Google Trends and tourists’ arrivals: Emerging biases and proposed corrections

Theologos Dergiades, Eleni Mavragani, Bing Pan

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)108-120
Number of pages13
JournalTourism Management
Volume66
DOIs
StatePublished - Jun 2018

All Science Journal Classification (ASJC) codes

  • Development
  • Transportation
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management

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