IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i7p3248-d1628665.html
   My bibliography  Save this article

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

Author

Listed:
  • Janwar Moreno

    (Department of Economic, Universidad de Pamplona, Pamplona 543050, Colombia)

  • Jairo Parada

    (Department of Economics, Universidad del Norte, Puerto Colombia 081007, Colombia)

  • David Daniel Peña-Miranda

    (Faculty of Business and Economic Sciences, Universidad del Magdalena, Santa Marta 470004, Colombia)

Abstract

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.

Suggested Citation

  • Janwar Moreno & Jairo Parada & David Daniel Peña-Miranda, 2025. "Agent-Based Model Applied for the Study of Overtourism in an Urban Context," Sustainability, MDPI, vol. 17(7), pages 1-26, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3248-:d:1628665
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/7/3248/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/7/3248/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3248-:d:1628665. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.