PurposeThis paper aims to analyze the current state of technological advancements research in addressing the diverse risk factors involved in earthmoving equipment operations through Rasmussen's (1997) risk management framework. It examines how existing technologies research capture, manage and disseminate risk information across various levels of safety management by defining their core functionalities. The research highlights gaps in current technological solutions research regarding the flow of information in the risk management framework. It emphasizes the need for an integrated approach in technological advancements to enhance the holistic safety management approach capable of capturing various risks across different levels of risk management.Design/methodology/approachThis research employs a multistep approach. Initially, earthmoving equipment risk factors and functionalities of technological solutions were identified through a systematic review of current scholarly works. Subsequently, social network analysis (SNA) and Pareto analysis were applied to evaluate and determine the importance of risk factors and functionalities of technologies for improving them.FindingsThe findings highlight the importance of multilevel approaches that expand technological functionalities to address risk factors across all levels of Rasmussen's (1997) risk management framework. The current combination of technological advancements focuses primarily on on-site monitoring, congested work sites, site layout/path planning, utility problems, safety training, and blind spot and visibility. Site monitoring and warning systems, supported by sensors and computer vision (CV), are pivotal for identifying risks and enabling data-driven safety management. However, workforce-level cognitive factors (W1-W6), which influence safety behavior, remain underexplored for enhancing their functionality to anticipation and response during the operation. Prevention is the core function of current technological solutions, emphasizing the need to address human and equipment risk factors such as sources of hazards in earthmoving operations. Learning: AI as a data-driven approach and IoT systems are key for future development, and when grounded in ontology-based knowledge of earthwork, they gain a structured vision of earthmoving equipment types, their interactions and the earthwork activities. It enhances the capabilities of these technologies to capture and manage complex interactions between hazard sources (human and equipment), supporting comprehensive risk factors across all levels of the risk management framework.Originality/valueThis paper elucidates that technological solutions for safety management in earthmoving equipment operations require a more holistic approach—grounded in an understanding of functionalities of technologies—to effectively capture risks across various levels of Rasmussen (1997) risk management. It emphasizes that technological solutions should not only address isolated hazards but also ensure the continuous flow of information on multiple risk factors across the risk management framework.
