Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Aug 2026, 01:50:39am WEST
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Daily Overview |
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Forestry 2 Location: D-104 Session Chair: Yuqi Song, The Hong Kong University of Science and Technology (Guangzhou) | |
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Estimating Recreation Demand with Random Forests and Shapley Values 1: Università degli Studi di Padova; 2: Virginia Tech This paper introduces an explainable machine-learning framework for environmental valuation using stated-preference data. We analyse recreation demand for the Cansiglio Forest in northeastern Italy, where congestion issues have prompted policy interest in parking fees as a management tool. Using data from a contingent-behaviour experiment, we estimate visit demand with a Random Forest model that flexibly captures nonlinearities, thresholds, and heterogeneous responses without imposing functional-form or distributional assumptions. To recover economic interpretability, we combine the Random Forest with Shapley values, which decompose each prediction into contributions of individual variables. The results show that seasonality and visitor characteristics dominate demand, while parking fees have a nonlinear and heterogeneous effect: moderate prices have little impact, whereas high fees reduce visits for a subset of more price-sensitive users. Our framework reveals threshold effects and heterogeneity that standard parametric models would be prone to mask. Overall, the approach offers a powerful tool for environmental valuation and support of policy design. | |