中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (5): 23-31.doi: 10.16265/j.cnki.issn1003-3033.2024.05.0301

• 安全社会科学与安全管理 • 上一篇    下一篇

动态惩罚机制下民航危险品运输演化博弈分析:以航空公司与地面服务代理人为例

沈海滨(), 胡玲, 李娜, 张文怡, 谢润琪   

  1. 中国民航大学 安全科学与工程学院 天津 300399
  • 收稿日期:2025-01-12 修回日期:2025-03-20 出版日期:2025-05-28
  • 作者简介:

    沈海滨 (1978—),男,黑龙江双鸭山人,硕士,副教授,主要从事民航危险品运输、民航安保等方面的研究。E-mail:

    沈海滨, 副教授

  • 基金资助:
    中央高校基本科研业务费项目中国民航大学专项(3122022037)

Evolutionary game analysis of dangerous goods transportation in civil aviation under dynamic penalty mechanism: case of airline and ground service agents

SHEN Haibin(), HU Ling, LI Na, ZHANG Wenyi, XIE Runqi   

  1. School of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Received:2025-01-12 Revised:2025-03-20 Published:2025-05-28

摘要: 为解决民航危险品运输地面代理服务中地面服务代理人的违规行为、航空公司疏于监督管理等问题,首先,分别在航空公司采取静态惩罚及动态惩罚机制下构建危险品运输航空公司与地面服务代理人的演化博弈模型;其次,探究博弈双方在不同机制下的演化稳定策略;然后,结合系统动力学模型,构建航空公司与地面服务代理人的定量分析模型;最后,模拟分析重要参数对博弈双方行为策略的影响。结果表明:静态惩罚机制下博弈系统无稳定点,双方无演化稳定策略,且双方的行为策略随时间呈现周期性反复趋势;引入动态惩罚机制后,博弈系统存在稳定点,双方的行为策略能够收敛到稳定的焦点;相较于低惩罚力度,较高的惩罚力度更能提高地面服务代理人严格执行代理协议的概率。

关键词: 动态惩罚机制, 危险品运输, 演化博弈, 航空公司, 地面服务代理人, 系统动力学

Abstract:

In addressing the issues of non-compliance by ground service agents and lax supervision by airlines in the transportation of hazardous materials in civil aviation. Firstly, evolutionary game models between airlines and ground service agents were constructed under both static and dynamic punishment mechanisms. The evolutionary stable strategies under different mechanisms were then explored. Subsequently, a quantitative analysis model was developed by integrating system dynamics to further analyze the interactions between the two parties. Finally, simulations were conducted to analyze the impact of key parameters on the behavioral strategies of both sides. The results reveal that under the static punishment mechanism, no stable equilibrium point is observed in the game system. No evolutionary stable strategy is formed, with the behavioral strategies of both parties showing periodic fluctuations over time. In contrast, when a dynamic punishment mechanism is introduced, a stable equilibrium point emerged in the game system. The behavioral strategies of both parties converge to a stable focal point. Moreover, compared with a low level of punishment, a higher level of punishment is found to be more effective in increasing the probability that ground service agents strictly comply with the agency agreement.

Key words: dynamic penalty mechanism, dangerous goods transportation, evolutionary game, airlines, ground service agents, system dynamics

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