IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v678y2025ics0378437125006077.html
   My bibliography  Save this article

Modeling spatial public goods games with differentiated strategies and asymmetric payoff allocation

Author

Listed:
  • Wang, Xiaonan
  • Lu, Gang
  • Guo, Peng

Abstract

Social dilemmas often arise in multiplayer settings where individuals must balance personal interests against collective gains. The public goods game (PGG), a canonical model for studying such dilemmas, typically assumes homogeneous strategies and uniform payoff allocation, oversimplifying real-world cooperative behavior. This study introduces a spatial PGG model on lattice networks that incorporates differentiated strategies, where individuals adopt distinct strategies toward different neighbors, and asymmetric payoff allocation mechanisms. Players are categorized as pure cooperators, pure defectors, or mixed strategy players, and payoffs are distributed unevenly based on strategic differentiation. Through extensive simulations, we analyze how these features influence cooperation dynamics. Results show that differentiated strategies significantly lower the threshold for cooperation to emerge, particularly when combined with asymmetric investment. Even under low enhancement factors, such differentiation fosters earlier and more widespread cooperative behavior. Asymmetric payoff allocation amplifies this effect by incentivizing cooperation and accelerating the decline of defection. Mixed strategy players act as transitional agents, smoothing the shift from defection to stable cooperation through adaptive payoff responses. Further robustness checks from the perspectives of network size, network structure, and initial cooperation rate confirm the robustness of these dynamics, thereby highlighting the general applicability of the model. These findings offer valuable insights for designing more effective cooperation-promoting policies and incentive structures in complex social systems.

Suggested Citation

  • Wang, Xiaonan & Lu, Gang & Guo, Peng, 2025. "Modeling spatial public goods games with differentiated strategies and asymmetric payoff allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 678(C).
  • Handle: RePEc:eee:phsmap:v:678:y:2025:i:c:s0378437125006077
    DOI: 10.1016/j.physa.2025.130955
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125006077
    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.2025.130955?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:678:y:2025:i:c:s0378437125006077. 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.