{'fraction_non_alphanumeric': 0.015613382899628252, 'fraction_numerical': 0.0, 'mean_word_length': 5.063063063063063, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Combining RP and SP data while accounting for large choice sets and travel mode – an application to forest recreation

This paper analyses the use of forests for recreational purposes in Lorraine, France, a region with many forests and easy access for recreational users. This implies that residents in Lorraine can choose between a large set of forests if they decide to visit a forest. The abundance of forests in Lorraine makes identification of the visited forests difficult. To facilitate identification of forests actually visited, we have incorporated an interactive map in a Web-based survey intended to include both revealed and stated preference data. We compare different sampling schemes to define the choice set used for site selection modelling when the actual choice set considered is potentially large and unknown to the analyst. Easy access to forests also implies that around half of the visitors walk or bike to the forest. We apply an error-component mixed-logit model to simultaneously model the travel mode decision and the site selection decision and to combine revealed and stated preference data. Finally, the effect on the willingness-to-pay of changes in forest quality and access is evaluated based on alternative choice set specifications, model specifications and data sources (revealed and stated preference data).