IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v676y2025ics0378437125004984.html
   My bibliography  Save this article

Incentive control of eco-evolutionary dynamics with environmental feedback

Author

Listed:
  • Zhong, Yi
  • Wang, Kaihong
  • Zeng, Siyuan
  • Ding, Chuan

Abstract

In this study, we incorporate an adaptive hybrid incentive strategy (AHIS) into an eco-evolutionary game model, if the density of cooperators surpasses the threshold, cooperators are rewarded; conversely, defectors are punished. We analyze the resulting piecewise-smooth continuous system and determine the optimal strategy switching threshold. Then, we identify a non-smooth Hopf bifurcation induced by policy switching and establish the stability and uniqueness of the resulting limit cycle. Through numerical simulations, we compare the effects of several incentive controls. The results demonstrate that AHIS, compared to pure incentive strategies, enables the establishment and maintenance of full cooperation under a broader set of conditions. Furthermore, implementing incentive policies with a higher switching threshold and avoiding frequent changes can improve outcomes. Our results provide a novel theoretical framework for addressing the tragedy of the commons and offer insights into designing effective incentive mechanisms in social and ecological systems.

Suggested Citation

  • Zhong, Yi & Wang, Kaihong & Zeng, Siyuan & Ding, Chuan, 2025. "Incentive control of eco-evolutionary dynamics with environmental feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 676(C).
  • Handle: RePEc:eee:phsmap:v:676:y:2025:i:c:s0378437125004984
    DOI: 10.1016/j.physa.2025.130846
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125004984
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2025.130846?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:phsmap:v:676:y:2025:i:c:s0378437125004984. 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/physica-a-statistical-mechpplications/ .

    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.