Recreation demand analysis of sensitive natural areas from an on-site survey

Abstract

Distribution électronique Cairn.info pour Armand Colin. © Armand Colin. Tous droits réservés pour tous pays. La reproduction ou représentation de cet article, notamment par photocopie, n'est autorisée que dans les limites des conditions générales d'utilisation du site ou, le cas échéant, des conditions générales de la licence souscrite par votre établissement. Toute autre reproduction ou représentation, en tout ou partie, sous quelque forme et de quelque manière que ce soit, est interdite sauf accord préalable et écrit de l'éditeur, en dehors des cas prévus par la législation en vigueur en France. Il est précisé que son stockage dans une base de données est également interdit.

From supply to demand factors: What are the determinants of attractiveness for outdoor recreation?

“…The attractiveness based on supply factors of each recreational unit is predicted with a count data model. These models are particularly accurate when the dependent variable is an integer that takes few values, such as visitors' trips to a destination site (Shaw, 1988;Englin and Shonkwiler, 1995;Baerenklau et al, 2010, Roussel et al, 2016.…”

“…where is the probability that a visitor coming from an outset location will take no trip to forest and 1 − is the probability that follows a Poisson law with a λ parameter (see Roussel et al (2016) for more explanations on the standard Poisson model).…”

A geospatial model of nature-based recreation for urban planning: Case study of Paris, France

“…the search radii for different age groups, a Poisson regression was applied to the stated number of visits. The count data models such as the Poisson or negative binomial are commonly used to analyse visitation data, as this type of models is particularly accurate when the dependent variable is an integer that takes few different values, such as visitor trips to a destination site (Shaw, 1988;Englin and Shonkwiler, 1995;Baerenklau et al, 2010;Roussel et al, 2016;Tardieu and Tuffery, 2019). When plotting the data, we found that the Poisson function best described the decay of visitation against travelled distance to greenspace in our dataset.…”

Economic contribution and social welfare of recreational charter boat fisheries in the northeast Atlantic: The cases of Galicia (Spain) and Madeira archipelago (Portugal)

“…We finally used the product between the round trip time and 1/3 of the wage rate to estimate the OCT (Martıńez-Espiñeira and Amoako-Tuffour, 2008;Roussel et al, 2016). The wage rate was approximated by the monthly income divided by the monthly hours of work (information that was provided in the questionnaires answered by the anglers).…”

“…Where p i (•) represents the vector of other visitor-specific independent predictors. These predictors included N i , which accounted for the number of days devoted to the practice of alternative leisure activities during the current fishing trip (following Roussel et al, 2016). G i included group size, i.e., the number of people traveling with the angler, in the fitted GAMs (including non-angling travelers).…”