TY - JOUR
T1 - Investment in enhancing resilience safety of chemical parks under blockchain technology
T2 - From the perspective of dynamic reward and punishment mechanisms
AU - Su, Chang
AU - Deng, Jun
AU - Li, Xiaoyang
AU - Huang, Wenhong
AU - MA, jiayi
AU - Wang, Caiping
AU - Wang, Xinping
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2025/4
Y1 - 2025/4
N2 - Industry and academia have long focused on safety risk management in chemical parks, and resilient safety is becoming a new goal for risk and emergency management in parks. In the context of blockchain, what is the behavioral law of chemical enterprises investing for resilient safety is a scientific question that needs to be studied urgently. This paper effectively combines prospect theory, mental account and evolutionary game theory, considers the herd effect, establishes a hypothetical model of limited rationality of chemical park resilience safety investment actors (core enterprises, supporting enterprises and local government regulators), analyzes the evolutionary stabilization strategies of the core enterprises, supporting enterprises and local government regulators under the static and dynamic rewards and punishments mechanisms, and finally, further conducts a Finally, numerical simulation analysis is further carried out. The results show that (1) the resilient safety investment of chemical park enterprises is jointly influenced by multiple factors, including external incentives and subjective factors of decision makers. (2) The government's dynamic reward and punishment mechanism can more effectively incentivize enterprises to invest in resilience safety. (3) Reducing the psychological pressure among supporting enterprises and reducing the influence of herd effect can push the system to tend to the state of positive investment. The marginal contribution of this paper is to reveal the evolution law of chemical park resilience safety investment behavior under blockchain technology. The findings provide empirical evidence for promoting resilient safety investment in chemical parks and enhancing the level of resilient safety in the parks.
AB - Industry and academia have long focused on safety risk management in chemical parks, and resilient safety is becoming a new goal for risk and emergency management in parks. In the context of blockchain, what is the behavioral law of chemical enterprises investing for resilient safety is a scientific question that needs to be studied urgently. This paper effectively combines prospect theory, mental account and evolutionary game theory, considers the herd effect, establishes a hypothetical model of limited rationality of chemical park resilience safety investment actors (core enterprises, supporting enterprises and local government regulators), analyzes the evolutionary stabilization strategies of the core enterprises, supporting enterprises and local government regulators under the static and dynamic rewards and punishments mechanisms, and finally, further conducts a Finally, numerical simulation analysis is further carried out. The results show that (1) the resilient safety investment of chemical park enterprises is jointly influenced by multiple factors, including external incentives and subjective factors of decision makers. (2) The government's dynamic reward and punishment mechanism can more effectively incentivize enterprises to invest in resilience safety. (3) Reducing the psychological pressure among supporting enterprises and reducing the influence of herd effect can push the system to tend to the state of positive investment. The marginal contribution of this paper is to reveal the evolution law of chemical park resilience safety investment behavior under blockchain technology. The findings provide empirical evidence for promoting resilient safety investment in chemical parks and enhancing the level of resilient safety in the parks.
KW - Blockchain technology
KW - Chemical parks
KW - Evolutionary gaming
KW - Resilient safety investments
UR - https://www.scopus.com/pages/publications/85211317502
U2 - 10.1016/j.jlp.2024.105523
DO - 10.1016/j.jlp.2024.105523
M3 - 文章
AN - SCOPUS:85211317502
SN - 0950-4230
VL - 94
JO - Journal of Loss Prevention in the Process Industries
JF - Journal of Loss Prevention in the Process Industries
M1 - 105523
ER -