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A stochastic catastrophe model of construction site safety hazards supervision and its resilience

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  • Guo, Wenqiang
  • Liang, Yunze
  • Lei, Ming
  • Cai, Dongliang
  • Wu, Xinwei

Abstract

Construction site safety hazards supervision (CSSHS) is directly related to the life safety of construction personnel and the social reputation of enterprises. This paper discusses the nonlinear evolution processes and resilience measure of CSSHS. First, evolutionary game theory is applied to establish replicator dynamic equations for construction enterprises and government departments. On this basis, white Gaussian noise and Itoˆ stochastic differential equations are introduced to construct its stochastic dynamical system. Second, we use limit probability density functions to transform the game model into stochastic catastrophe model and introduce resilience indicator to quantitatively characterize the system’s capacity to absorb disturbances. Finally, through simulation experiments, we further analyze the impact of relevant parameter variations on the system’s nonlinear evolution and resilience. The results show that: (1) the self-organized phase transition generated by the combination of variables in the bifurcation point set induces a structural catastrophe in the selection of a strategy by regulatory entities; (2) the change in resilience of CSSHS system corresponds to the occurrence of a structural catastrophe in the system state; (3) beyond certain thresholds, supervision frequency and pecuniary penalty have positive effects on the resilience of CSSHS system; (4) the probability of potential safety incidents negatively influences the resilience of CSSHS system, fostering a “gambling” mentality among regulatory entities, particularly when lower probabilities of incident occurrences are predicted.

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  • Guo, Wenqiang & Liang, Yunze & Lei, Ming & Cai, Dongliang & Wu, Xinwei, 2024. "A stochastic catastrophe model of construction site safety hazards supervision and its resilience," Energy, Elsevier, vol. 300(C).
    • Handle: RePEc:eee:energy:v:300:y:2024:i:c:s0360544224012416
    DOI: 10.1016/j.energy.2024.131468
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