Self-regulation and government regulation, community policing and external powerful forces, respectively, form vital part of today’s global economy and social management. The implementation of regulation from self-regulation or community policing requires considerable disciplined members to share the costs of execution, while government or external powerful forces are more likely to make an strong intervention as the industry or community is being widely eroded, which are thus two definitely different feedback regulation schemes. Together with those wrong-doers, the organizations of the two feedback regulation schemes consist of both first-order and novel second-order social dilemma. It still remains a significant challenge to identify an optimal structure to simultaneously alleviate the two dilemmas, and even to additionally favor the altruistic individuals. To address this issue, in this paper we adopt an evolutionary game model within the framework of the public good model, by considering defector-driven and cooperator-driven punishment to map the two feedback regulation schemes, respectively. Through a series of extensive Monte Carlo simulation experiments and mean-field analysis based on replicator dynamics, we finally uncover the combination of clustering and shortcuts, say the small-world structure, is required to largely alleviate both first-order and novel second-order dilemma, which can not only yield optimal public goods by successfully eliminating defectors through strong network reciprocity from dense local connections, but also provide sufficient shortcuts to promote the dominance of defector-driven punishers. Our findings can be beneficial for improving self-regulation or community policing systems by constructing novel monitoring networks.

自我监管和政府监管、社区警务和外部强大力量分别构成当今全球经济和社会管理的重要组成部分。自我监管或社区警务的监管实施需要相当多的纪律严明的成员来分担执行成本，而政府或外部强大力量更有可能在行业或社区受到广泛侵蚀的情况下进行强力干​​预，因此这是两个肯定不同的反馈调节方案。与这些不法分子一起，这两种反馈调节方案的组织既包含一阶社会困境，也包含新的二阶社会困境。确定一个最佳结构以同时缓解这两个困境仍然是一个重大挑战，甚至还偏爱无私的人。为了解决这个问题，在本文中，我们在公益模型的框架内采用进化博弈模型，分别考虑背叛者驱动和合作者驱动的惩罚来映射两种反馈调节方案。通过一系列广泛的蒙特卡罗模拟实验和基于复制器动力学的平均场分析，我们最终揭示了聚类和捷径的组合，比如小世界结构，是在很大程度上缓解一阶和新的二阶结构所必需的困境，它不仅可以通过密集的本地连接通过强大的网络互惠成功地消除叛逃者来产生最优的公共产品，而且还提供了足够的捷径来促进叛逃者驱动的惩罚者的主导地位。