Forecasting London Museum Visitors Using Google Trends Data

Authors

  • Ekaterina Volchek School of Hotel and Tourism Management The Hong Kong Polytechnic University
  • Haiyan Song School of Hotel and Tourism Management The Hong Kong Polytechnic University
  • Rob Law School of Hotel and Tourism Management The Hong Kong Polytechnic University
  • Dimitrios Buhalis Department of Tourism and Hospitality Bournemouth University

Keywords:

Attractions, museum, forecast, search engine, information search, Google Trends

Abstract

Information search is an indicator of tourist interest in a specific service and potential purchase decision. User online search patterns are a well-known tool for forecasting pre-trip consumer behaviour, such as hotel demand and international tourist arrivals. However, the potential of search engine data for estimating the demand for tourist attractions, which is created both before and during a trip, remains underexplored. This research note investigates the relationships between Google search queries for the most popular London museums and actual visits to these attractions. Preliminary findings indicate high correlation between monthly series data. Search query data is expected to generate reliable forecasts of visits to London museums.

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Published

2018-02-05

How to Cite

Volchek, E., Song, H., Law, R. and Buhalis, D. (2018) “Forecasting London Museum Visitors Using Google Trends Data”, e-Review of Tourism Research. Available at: https://ertr-ojs-tamu.tdl.org/ertr/article/view/121 (Accessed: 28 March 2024).

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