Decision-making in safety efforts: Role of the government in reducing the probability of workplace accidents in China

Ma, Yanhong; Zhao, Qiuhong

doi:10.1016/j.ssci.2017.12.038

Cited by 31 publications

(16 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Various studies have been conducted to increase the awareness of construction workers about the risks of the work they face and to reduce the possibility of workplace accidents [13][14][15].…”

Section: Discussionmentioning

confidence: 99%

The Safety Awareness of Construction Workers Regarding Workplace Health and Safety Standard

Fauzania¹,

Aryanti²,

Herman³

et al. 2019

Proceedings of the 5th UPI International Conference on Technical and Vocational Education and Training (ICTVET 2018)

View full text Add to dashboard Cite

Construction work is one of the professions which has a high risk of accidents. Therefore, construction work has to be carried out properly in terms of occupational health and safety standards. The high rate of workplace accidents shows workers' lack of understanding of occupational health and safety standards. The purpose of this research was to identify workers' awareness especially construction workers regarding occupational health and safety standards. This research uses a qualitative approach, and the data is collected by interviewing 24 construction workers in Bandung, Indonesia. The result of this research indicates that not all of the workers understand the importance of occupational health and safety. Hence, they rarely wear protective clothing even for they own safety.

show abstract

Section: Discussionmentioning

confidence: 99%

The Safety Awareness of Construction Workers Regarding Workplace Health and Safety Standard

Fauzania¹,

Aryanti²,

Herman³

et al. 2019

Proceedings of the 5th UPI International Conference on Technical and Vocational Education and Training (ICTVET 2018)

View full text Add to dashboard Cite

show abstract

“…The main research on evolutionary games has focused on several aspects, such as the analysis of evolutionary stability strategies (Brown & Vincent, 1987; Kuzmics, 2004), individual adaptive learning, replicator dynamics (Hausken, 1995a; Riechmann, 2001; Tuyls & Parsons, 2007), and the evolutionary cooperation problem of game players under mutations (Fosco & Mengel, 2011; Metzler & Horn, 2003). In recent years, evolutionary game theory has been used extensively in the field of regulation (Khanmohamadi, Bagheri, Khademi, & Ghannadpour, 2018; Liu, Li, & Meng, 2019; Liu, Xiao, Li, & Wang, 2015; Ma & Zhao, 2018; Zhang, Gao, & Guan, 2015). Several studies on problems existing in the railway operational safety supervision system have achieved some results.…”

Section: Literature Reviewmentioning

confidence: 99%

China's Railway Transportation Safety Regulation System Based on Evolutionary Game Theory and System Dynamics

2020

View full text Add to dashboard Cite

China's railways were restructured in 2013. The number of regulatory practitioners has decreased significantly, making real-time regulation more difficult. Regulatory transfers from inside to outside the railway industry increases information risks. A more reasonable regulation mechanism is needed. The article considers introducing a public supervision mechanism into the railway transportation safety regulation system, which includes two regulators and one regulatee. As the government regulator, the State Railway Administration (SRA) regulates the safety of China Railway Corporation (CR) and encourages the public to act as supervisors to expose the CR's unsafe production information. To analyze the risks and effectiveness of the system, a multiplayer evolutionary game and system dynamics-based model for railway transportation safety regulation is established. The decision processes of players under different conditions are simulated. The results show that improving the public supervision ratio is conducive to improve the CR's safe production ratio. However, there is no evolutionarily stable strategy (ESS) in the system. Strategies and evolutionary processes have large fluctuations, which represent high risk. Excessive penalty and reward coefficients can aggravate the amplitude and frequency of fluctuations, causing uncertainty in regulation and making it more difficult to control the actual problems. A dynamic reward and punishment mechanism is proposed to control these fluctuations. The system finally achieves an ESS that results in the lowest regulation investment for the SRA, a safe production ratio for the CR of 95%, and a public supervision ratio of 95.2%. Introducing public supervision and dynamic reward and punishment mechanisms help to stabilize and improve the CR's safe production ratio and to decrease the SRA's regulatory investment.

show abstract

“…The prediction of coalmine water inrush must be rapid, accurate, and effective. Hence, it is important to improve the operating speed of the prediction model, while ensuring the prediction accuracy [21][22][23]. Bhattacharjee et al [24] developed a hybrid prediction model based on extreme learning machine (ELM) and the principal component analysis (PCA), and proved that the hybrid model is more accurate and faster than the least squares (LS) SVM and traditional BP model.…”

Section: Introductionmentioning

confidence: 99%

A Coalmine Water Inrush Prediction Model Based on Artificial Intelligence

Wang¹,

Wei²,

Yao³

2020

IJSSE

View full text Add to dashboard Cite

The prevention of water inrush is of great significance to the work safety in coalmines. However, the existing prediction models for coalmine water inrush cannot achieve desirable speed, accuracy, or generalization ability, owing to the complexity and diversity of causes of this accident. Therefore, this paper develops an artificial intelligence (AI)based coalmine water inrush safety prediction model, making coalmine water inrush prediction more accurate, real-time, and robust. Firstly, the causes of coalmine water inrush were combed, and used to build a reasonable evaluation index system. Next, the extreme learning machine (ELM) was optimized with particle swarm optimization (PSO) algorithm and ant colony optimization (ACO) algorithm, and developed into a coalmine water inrush safety prediction model. The dimensionality reduction in subset classification was introduced in great details. Finally, the effectiveness of our model was proved through experiments. The research results provide the basis for the application of combinatory optimized learning machines in hazard prediction of other fields.

show abstract

Decision-making in safety efforts: Role of the government in reducing the probability of workplace accidents in China

Cited by 31 publications

References 19 publications

The Safety Awareness of Construction Workers Regarding Workplace Health and Safety Standard

The Safety Awareness of Construction Workers Regarding Workplace Health and Safety Standard

China's Railway Transportation Safety Regulation System Based on Evolutionary Game Theory and System Dynamics

A Coalmine Water Inrush Prediction Model Based on Artificial Intelligence

Contact Info

Product

Resources

About