Hospital performance possesses strategic significance in achieving an essential completive advantage for the public hospitals. This study aimed to examine the relationship between patient safety culture (PSC) and the performance of traditional Chinese medicine (TCM) public hospitals in Sichuan, China. To address the research purpose, this study analyses the hospital performance and Patient safety culture in traditional Chinese medicine public hospital in China. We examine the propose model by analyzing cross-sectional survey data from 194 clinical directors at 194 public traditional Chinese medicine hospitals using the Partial least squares structural equation model in Smart PLS 4.0. This study provides predictive evidence that PSC in unit management and management support can lead to better patient safety outcomes. The results revealed patient safety outcomes significantly and positively effects of patient safety related to unit management and management support on overall hospital performance (p-value: 0.000–0.003).

The rapidly growing construction industry often deals with complex and dynamic projects that pose significant safety risks. One of the state-owned companies in Indonesia is engaged in large-scale toll road construction projects with a high incidence of workplace accidents. This study aims to improve safety performance in toll road construction by implementing the Scrum framework. The study uses a System Dynamics approach to model interactions between the Scrum framework, project management, and work safety subsystems. Various scenarios were designed by modifying controlled variables and system structures, including introducing a punishment entity. These scenarios were evaluated based on their impact on reducing incidents and the incident rate over the project period. The results indicate that the combined scenario significantly reduces incidents and incident rates in different conditions. The study also finds a strong relationship between Scrum framework implementation and improved safety performance, demonstrating a reduction in incidents and incident rates by over 50% compared to existing conditions. This research underlines the effectiveness of the Scrum framework in enhancing safety in construction projects.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.

Road accidents involving motorcyclists significantly threaten sustainable mobility and community safety, necessitating a comprehensive examination of contributing factors. This study investigates the behavioral aspects of motorcyclists, including riding anger, sensation-seeking, and mindfulness, which play crucial roles in road accidents. The study employed structural equation modeling to analyze the data, utilizing a cross-sectional design and self-administered questionnaires. The results indicate that riding anger and sensation-seeking tendencies have a direct impact on the likelihood of road accidents, while mindfulness mitigates these effects. Specifically, mindfulness partially mediates the relationships between riding anger and road accident proneness, as well as between sensation-seeking and road accident proneness. These findings underscore the importance of effective anger management, addressing sensation-seeking tendencies, and promoting mindfulness practices among motorcyclists to enhance road safety and sustainable mobility. The insights gained from this research are invaluable for relevant agencies and stakeholders striving to reduce motorcycle-related accidents and foster sustainable communities through targeted interventions and educational programs.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.