Effectiveness of Joint Liability Mechanism in Controlling Unsafe Behaviour of Coal Miners: A Stochastic Evolutionary Game Model

ABSTRACT

The joint liability mechanism is widely used to control unsafe behaviour of coal miners. However, existing research on its effectiveness remains controversial, partly because most studies regard the number of members subject to joint liability constraints as a fixed value and overlook the role of behavioural risk levels. This study addresses these gaps by constructing a stochastic evolutionary game model based on the Moran process to analyse coal miners' behavioural strategies under joint liability. The model calculates the fixation probabilities of “safe behaviour” and “unsafe behaviour” strategies in a finite population and derives the evolutionary equilibrium conditions under both weak selection and strong selection. The regulatory effects of static joint liability and dynamic joint liability on unsafe behaviour are discussed. Research shows that the application conditions of static joint liability are relatively stringent, and its effectiveness is affected by the risk level of unsafe behaviour and the number of coal miners. Increasing the number of coal miners subject to static joint liability is conducive to reducing high‐risk unsafe behaviour. However, for low‐risk unsafe behaviour, static joint liability is ineffective. In contrast, the application conditions of dynamic joint liability are more flexible, and its effectiveness is not affected by the risk level of unsafe behaviour and the number of coal miners, making it a useful supplement to static joint liability. Theoretically, this study introduces the Moran process into the field of coal miners' behaviour management and clarifies the boundary conditions under which joint liability is effective. Practically, static joint liability should be reserved for high‐risk unsafe behaviours in groups above the critical size, while dynamic joint liability should be adopted for low‐risk behaviours or groups below the critical size.