An Interactive Model among Potential Human Risk Factors: 331 Cases of Coal Mine Roof Accidents in China.

In order to explore optimal strategies for managing potential human risk factors, this paper developed an interactive model among potential human risk factors based on the development processes of accidents. This model was divided into four stages, i.e., risk latency stage, risk accumulation stage, risk explosion stage and risk residue stage. Based on this model, this paper analyzed risk management procedures and relevant personal's responsibility in each stage, and then probed into the interactive mechanism among human risk factors in three aspects, i.e., knowledge, information and communication. The validity and feasibility of the model was validated by analyzing a coal mine roof accident in China. In addition, the contribution of different functional levels' personnel in risk evolution was discussed. It showed that this model can effectively reveal the interactive mechanism of potential human risk factors, and can thus give significant insights into the development of risk management theories and practices. It also proves that the contribution of different functional levels' personnel in the model is different. This can further help practitioners design enhanced Behavioral-Based Safety (BBS) intervention approaches which can have a more sustainable and persistent impact on corporate personnel's safety behavior. Specific recommendations and suggestions are provided fundamentally for future BBS practices in the coal mine industry.

Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data.

As a high-risk occupation, coal mining has many accidents, primarily due to the unsafe behavior of coal miners. Based on the research of analysis of unsafe behavior and pan-scenario data of miners, a theoretical framework for the analysis of unsafe behavior characteristics was proposed in this paper. The collected data were divided into realistic scenes and abstract scenes according to different manifestations; the pan-scene data were described from the eight dimensions of time, behavioral trace, location, behavioral property, behavioral individual, degree, unsafe action, and specialty using a quantitative method for the structure conversion; and the rules were discovered through cluster analysis and association analysis. A total of 225 coal mine gas explosion accidents were used for analysis, and the pan-scene data description and structure conversion of unsafe behavior that caused these accidents were realized. In a certain cluster, the distribution rules of dimensions and the interaction between different dimensions of unsafe behavior were explored after analysis. The results show that the proposed eight dimensions can fully explain the basic characteristics and attributes of the unsafe behavior of coal miners. The structure conversion can reduce the workload of managers and effectively improve the safety data processing capabilities, and the result of data analysis can provide data support and a management basis for safety management. A new method and thought for the data analysis of miners' unsafe behavior is provided.