The Dynamic Evolution Law of Coal Mine Workers’ Behavior Risk Based on Game Theory

Abstract

In the safety production system of coal mining enterprises, the income of workers affects the evolution of group behavior and then affects risky behaviors. Due to the nonlinearity and chaos of group behavior, its evolution is long and complex. This study investigated the dynamic evolution process of coal miners’ group behavior to explore the law of group safety behavior and effectively promoted the safety of group behavior. First, a questionnaire survey was conducted on the influencing factors of coal mine workers’ group safety behavior. Then, based on the results of the questionnaire, the coefficients of the influencing factors were obtained, and the game model was established. Finally, the game income was simulated and analyzed. The results showed that the income of workers was positively correlated with the safety of group behavior. Safety performance could effectively improve the level of group safety behavior. The safety management system of coal mining enterprises was further improved and expanded and was applied. The statistical analysis of the violations showed that the results of this study could be used to influence the risky group behavior of coal mine workers and improve the level of coal mine safety production.

Risk Assessment of Insider Threats Based on IHFACS-BN

“…Effective accident prevention requires incorporating HFs into accident analysis models [25,26]. This study uses the HFACS model [27], which Shapell and Wiegmann developed to study HFs in accidents based on the Swiss cheese model by analyzing a large amount of aviation accident data.…”

A Three-Party Decision Evolution Game Analysis of Coal Companies and Miners under China’s Government Safety Special Rectification Action

“…Elevating safety investment not only empowers miners to utilize safer mining techniques and equipment, but also facilitates the refinement of management systems within the mining industry. This includes establishing suitable incentive and penalty mechanisms and augmenting miners' safety awareness education, all contributing to the mitigation of coal mine accidents [21][22][23]. Wang et al combined DEMATEL and ISM to establish a hierarchical model for analyzing the factors and mechanisms affecting mine safety.…”

“…Scholarly research underscores that miners' unsafe behavior significantly contributes to the ongoing high incidence of coal mine accidents. To tackle this issue, it is crucial to institute tailored incentive and penalty mechanisms while simultaneously strengthening safety education initiatives [12,23,27]. Analyzing data on Chinese coal mine accidents over the past decade, human factors account for 94% of the causes of coal mine accidents, with intentional violations and poor management being the primary reasons [28,29].…”

“…Lu and others constructed an evolutionary game model within the miner community, considering the influence of managers as an external factor. The results indicated a positive correlation between workers' income and the safety of group behavior, with safety performance effectively enhancing the level of group safety behavior [23]. As the study of evolutionary game theory in the safety field continues to advance, some scholars have introduced system dynamics into the analysis of coal mine safety's evolutionary game, aiding in the analysis of complex dynamic structures [46,47].…”

Intelligent Safety Risk Analysis and Decision-Making System for Underground Metal Mines Based on Big Data

“…As a valuable asset accumulated by mines in the process of dealing with actual safety risks, the use of intelligent analysis tools to fully explore the information of the laws implied in safety production data and realize the in-depth utilization of safety data assets has become an effective means to strengthen the pertinence and scientificity of safety management and control. Current research on the in-depth utilization of safety production data mainly focuses on safety status assessment and prediction [8][9][10][11][12][13][14], safety risk identification and analysis [15][16][17][18], and safety risk pre-control [19][20][21]. Wu et al [22] established a mine safety supervision capability evaluation index system consisting of a target layer, a criterion layer, and a sub-criterion layer, and identified effective measures that could improve the efficiency of safety supervision by determining the weights of each index and combining the accident causation 2-4 model.…”