Research on the Game Strategy of Mutual Safety Risk Prevention and Control of Industrial Park Enterprises under Blockchain Technology

IF 2.3 4区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Systems Pub Date : 2024-09-06 DOI:10.3390/systems12090351
Chang Su, Jun Deng, Xiaoyang Li, Fangming Cheng, Wenhong Huang, Caiping Wang, Wangbo He, Xinping Wang
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Abstract

Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain.
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区块链技术下园区企业安全风险互控博弈策略研究
工业园区企业安全风险系统化管理已成为热门话题。而风险防控互助是园区风险应急管理的一种全新模式。在区块链背景下,如何激励企业积极投入安全风险防控互助,成为政府监管部门面临的一系列关键问题。本文创新性地将前景理论、心智核算和演化博弈理论相结合,为安全风险防控互助中的关键利益相关者(核心企业、配套企业和政府监管部门)的行为创建了有限理性的假设模型。在静态奖惩机制和动态惩罚机制下,分析了利益相关者的演化稳定策略,并通过实例进行了数值模拟分析。结果表明:(1)园区企业间的风险防控互助受多种因素影响,包括外部因素和主观因素,并通过复杂的演化路径(如参考点、价值认知等)进行演化。(二)针对静态机制的弊端,政府部门越来越多地实施动态奖惩措施。政府部门应动态调整奖惩策略,明确确定奖惩的最高标准,各种奖惩措施相结合,可以显著提高安全风险防控互助投资决策的有效性。(三)不断优化奖惩机制设计、将区块链技术与激励企业参与的管理策略相结合、发挥参与者反馈作用等策略和建议,为促进企业积极投资安全风险防控互助提供了新的启示。本文的边际贡献在于揭示了区块链背景下化工园区企业安全风险互助防控行为的演化规律。
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来源期刊
Systems
Systems Decision Sciences-Information Systems and Management
CiteScore
2.80
自引率
15.80%
发文量
204
审稿时长
11 weeks
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