Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

Abstract

The unsafe behavior of miners seriously affects the safety of deep mining. A comprehensive evaluation of miners’ unsafe behavior in deep coal mines can prevent coal mine accidents. This study combines HFACS-CM, SEM, and SD models to evaluate miners’ unsafe behaviors in deep coal mining. First, the HFACS-CM model identifies the risk factors affecting miners’ unsafe behavior in deep coal mines. Second, SEM was used to analyze the interaction between risk factors and miners’ unsafe behavior. Finally, the SD model was used to simulate the sensitivity of each risk factor to miners’ unsafe behavior to explore the best prevention and control strategies for unsafe behavior. The results showed that (1) environmental factors, organizational influence, unsafe supervision, and unsafe state of miners are the four main risk factors affecting the unsafe behavior of miners in deep coal mines. Among them, the unsafe state of miners is the most critical risk factor. (2) Environmental factors, organizational influence, unsafe supervision, and the unsafe state of miners have both direct and indirect impacts on unsafe behaviors, and their immediate effects are far more significant than their indirect influence. (3) Environmental factors, organizational influence, and unsafe supervision positively impact miners’ unsafe behavior through the mediating effect of miners’ unsafe states. (4) Mental state, physiological state, business abilities, resource management, and organizational climate were the top five risk factors affecting miners’ unsafe behaviors. Taking measures to improve the adverse environmental factors, strengthening the organization’s supervision and management, and improving the unsafe state of miners can effectively reduce the risk of miners’ unsafe behavior in deep coal mines. This study provides a new idea and method for preventing and controlling the unsafe behavior of miners in deep coal mines.

Human factors analysis of coal mine gas accidents based on improved HFACS model

“…On the other hand, the precondition for unsafe behavior exhibits the lowest central value in terms of accident handling, indicating a relatively weaker influence. This is attributed to the fact that if the workplace adopts highly efficient technological and engineering control measures to mitigate the risk of gas leakage or explosions, the impact of employees' unsafe behavior may be comparatively reduced (Yang, Wang, Zhu, Sun, et al, 2022). These measures may encompass intelligent systems, gas detection equipment, risk assessments, and isolation measures, among others.…”

“…In recent years, the HFACS model has gradually found its way into the analysis of coal mine accidents. Yang, Wang, Zhu, Sun, et al (2022), drawing inspiration from the tenets of grounded theory, encoded the collected data and employed the HFACS model to comprehensively identify the perilous factors affecting the unsafe behaviors of coal miners. Zhao et al (2014), focusing on the most prevalent gas accidents, consulted the HFACS framework and analyzed the underlying reasons for 100 typical coal mine gas accidents in the past decade using SPSS 13.0.…”

Game analysis of enterprise safety investment and employee safety behavior strategy evolution in high-risk industries

“…Tian et al [ 17 ] made a quantitative analysis of unsafe behaviors of miners based on the grey theory, and concluded that unsafe behaviors violating labor discipline have the highest risk value, which is an important direction to improve the safety production of coal mines. In addition, Yang et al [ 18 ] analyzed the unsafe behaviors of deep mining miners through the comprehensive use of HFACS-CM, SD, SEM mathematical methods, and found that the physiological state, psychological state, business ability, resource management, and organizational climate are the five major factors affecting the unsafe behaviors of miners.…”

A study on the simulation of psychological and behavioral dynamics in the unsafe state of coal mine workers

“…To some extent, it provides technical and theoretical support for describing human behavior characteristics (Qiao et al, 2018;Cao et al, 2019;You et al, 2019;Chen et al, 2022). Based on the existing research results in psychology and physiology, the combination of the generation and action mechanism of human emotions, related scholars have constructed a human behavior model, creating a new direction of human behavior simulation research (Reynolds, 1987;Yang et al, 2022b). At the same time (Reynolds, 1987;Tu and Terzopoulos, 1994;Zhang et al, 2017), used the law of individuals imitating each other in group psychology simulates human behavior (Musse and Thalmann, 1997;Thalmann et al, 2000).…”