Predictive Modelling for Sustainable Pilgrim Flow Management on the Camino de Santiago

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When destinations are in a growth or maturity phase, two simultaneous debates usually arise: is there overtourism? and ‑if it exists ‑ does it have negative consequences? The literature has been concerned with providing scientific answers to these questions analysing cases of urban and sun and sand destinations. The differential elements of rural destinations in relation to this topic have usually been neglected. This study presents a prediction instrument built specifically for a growing destination located ‑ almost entirely ‑ in a rural environment: El Camino de Santiago. Based on the information collected over the last 20 years by the Pilgrim’s Welcome Office receiving more than 4 million pilgrims, this instrument is aimed at predicting the number of pilgrims who will pass through a series of hotspots ‑employing Seasonal Autoregressive Integrated Moving Average (SARIMA), and Trigonometric seasonality, Box ‑Cox transformation, ARMA errors, Trend and Seasonal Components (TBATS) models ‑ to help control management of pilgrim flows and thus counteract the possible negative consequences of overtourism, optimising the experience for tourists, business owners, and residents of the hotspots.