Lean Construction 4.0: enhancing situational awareness for autonomous decision-making through digital visual management

Purpose – This paper aims to address the need for a comprehensive management framework that supports decentralised and autonomous decision-making to reduce waste and improve flow in construction. Design/methodology/approach – Following a design science research approach, an integrative literature review was conducted to build the framework, which was then comparatively assessed against existing visual-management and situation-awareness systems to identify functional gaps and potential applications. Findings – The resulting framework links the physical, informational and socio-psychological dimensions of construction to deliver continuously accessible, task-relevant information that supports real-time decision-making and coordination across trades. Research limitations/implications – Implementation of the DVM framework remains limited by economic, organisational and technological barriers. This calls for future research on scalable adoption, interoperability and digital skills development. Practical implications – The framework strengthens operational decision-making and cross-trade coordination by integrating automated data capture, analysis, and visual information delivery. In practice, it supports proactive constraint management, increases safety and resource efficiency and minimises waste arising from fragmented information flow. Social implications – The framework advances human-centric construction management by strengthening workers' autonomy and situational awareness while integrating digital systems that support, rather than replace, human judgement. It highlights management as a socio-technical process built on awareness, trust and informed decision-making. Originality/value – The study introduces a digital visual management framework that unites physical, digital and cognitive perspectives, extending lean construction theory and offering a practical foundation for developing and implementing next-generation, human-centric decision-support systems in construction projects.