Optimizing Urban Project Implementation Processes through Digital Twin Smart Cities

Urban digital twins, as one of the key technologies of the Fourth Industrial Revolution, establish a dynamic connection between the physical and virtual environments, enabling real-time monitoring, scenario simulation, and data-driven decision-making. Given the complexity of urban project implementation, the diversity of stakeholders, and resource constraints, this technology has significant potential to optimize project execution processes. This study aims to investigate the role and capabilities of digital twin smart cities in optimizing the implementation of urban projects. The research adopts a qualitative approach based on content analysis of scientific documents and publications. In addition, VOSviewer was employed to analyze the knowledge structure and keyword co-occurrence within the existing literature. The study also examines the spatial scales of digital twin smart cities—including the building, street, neighborhood, and city levels—as well as their functional maturity levels, namely passive, predictive, programmable, and autonomous, alongside successful international case studies. The findings indicate that digital twin smart cities, by providing dynamic and data-driven models, contribute to improved project scheduling and implementation speed, reduced costs, enhanced execution quality, increased environmental sustainability, strengthened stakeholder participation, and more effective urban management and decision-making. The results further demonstrate that digital twin smart cities extend far beyond a simulation tool, serving as a strategic platform for data integration, intelligent management, and the optimization of urban project implementation. Consequently, they offer an effective framework for advancing smart city development while enhancing urban planning and policymaking.