Hoisting is an essential aspect of Industrial Building System (IBS) construction. Although research on hoisting safety in China has made strides to focus on "worker," "data," "task," "site," and "accident," there still needs to be more approaches based on multi-dimensional social system thinking. Therefore, the paper aims to fill this gap. We investigated 105 hoisting accidents in China and found that hoisting accidents occurred most frequently in China's southeast coastal region; truck-mounted cranes and tower cranes were the most common types of machinery involved in accidents; hoisting load off, capsizing of crane machinery, and workers falling from height are the three most common accident types; the average impact of a single hoisting accident is approximately RMB 2.43 million direct economic loss, 1.543 deaths and 0.829 injured. This study used three algorithms (Rindge regression, Lasson regression, and partial least squares regression) to explore the impact of deaths and injuries on direct economic losses. By combining Rasmussen's risk framework with the characteristics of hoisting construction, six risk domains and thirty-six safety risk factors were identified. Finally, we used AcciMap technology to construct a qualitative IBS hoisting management model, which exhaustively presents the systematic levels and propagation paths of the influencing factors by the PDCA method. The research helps academics explore strategies to improve the safety of hoisting construction in IBS. Moreover, the study outcomes can inform the policy-making process towards promoting healthy and sustainable construction development.
Occupational injuries in the construction industry have plagued many countries, and many cases have shown that accidents often occur because of a combination of project participants. Assembled construction (AC) projects have received extensive attention from Chinese scholars as a future trend, but few studies have explored the interrelationships and potential risks of various stakeholders in depth. This study fills this research gap by proposing a multi-stakeholder AC risk framework. The study surveyed 396 stakeholders, then analyzed the collected data and created a risk framework based on Structural Equation Modelling (SEM) and the CRITIC weighting method. The results revealed that factors like "regular supervision is a formality," "blindly approving the wrong safety measures," and "failure to organize effective safety education and training." are vital risks in AC of China. Finally, the study validates the risk factors and the framework with 180 real-life cases, which shows that the proposed framework is theoretically grounded and realistic. The study also suggests multi-level strategies such as introducing AI-based automated risk monitoring, improving the adaptability of normative provisions to technological advances, and advancing the culture of project communities of interest to ensure AC's safe practices.