Big data spatial analysis of campers' landscape preferences: Examining demand for amenities.

Outdoor recreation decision-making has received significant research interest over the last fifty years. In the context of campsite choice, this previous research has almost exclusively used stated preference data and aspatial methods to understand decision-making. This present research seeks to understand how recreationists reach decisions on the selection of campsites and what aspects of the recreational setting drive demand through an examination of a big dataset of revealed preference data using a spatial regression. Specifically, we examine which managerial, social, and ecological aspects of the setting influence demand for campsites in Zion National Park's (USA) Watchman Campground using reservation data from the Recreation Information Database (RIDB). Results indicate that price, access to electricity, ease of access, and proximity to the Virgin River are significantly predictive of demand. Study implications for park management, including campsite allocation and distributive justice, are provided. Additionally, implications for future research methodology, including the use of transaction-style big data in protected area management research, are discussed.