New Paper Published – Volchek, K., Liu, A., Song, H., Buhalis, D. (2018). Forecasting tourist arrivals at attractions: Search engine empowered methodologies. Tourism Economics. https://doi.org/10.1177/1354816618811558
Abstract
Tourist decision to visit attractions is a complex process influenced by multiple factors of individual context. This study investigates how the accuracy of tourism demand forecasting can be
improved at the micro level. The number of visits to five London museums is forecast and the predictive powers of Naïve I, seasonal Naïve, seasonal autoregressive moving average, seasonal autoregressive moving average with explanatory variables, SARMAX-mixed frequency data sampling and artificial neural network models are compared. The empirical findings extend understanding of different types of data and forecasting algorithms to the level of specific attractions. Introducing the Google Trends index on pure time-series models enhances the forecasts of the volume of arrivals to attractions. However, none of the applied models outperforms the others in all situations. Different models’ forecasting accuracy varies for short- and long-term demand predictions. The application of higher frequency search query data allows for the generation of weekly predictions, which are essential for attraction- and destination-level planning.
Keywords: artificial intelligence, attractions, forecasting, Google Trends, search engine, tourist demand
Every BU academic has a
By clicking on this box, on the left of the Research Blog home page just under the text ‘Funding Opportunities‘, you access a 













The significance of Rights and Protocols in Disaster Response
Celebrate World Wellbeing Week This June
Official book launch at Bournemouth University
Take a Break: Join the Creative Wellbeing Event
Psychology, Psychiatry and Neuroscience academics – would you like to get more involved in preparing our next REF submission?
Horizon Europe Cluster 3 (Civil Security for Society) 2026 Calls Now Open
MSCA Doctoral Networks 2026 Call Information Webinar
ESRC Festival of Social Science 2026: Application Deadline Extended to Thursday 25 June 2026
Reminder: Register for the ESRC Festival of Social Science 2026 Information Session
ECR Funding Open Call: Research Culture & Community Grant – Apply now
ERC Advanced Grant 2025 Webinar
Update on UKRO services
European research project exploring use of ‘virtual twins’ to better manage metabolic associated fatty liver disease