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Evolutionary dynamics of public goods game with tax-based rewarding cooperators

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  • Shen, Yong
  • Lei, Wei
  • Kang, Hongwei
  • Li, Mingyuan
  • Sun, Xingping
  • Chen, Qingyi

Abstract

In public goods games, rewards have been demonstrated as an effective mechanism for sustaining cooperation among individuals. Rewarding cooperators are willing to incur personal costs to incentivize cooperative behavior. However, pure cooperators become second-order free-riders because they are not willing to bear these additional costs. To address this issue and ensure the effectiveness of the reward strategy, we propose the introduction of a tax mechanism. We examine the performance of strong altruistic rewarding cooperators and weak altruistic rewarding cooperators separately, with the support of the tax mechanism. Through theoretical analysis and numerical calculations, our study reveals that tax-based rewarding cooperators possess an evolutionary advantage in maintaining cooperation. In addition, we found that strong altruistic rewarding cooperators were more effective than weak altruistic rewarding cooperators in solving the second-order free-riders problem. Our findings contribute to the understanding of cooperative behavior in public goods games and provide insights into the design of mechanisms that promote sustained cooperation. The introduction of a tax mechanism in combination with strong altruistic reward strategies can offer an effective solution to the second-order free-riders problem.

Suggested Citation

  • Shen, Yong & Lei, Wei & Kang, Hongwei & Li, Mingyuan & Sun, Xingping & Chen, Qingyi, 2023. "Evolutionary dynamics of public goods game with tax-based rewarding cooperators," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
  • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923009311
    DOI: 10.1016/j.chaos.2023.114030
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    References listed on IDEAS

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    1. Li, MingYuan & Kang, HongWei & Sun, XingPing & Shen, Yong & Chen, QingYi, 2022. "Replicator dynamics of public goods game with tax-based punishment," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    2. Dominic D. P. Johnson & Pavel Stopka & Stephen Knights, 2003. "The puzzle of human cooperation," Nature, Nature, vol. 421(6926), pages 911-912, February.
    3. Wang, Mie & Kang, HongWei & Shen, Yong & Sun, XingPing & Chen, QingYi, 2021. "The role of alliance cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. Yang, Luhe & Zhang, Lianzhong, 2021. "Environmental feedback in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. Sun, Xingping & Li, Mingyuan & Kang, Hongwei & Shen, Yong & Chen, Qingyi, 2023. "Combined effect of pure punishment and reward in the public goods game," Applied Mathematics and Computation, Elsevier, vol. 445(C).
    7. Ernst Fehr & Simon Gächter, 2003. "The puzzle of human cooperation," Nature, Nature, vol. 421(6926), pages 912-912, February.
    8. Wang, Shengxian & Chen, Xiaojie & Xiao, Zhilong & Szolnoki, Attila, 2022. "Decentralized incentives for general well-being in networked public goods game," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    9. Lee, Hsuan-Wei & Cleveland, Colin & Szolnoki, Attila, 2022. "Mercenary punishment in structured populations," Applied Mathematics and Computation, Elsevier, vol. 417(C).
    10. Cheng-Yi Xia & Sandro Meloni & Yamir Moreno, 2012. "Effects Of Environment Knowledge On Agglomeration And Cooperation In Spatial Public Goods Games," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-17.
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