THE ROLE OF BIG DATA IN FORECASTING TOURIST ROUTES TO PROTECTED AREAS
Abstract
The article examines the role of big data in forecasting tourist routes to protected areas as an economically meaningful instrument for governing visitors’ spatial behaviour. The relevance of the study stems from the fact that the recovery and expansion of tourism mobility amplify the risk of localised congestion on trails, access nodes and viewing points, while ecological fragility and limited carrying capacity generate substantial external costs that remain largely invisible in individual travel choices. The purpose of the paper is to justify an analytical framework in which a route is treated as a sequence of choices on a network of zones and segments, and route-level flow forecasts are used to minimise expected social losses while preserving the recreational value of the destination. Methodologically, the study relies on integrating official tourism and conservation statistics with high-frequency digital traces from mobility data and outdoor tracking platforms, which makes it possible to anchor the overall scale of demand and, at the same time, refine the internal spatiotemporal allocation of visits. The results demonstrate that the main advantage of big data lies in moving from aggregate visitation forecasting to route-flow forecasting, thereby enabling management of concentration on a small subset of segments where marginal external costs rise nonlinearly. The paper offers an economic interpretation of forecasts through a welfare-loss function that aggregates ecological and service-related consequences of congestion, and through concentration indicators capturing the degree to which flows “lock in” on the most popular parts of the network. It is further argued that, without validation procedures and representativeness corrections, mobility and platform data may reproduce digital inequality as a misleading proxy for demand. The proposed approach makes it possible to treat a tourist route not merely as a spatial trajectory, but as an economically relevant object of management, taking into account capacity constraints and congestion externalities. The results can be applied by protected area authorities to substantiate preventive decisions aimed at redistributing visitor flows.
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