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Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

This chapter presents a theoretical framework of the industrial relations (IR) system in China’s coal mining industry, combining the roles of management organizations, workers, and trade unions, as well as government agencies. It is one of the first empirical attempts to investigate the relationship between human resource (HR) practices, labor relations, and occupational safety in China’s coal mining industry over the past 60 years, based on the secondary data on coal mining accidents and case studies of two state-owned coal mines in a northern city in Anhui Province, China. The fluctuating occupational safety has been affected by government regulations over different time spans, marked by key political agendas, and by coal mining firms taking concrete measures to respond to these regulations, while exhibiting differing safety performance in state-owned versus township-and-village-owned mines. The field studies compared a safety-oriented to a cost-control-oriented HR and labor relations system, and their influences on safety performance. Coal mining firms and practitioners are advised to shift the traditional personnel management paradigm to a modern HR management system. In addition, although workers are often blamed directly for accidents, it is suggested that workers’ participation and voice in various processes of decision-making and policy implementation, and trade unions’ active involvement in protecting workers from occupational hazards, be encouraged.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

In China, external supervision on construction safety mainly comes from the government and supervision engineers (SEs). However, the construction safety supervisory mechanism (CSSM) contains some dilemmas affecting the improvement of safety performance, such as the declining impact of SEs, the increasing rent-seeking behaviors of contractor and excessive government interference. This study aims to depict and analyze the CSSM in China from an evolutionary game view. The objectives are to understand the supervision strategy and evolutionary behaviors of different stakeholders, propose suggestions for improving safety performance and help the key safety supervision stakeholders, especially the government, formulate a suitable safety supervision strategy.

This research uses tripartite dynamic evolutionary game theory to study the CSSM in China and solve the stable equilibrium solution using system dynamics.

This study has revealed the game relationship of construction safety supervision mechanisms in China and solved the stable equilibrium solution. The results prove that a supervision engineer (SE) plays a crucial role in the CSSM, and “supervision engineer useless” is an unreasonable assertion. For government supervision agency (GSA), excessive inspection and free-market regulation are neither wise strategies. GSA can reduce the inspection frequency when general contractors (GCs) input high safety investments and SEs implement responsible supervision. But keeping proper government supervision to avoid GC's unlawful behaviors and SE's rent-seeking is indispensable. In addition, excessive governmental supervision will weaken SE's role, so the government should transfer some supervision powers to SE.

This study focuses on the dynamic evolution process between GSA, GC and SE. This method is different from most research that neglected the dynamic characteristic of system and game solution stability. The research methods not only contribute to construction safety supervision policy-making in China but also help to improve supervision efficiency in other countries and other fields.

With the rapid low-carbon transformation in China, the industrial approach and labor structure of mining enterprises are undergoing constant changes, leading to an increasing psychological dilemma faced by coal miners. This study aims to reveal the relationship and mechanism of factors influencing the psychological dilemma of miners, and to provide optimal intervention strategies for the safety and sustainable development of employees and enterprises.

To effectively address the complex issue of the psychological dilemma faced by miners, this study identifies and constructs five-dimensional elements, comprising 20 indicators, that influence psychological dilemmas. The relational mechanism of action of factors influencing psychological dilemma was then elucidated using an integration of interpretive structural modeling and cross-impact matrix multiplication.

Industry dilemma perception is a “direct” factor with dependent attributes. The perceptions of management response and relationship dilemmas are “root” factors with driving attributes. Change adaptation dilemma perception is a “susceptibility” factor with linkage attributes. Work dilemma perception is a “blunt” factor with both dependent and autonomous attributes.

The aforementioned findings offer a critical theoretical and practical foundation for developing systematic and cascading intervention strategies to address the psychological dilemma mining enterprises face, which contributes to advancing a high-quality coal industry and efficient energy development.