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首页> 外文期刊>Computational Social Systems, IEEE Transactions on >Accessing the Role of Trust Profiles for the Economic Growth of Societies: A Stochastic Rule-Based Simulation Using the Prisoner’s Dilemma Game
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Accessing the Role of Trust Profiles for the Economic Growth of Societies: A Stochastic Rule-Based Simulation Using the Prisoner’s Dilemma Game

机译:访问信托概况的作用,以便使用囚犯困境游戏的随机规则的模拟

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摘要

According to Robert Putnam, trust can be a proxy for social capital. Thus, a higher societal trust could be related to economic growth. To test this hypothesis, we simulated the association between trust and economic growth in two artificial societies. One artificial society (New Zealand) exhibited higher levels of initial trust, and the other (Argentina) had lower levels of trust. Initial starting points for simulations were set using representative survey data (using the global trust inventory). Computational simulation relied on a rule-based model (RBM), integrating time through a stochastic simulation algorithm implemented in PISKaS. Agents in the artificial societies were distributed according to proportions of four trust profiles, with more high trusters (HTs) in New Zealand. In each iteration, the agents played a prisoner's dilemma, earning or losing money according to different payoff matrices, cooperation probabilities, and interaction frequencies, modeling different conditions for economic exchange. We analyzed the economic performance of each country, together with the performance of each trust profile. Results support the notion that societies with high trust perform economically better, on average, than those with low trust, but only if interaction frequency is held constant. Despite the relevance of HTs for economic development, their performance is tightly linked to the type of society in which they interact: they prosper more in a Rule of Law society, and where HTs are more common, compared with a predators' paradise, where the sucker's payoff is more punitive.
机译:根据Robert Putnam的说法,信任可以成为社会资本的代理。因此,更高的社会信任可能与经济增长有关。为了测试这一假设,我们模拟了两种人工社会的信任和经济增长之间的关联。一个人工社会(新西兰)呈现出更高层次的初始信任,另一个(阿根廷)的信任程度较低。使用代表性调查数据(使用全局信任库存)设置初始启动点。基于规则的模型(RBM),计算模拟依赖于基于规则的模型(RBM),通过PIESSAS中实现的随机仿真算法集成时间。人工社会中的代理根据四个信托档案的比例分发,新西兰的高度克拉斯人(HTS)。在每次迭代中,代理商根据不同的回报矩阵,合作概率和相互作用频率,为不同的经济交换条件展示了囚犯的困境,赚钱或减少了金钱。我们分析了每个国家的经济表现,以及每个信托概况的表现。结果支持高度信任的社会的概念,平均而言,平均而言,只有具有低信任的人,而且只有相互作用频率保持不变。尽管HTS对经济发展的相关性,但它们的表现与他们互动的社会类型紧密相关:他们在法治社会中繁荣昌盛,而HTS比捕食者的天堂相比,HTS更常见吸盘的回报更加惩罚。

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