An Data-Driven Framework for Optimising Safety Investment Allocation Construction Site

<p dir="ltr">Construction site accidents can result in numerous casualties, significant economic losses, and substantial social impacts worldwide. Effective safety management measures are essential for mitigating the risks during construction. The Chinese construction industry faces major safety challenges, which have attracted considerable societal attention. Efficient resource allocation on construction sites is key to optimising safety management. However, research on decision-making regarding resource distribution remains limited. This research aims to develop an integrated framework for optimising safety investment allocation on Chinese construction sites to balance safety performance, safety vulnerability, and cost. The proposed framework generates the optimal investment strategies based on historical accident data, expert recommendations and questionnaires. Within this framework, the loss index is defined to quantify the severity and probability of the construction accidents. The impact of risk prevention strategies in the construction safety management is then evaluated through Quality Function Deployment (QFD) framework. Last, the Multi-Objective Optimization (MOO) method is leveraged to balance the impact of the accident and the corresponding risk mitigation strategies to compute the resource allocation plan for construction site safety management. This research provides a systematic approach for Chinese construction management authorities to enhance safety management, reduce accidents, and make informed decisions regarding safety investments. Furthermore, it contributes to improving construction safety by providing data-driven, practical solutions for resource allocation.</p>