煤矿安全隐患监管策略演化与动态惩罚机制研究

The evolution of supervision strategies on coal mine safety hazards and dynamic penalty

  • 摘要: 为研究动态惩罚机制下煤矿企业面对不同监管措施时的行为策略,将前景理论与演化博弈相结合,构建了地方政府与煤矿企业之间的演化博弈模型。在讨论静态惩罚机制和动态惩罚机制下系统的演化稳定策略基础上,通过数值仿真分析了不同参数变化对博弈双方的演化轨迹的影响。结果显示,动态惩罚机制可以抑制静态惩罚机制中的博弈双方策略选择的波动性;在动态惩罚机制下,过度增大监管频率和惩罚额度的上限值会增大双方博弈的时间,不利于提高监管效率;监管频率与惩罚额度上限值的合理取值范围,受事故损失成本、隐患整改成本、政府和企业的感知收益以及政府监管部门的监管成本的影响。

     

    Abstract: This study constructed an evolutionary game model between local government and coal mining enterprises by combining prospect theory and evolutionary game to study the behavioral strategies of coal mining enterprises facing different regulatory measures under the dynamic penalty mechanism. We discussed the evolutionary stabilization strategies of the system under the static and dynamic penalty mechanism. Numerical simulation was conducted to analyze the effects of different parameter variations on the evolutionary trajectories of the two sides of the game. Results show that the dynamic penalty mechanism can inhibit the volatility of the strategy choices of both sides of the game in the static penalty mechanism. Under the dynamic penalty mechanism, over-increasing the upper limit of the regulatory frequency and penalty amount increases the time of the game between the two sides—not conducive to improving regulatory efficiency. A reasonable range of values is influenced by the loss cost of accidents, the rectification cost of hidden dangers, the perceived benefits of government and enterprises, and the regulatory cost of government regulators.

     

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