Publication: Brief report on visitor frequency in the AIR use cases

How are visitor frequencies distributed over the year and what share do the different visitor groups have? The project AIR (= AI-based Recommender for Sustainable Tourism) has answered this question comprehensively in the latest short report for selected case studies in Schleswig-Holstein, North Rhine-Westphalia and Bavaria. For this purpose, anonymized mobile location events (location data from the GPS receiver in the smartphone) were collected and descriptively analyzed in a total of 19 polygons for the years 2022 and 2023.

The results make it clear that day tourists make up the largest proportion of visitors in many of the areas surveyed and that the frequency of visits is often subject to seasonal fluctuations. Locations with highly seasonal attractions, such as ski resorts or coastal regions, show significantly higher demand in individual calendar weeks. Overall, the frequency of visits tended to fall in 2023. This understanding of visitor frequency and seasonal fluctuations supports the optimization of tourism infrastructure and the targeted development of digital visitor management.

The AIR project aims to develop digital strategies to avoid the temporary congestion of travel and excursion destinations by providing visitors with targeted information and suggesting alternative destinations. The use of a recommender is intended to improve the distribution of visitor flows in order to support the sustainable development of tourism. The project is being funded by the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) until the end of 2024.

Please also visit the project website with lots more information at https://di-tourismusforschung.de/de/details-zu-projekte/ai-basierter-recommender-fuer-nachhaltigen-tourismus-airund www.air-tourism.de.

If you have any questions, please contact Julian Reif and Denise Engelhardt.