Evolution of trust in N-player trust games with loss assessment.

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED Chaos Pub Date : 2024-09-01 DOI:10.1063/5.0228886
Yuyuan Liu, Lichen Wang, Ruqiang Guo, Shijia Hua, Linjie Liu, Liang Zhang
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引用次数: 0

Abstract

Trust plays a crucial role in social and economic interactions, serving as the foundation for social stability and human cooperation. Previous studies have explored the evolution of trust between investors and trustees by constructing trust game models, incorporating factors such as network structure, reputation, and incentives. However, these studies often assume that investors consistently maintain their investment behavior, neglecting the potential influence of the investment environment on investment behavior. To address this gap, we introduce a loss assessment mechanism and construct a trust game model. Specifically, investors first allocate their investment amount to an assessment agency, which divides the amount into two parts according to a certain allocation ratio. One part is used for investment assessment, and the results are fed back to the investors. If the payoff from this portion exceeds the investors' expected value, the remaining amount is invested; otherwise, it is returned to the investors. The results indicate that investors with moderate expectations are more likely to form alliances with trustworthy trustees, thereby effectively promoting the evolution of trust. Conversely, lower or higher expectations yield opposite results. Additionally, we find that as investors' expected values increase, the corresponding allocation ratio should also increase to achieve higher payoffs.

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有损失评估的 N 人信任博弈中的信任演变。
信任在社会和经济互动中发挥着至关重要的作用,是社会稳定和人类合作的基础。以往的研究通过构建信任博弈模型,结合网络结构、声誉和激励机制等因素,探讨了投资者与受托人之间信任的演变。然而,这些研究往往假定投资者始终保持其投资行为,而忽视了投资环境对投资行为的潜在影响。为了弥补这一不足,我们引入了损失评估机制,并构建了一个信任博弈模型。具体来说,投资者首先将投资金额分配给评估机构,评估机构按照一定的分配比例将投资金额分成两部分。其中一部分用于投资评估,评估结果反馈给投资者。如果这部分的回报超过了投资者的预期值,剩余的金额将用于投资;反之,则返还给投资者。结果表明,预期值适中的投资者更有可能与值得信赖的受托人结成联盟,从而有效促进信任的发展。相反,较低或较高的预期则会产生相反的结果。此外,我们还发现,随着投资者预期值的增加,相应的分配比例也应增加,以获得更高的回报。
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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
期刊最新文献
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