Towards a joint visitor monitoring approach: Applying protected area experiences in destination management – Lessons from Schrecksee, Germany
Year: 2025
Type: article
Study design: Observational Study
Abstract: Destination management organisations (DMO) increasingly face the challenge of managing visitor flows due to overtourism problems, critical attitudes of local residents and stakeholders towards tourism but also aspirations for more sustainability in tourism. Effective, applicable evidence-based visitor management requires data from visitor monitoring, which in Germany is currently mostly limited to large-scale protected areas with some destinations setting up first approaches. Therefore, we demonstrate how established monitoring approaches from protected areas can be successfully transferred to less strictly protected settings including the spheres of DMOs. We advocate for a cooperative joint approach between DMOs and protected area actors to enable evidence-based visitor governance. As a showcase, we use Lake Schrecksee in the Nature Conservation Area Allgäuer Hochalpen, Germany, a site notorious for overtourism complaints during the Covid-19-pandemic. Based on four years of automated visitor counting and two standardized online visitor surveys (n=232 each), a low threshold yet robust monitoring approach is introduced. Results reveal pronounced seasonal and weather-related peaks in visitation (culminating at almost 25,000 visits in 2021), with 62.3 % of daily fluctuations explained by key variables in time-series regression modelling. The survey results illustrate information about visitor structure, motivation, satisfaction, crowding perception, knowledge about and affinity for protected areas. Based on the literature, our results and experiences at the Schrecksee we derive a list of practical recommendations for DMO managers and actors responsible for protected areas to set up visitor monitoring approaches beyond large-scale and strictly protected areas.
DOI: 10.1515/tw-2025-0022
Authors: Michael Grimm, Marius Mayer
Institution: Munich University of Applied Sciences
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W4415488037