non-adjusted index.
ISSN: 0261-5177
Other Identifiers: 10.1016/j.tourman.2017.10.014
Appears in Collections:Department of International and European Studies

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