IDEAS home Printed from https://ideas.repec.org/a/eee/anture/v111y2025ics0160738325000386.html
   My bibliography  Save this article

Tourism combination forecasting with swarm intelligence

Author

Listed:
  • Li, Hengyun
  • Guo, Honggang
  • Wang, Jianzhou
  • Wang, Yong
  • Wu, Chunying

Abstract

Combination forecasting is an effective method for improving the accuracy of tourism demand. This study proposes an innovative combination strategy based on a multi-objective swarm intelligence optimization algorithm and, for the first time, examines whether and how this algorithm can enhance the performance of tourism demand combination forecasting. An empirical study conducted under several scenarios demonstrates that the proposed combination strategy enhances the interaction among single forecasts, leading to improved forecast accuracy and stability compared with traditional combination methods. The model remained effective even during the COVID-19 pandemic. The findings have a positive impact on predictive research, offering new insights and methodologies for tourism demand modeling.

Suggested Citation

  • Li, Hengyun & Guo, Honggang & Wang, Jianzhou & Wang, Yong & Wu, Chunying, 2025. "Tourism combination forecasting with swarm intelligence," Annals of Tourism Research, Elsevier, vol. 111(C).
    • Handle: RePEc:eee:anture:v:111:y:2025:i:c:s0160738325000386
    DOI: 10.1016/j.annals.2025.103932
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160738325000386
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.annals.2025.103932?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:anture:v:111:y:2025:i:c:s0160738325000386. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/annals-of-tourism-research/ .

    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.