Integrating digital twins and decision support systems for predictive risk management in urban renewal

Urban renewal projects are increasingly central to addressing rapid urbanisation, deterioratin infrastructure, and climate-induced vulnerabilities. However, they are characterised by complex and interdependent risks spanning structural, socio-economic, environmental, and managerial domains that remain poorly managed by conventional methods. While digital twin (DT) technology has demonstrated value in construction monitoring, predictive maintenance, and safety management, its application as an integrated framework for risk management in urban renewal remains underdeveloped. This study addresses this critical gap by developing a DT-enabled decision support system tailored for risk management in urban renewal construction. Scopus database for peer-reviewed publications from (2014–August 2025) was used, synthesising evidence from 47 peer-reviewed studies that met the inclusion and exclusion criteria guided by PRISMA methodology for systematic review process. Findings reveal that existing DT applications are fragmented, focusing on isolated risks rather than adopting a holistic perspective on urban renewal challenges. To overcome this limitation, a comprehensive conceptual framework that integrates DT technology with decision support systems, enabling real-time monitoring, predictive risk modelling, and proactive decision-making across the full project lifecycle was proposed. The framework demonstrates novelty of this research by bridging structural, environmental, and socio-economic risks, offering a multi-dimensional approach to urban futures resilient through DTs potentials.