Agent-Based Model Applied for the Study of Overtourism in an Urban Context

This research aims to analyze the spatial and temporal distribution of residents and tourists in an urban context, assessing the risk of overtourism. To achieve this, a tourist city is conceptualized as a complex system and examined through an agent-based model (ABM), which simulates the interactions between heterogeneous agents and their environment. This computational approach enables the exploration of emergent spatial-temporal patterns and facilitates the interpretation of overtourism as a real-world experiment. The case study focuses on Santa Marta (Colombia), a well-established coastal destination currently facing potential entry into a phase of tourism decline if management remains reactive. Simulation results reveal a high risk of overtourism and illustrate the differentiated effects of two plausible management strategies at distinct spatial scales. Additionally, this study proposes a tourism intensity indicator, addressing the problem of overestimating tourism pressure in existing metrics. The proposed model offers a valuable decision-support tool for assessing impacts and designing proactive management measures in destinations experiencing rapid tourist growth across multiple spatial and temporal dimensions.