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The Relationship between Measured Visitor Density and Perceived Crowding Revisited

Predicting Perceived Crowding in Outdoor Recreation

Bibliographic Data

ID6441353
AuthorsStefanie Döringer (0000-0002-7817-4698, Bavarian Forest National Park, corresponding author), Florian Porst (Bavarian Forest National Park), Lena Stumpf (Bavarian Forest National Park), Marco Heurich (0000-0003-0051-2930, Bavarian Forest National Park)
Year2023
Volume47
Issue8
Pages2071-2094
Publication date2023-10-11
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueLeisure Sciences (JOURNAL)
Journal identifiersISSN: 0149-0400 • E-ISSN: 1521-0588
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/01490400.2023.2265366
OpenAlexW4387525044
LanguageEN
Citations received3
References cited61

Protected areas around the globe face increasing visitation numbers and crowding, a situation exacerbated by the COVID-19 pandemic. Although measured visitor density and perceived crowding are strongly related, analyses of this relationship are lacking. We argue that measured visitor density serves as a reliable and objective indicator of perceived crowding. This study therefore examined the effects of visitation numbers, perceived encounters, and expectations on perceived crowding in the Bavarian Forest National Park (Germany). Automated visitor counts at six park locations were linked to data from an on-site crowding survey conducted in 2021. A predictive model and visitation thresholds were calculated using a logistic regression, which showed that visitation numbers are a well-suited predictor of crowding. The results indicated a strong association between measured visitor density and perceived crowding, moderated by site-specific conditions. The calculated thresholds provide a valuable instrument that can be used to inform the public in advance about peak visiting times.Keywords: Perceived crowdingpredictive modelprotected areavisitation numbersvisitor density AcknowledgmentsWe are indebted to the interviewers and to the survey participants in the Bavarian Forest National Park.Disclosure statementWe declare no conflict of interest.Correction StatementThis article has been republished with minor changes. These changes do not impact the academic content of the article.Additional informationFundingThis work was funded by the Bavarian State Ministry of the Environment and Consumer Protection, project "Analysis of the socio-ecological system in the Bavarian Forest National Park

Crowding · Crowding out · Descriptive statistics · Economics · Geography · National park · Recreation · Socioeconomics · Sociology · Statistics · Visitor pattern · Computer Science · Demography · Diverse Aspects of Tourism Research · Ecology · Mathematics · Psychology · Recreation, Leisure, Wilderness Management · Social Psychology · Urban Green Space and Health

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Unique citing works3
Citations per year1,5
Citation span2024 - 2024 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 3

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