The synergistic interaction between emergency management departments and enterprises constitutes a fundamental mechanism for mitigating the risks of technological accidents caused by natural disasters (Natech). The efficacy of this collaborative approach is impacted by comprehensive risk analyses and the game between government and enterprise. Predicated on these premises, the evolutionary game analysis of government–enterprise collaboration in coping with Natech risk was carried out. Firstly, an evolutionary game model of government–enterprise collaboration in coping with Natech risk was constructed. Secondly, the evolutionary stability strategy (ESS) was developed. Finally, these strategies were substantiated through numerical simulations. The findings revealed that at lower levels of Natech risk, enterprises will choose low investment in coping capacity building, and emergency management departments will choose delayed disposal. Under moderate Natech risk, enterprises will increase their investments if emergency management departments persist with delayed strategies, and emergency management departments will react proactively if enterprises persist with low investment. Under a high Natech risk, a pattern of strategic misalignment emerges between the two entities. This study contributes a theoretical basis for the optimization of government–enterprise collaboration in coping with Natech risks.

Humans are at the core of the social-technical system, and their behavioral errors affect the reliability and safety of the entire system in varying degrees. Occupational accidents and large-scale industrial accidents are often attributed to human errors, accounting for more than 80% of accidents. In view of the complexity of systems and the coupling of elements, a new HFA method is proposed based on a complex network. According to system safety theory, a complex network is regarded as a network composed of humans, matters, environments, and management, and the basic structure of the HFA network is summarized. On this basis, a system safety method of HFA is developed which proposes a universal human error causation model. Moreover, a network analysis method for human errors is also presented, which is a comprehensive analysis of human errors that have occurred. Finally, the above methods are applied to gas explosion accidents that occurred in China. Results show that the two methods proposed are universal to all fields, and their combination improves the effectiveness of human error management and promotes the targeted, proactive, systematic, and dynamic prevention of critical nodes and paths from a holistic perspective.

Students’ unsafe behavior is the main factor related to accidents in university laboratories. The safety climate is an important factor that affects individual safety behavior on the organizational level. Therefore, to improve the effect of university laboratory safety management, based on the theoretical framework of AMO and the SEM method, the influence of the laboratory safety climate on the safety compliance behavior and safety participation behavior of 500 university students in China was investigated and analyzed. The results show that safety ability and safety motivation play parallel mediating roles, and their synergistic effect promotes the generation of safety behavior: the safety climate in the laboratory has a direct positive effect on both safety compliance behavior and safety participation behavior; safety knowledge and safety skills have significant mediating effects on both safety compliance behavior and safety participation behavior in the laboratory safety climate; external safety motivation has a significant mediating effect on safety compliance behavior and safety participation behavior in the laboratory safety climate; and internal safety motivation does not have a mediating effect on safety compliance behavior and safety participation behavior in the laboratory safety climate. To improve students’ safety behavior performance, measures such as strengthening the construction of the dynamic improvement mechanism of the laboratory safety climate, optimizing the laboratory safety access system, and taking comprehensive measures to ensure the continuous positive influence of the safety climate on students’ safety behavior can be adopted.

Climate change is driving the traditional development mode to a green, low-carbon, and sustainable development path. Enterprise green transformation is an important path to achieve green and low-carbon. This study, based on evolutionary game theory, analyzes the driving mechanisms of enterprises green transformation, focusing on the interactive relationship between government policy support and enterprise green transformation. By constructing a game model for both government and enterprises, it examines the impacts of different levels of policy support, enterprise transformation costs, market return expectations, and environmental penalties on enterprise green transformation decisions. The results indicate that high government policy support significantly enhances the success rate of enterprise green transformation, while transformation costs, market returns, and environmental penalties play important moderating roles in the decision-making process. Particularly in the context of the “dual carbon” goals, sustained and stable policy support is crucial for enterprise green transformation. This study further suggests promoting enterprise green transformation through market-oriented measures, digital technology empowerment, and long-term incentive mechanisms, providing theoretical foundations and practical guidance for government policy formulation and enterprise green development.

Organizational safety decisions rely heavily on safety information in today’s data-driven era, but there is a significant danger of information distortion that can compromise system safety. To address the issue of information distortion and enhance system safety, a new approach called information delayering safety management (IDSM) has been developed and implemented. The IDSM method combines delayering management mode and graph theory to study the relationship between information distortion management and delayering management. By using the delayering mode as a theoretical foundation for safety information management, information distortion can be reduced. The implementation of this approach from a graph theory perspective has been tested using a case study and has been proven to effectively enhance the reliability of safety information and ensure system safety. The minimum control set of the directed graph algorithm can be used to realize the whole network management of safety information distortion. The amount of safety information and signal noise can be controlled by adjusting connectivity, and safety information distortion can be regulated through the adjustment of structural holes and flow direction. Overall, IDSM offers a new, effective method for accident analysis and safety management, allowing safety professionals to make informed decisions based on robust advanced evidence.