IDEAS home Printed from https://ideas.repec.org/a/sae/toueco/v31y2025i4p803-810.html
   My bibliography  Save this article

Optimizing control variable selection with algorithms: Parsimony and precision in regression analysis

Author

Listed:
  • Fernando Campayo-Sanchez
  • Juan Luis Nicolau

Abstract

This research note explores the pivotal role of control variables in any tourism and hospitality research that utilizes regression models in statistical analyses. While theory-driven independent variables offer insight into expected effects, the inclusion of control variables is crucial for mitigating potential confounding factors. In an attempt to strike a balance between model complexity and parsimony, researchers face the challenge of selecting the optimal control variables. To address this issue, the study tests three alternative methods: genetic algorithms, lasso models, and the branch and bound algorithm. Despite their underutilization in tourism research, these methods offer efficient means of selecting control variables, enhancing model precision and interpretation without unnecessarily convoluting the model with irrelevant factors.

Suggested Citation

  • Fernando Campayo-Sanchez & Juan Luis Nicolau, 2025. "Optimizing control variable selection with algorithms: Parsimony and precision in regression analysis," Tourism Economics, , vol. 31(4), pages 803-810, June.
    • Handle: RePEc:sae:toueco:v:31:y:2025:i:4:p:803-810
    DOI: 10.1177/13548166241287953
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/13548166241287953
    Download Restriction: no
    File URL: https://libkey.io/10.1177/13548166241287953?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
    ---><---

    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:sae:toueco:v:31:y:2025:i:4:p:803-810. 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: SAGE Publications (email available below). General contact details of provider: .

    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.