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N-player repeated evolutionary trust game under government management

Author

Listed:
  • Liu, Yuyuan
  • Liu, Linjie
  • Guo, Ruqiang
  • Zhang, Liang

Abstract

Trust game is a common framework for studying trust behavior between unrelated individuals. Previous theoretical research has found that network structure or reputation can promote trust and cooperation, but these studies often assume that interactions between players are one-time and investors have no choice but to invest, which is inconsistent with reality. Here we introduce the conditional investment strategy and government management into a repeated N-player trust game, where investors can make investment decisions based on the investment environment and the government plays the role of a regulator. We consider a reporting mechanism to allow investors to report untrustworthy trustees, thereby the government punishes reported untrustworthy trustees and rewards investors who successfully report untrustworthy trustees. We find that the introduction of the conditional investment strategy and incentives can prompt the evolution of trust. Besides, we reveal that as punishment intensity increases, not only can trust emerge but investment behavior can also be maintained. Furthermore, we verify the above theoretical results by numerical simulations.

Suggested Citation

  • Liu, Yuyuan & Liu, Linjie & Guo, Ruqiang & Zhang, Liang, 2023. "N-player repeated evolutionary trust game under government management," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923009323
    DOI: 10.1016/j.chaos.2023.114031
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    References listed on IDEAS

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    8. Sun, Ketian & Liu, Yang & Chen, Xiaojie & Szolnoki, Attila, 2022. "Evolution of trust in a hierarchical population with punishing investors," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
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    Cited by:

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