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 by predicting the number of visits to London museums. The number of visits to London museums is forecasted and the predictive powers of Naïve I, seasonal Naïve, SARMA, SARMAX, SARMAX-MIDAS 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 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 generation of weekly predictions, which are essential for attraction-and destination-level planning.

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Metaverse is named among the technologies that are predicted to transform everyday life. The proliferation of such technologies as the Internet and smartphones has triggered major transformations in the tourism industry. This paper conceptualises the phenomenon of Metaverse towards the phenomenon of tourism. It applies a semi-systematic literature review methodology to identify existing alignment between the phenomena. The paper concludes that there is a conceptual alignment between the critical dimensions of the Metaverse and tourism. Tourism should be ready for the reciprocal effects of metaverse development on tourism and vice versa, from new opportunities to enhance tourist experience to a possible dissolution of the contemporary understanding of tourism.

The personalisation-privacy paradox demonstrates a two-fold effect of tourists’ awareness about personalisation on their experience. Compulsory personal data agreements under the GDPR and similar legislation acts raise tourists’ concerns regarding privacy and security. The role of tourist awareness about the value of data-driven personalisation in their co-creation behaviour remains underexplored. This paper applies an exploratory experiment methodology to identify the effects of information about personalisation on tourists’ experience with travel information websites. It triangulates the data from eye-tracking and self-report techniques, to compare the co-creating behaviour of respondents who have or have not been informed about the value of personalisation. The study demonstrates the presence of a personalisation-privacy paradox. It further reveals that awareness about data-driven personalisation motivates tourists to reinforce value co-creation by ensuring the accuracy of information filtering. The study advances our understanding of tourist digital behaviour and provides insights for the design of personalised information services.

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