Using network theory to explore the complexity of subway construction accident network (SCAN) for promoting safety management

PurposeThe image of the construction industry in China, as in many other countries, is tarnished by its poor safety record. With the rapid development of subway systems in Chinese urban areas, construction workers are being exposed to new risks which are poorly understood and managed. Subway construction projects are large scale and scattered over many construction sites, and involve numerous stakeholders and sophisticated technologies in challenging underground environments. Accident rates are high and have significant economic and social consequences for the firms and people involved. Addressing the gap in research about the safety risk in these projects, the purpose of this paper is to advance understanding of the factors influencing the safety of Chinese subway construction projects with the overall objective of reducing accident rates.Design/methodology/approachA survey was conducted with 399 subway construction professionals across five stakeholder groups. Follow-up interviews were also conducted with five experienced experts in safety management on subway projects to validate the results.FindingsIt was found that the eight most critical factors perceived by stakeholders to influence safety risks on Chinese subway projects are: project management team; contractor-related factors; site underground environment; safety protection during the use of machines; safety management investment; site construction monitoring and measurement; hazard identification and communication; and use of machines in all stages. This indicates that in allocating limited project resources to improve the safety of subway projects, managers should focus on: developing safety knowledge and positive attitudes in leadership teams; formulating effective risk management systems to identify, assess, mitigate, measure and monitor safety risks on site; improving communications with stakeholders about these risks and effectively managing plant, equipment and machinery.Originality/valueThis research contributes a new multi-stakeholder perspective to the lack of safety research in Chinese subway construction projects. The research findings provide important new insights for policymakers and managers in improving safety outcomes on these major projects, producing potentially significant social and economic benefits for society and the construction industry.

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Intelligent Recognition of Safety Risk in Metro Engineering Construction Based on BP Neural Network

Mathematical Problems in Engineering ◽

10.1155/2021/5587027 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Mengchu Li ◽

Jingchun Wang

Keyword(s):

Neural Network ◽

Bp Neural Network ◽

Safety Management ◽

Rapid Development ◽

Construction Safety ◽

Urban Rail Transit ◽

Safety Risk ◽

Subway Construction ◽

Under Construction ◽

Assessment Problems

With the rapid development of urban economy, the development of urban rail transit is becoming more and more rapid. As an energy-saving, land-saving, and environment-friendly green travel mode, the subway provides realistic and feasible solutions to the increasingly prominent traffic environment and other urban diseases in our country and brings a booming development in the subway construction industry with efforts to promote and build in many large cities. For a large number of subway constructions, it is particularly important to judge the construction safety status in time during the entire safety management process. Regularly conducting safety risk assessments on subway construction status can accurately predict and judge the types of accidents that occur. In order to solve the current safety risk assessment problems in the process of subway construction in our country, this paper is based on the BP neural network to intelligently identify the safety risks of subway construction, choosing from three aspects: human factors, management factors, and risk factors. We evaluate the construction safety of subway projects under construction through the model, predict the types of accidents that may occur, so that the construction unit can take corresponding preventive and improvement measures, improve the relevant safety technology of subway construction in a targeted manner, and propose corresponding reductions. We provide suggestions and measures for risk probability, to ensure that the construction unit discovers the danger in time and takes safety measures. The rectification measures provided theoretical basis and guidance.

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