Smart infrastructure projects (SIPs) are increasingly critical in the era of digital transformation. While advanced technologies enhance intelligence and efficiency, they also introduce new and interacting risks that intensify the overall risk landscape. This study aims to systematically identify, model, and analyze SIP risks to support effective risk governance and resilience-building of new SIPs.
Adopting a cyber-physical-social (CPS) perspective and network paradigm, a multiscale risk network model is developed, and a multilevel network analysis is conducted to reveal cross-dimensional interdependencies and propagation mechanisms of SIP risks. A mixed-method combining literature review and expert interviews is employed for risk identification.
A total of 40 components and 107 risk factors are identified, established as 6 risk network models. The local and global interfaces and internal-external risk propagation among CPS dimensions are revealed. The results show that social-related risks and cyber-social interfaces are dominant that accelerate cross-dimensional propagation. Three categories of critical risk points are distinguished, each exhibiting distinct propagation dynamics and impacts. Key risk paths are identified, including cascading chains extending from regulatory contradictions to technological resource deficiencies.
This research offers an innovative perspective to conceptualize SIP risks as a complex system based on the new characteristics of smart infrastructure. It contributes (1) a theoretical framework for understanding emerging risk situations under smart technologies; (2) practical tools to model and analyze risk units, risk districts, and the whole risk system; (3) targeted risk mitigation and resilience enhancement measures from micro to macro levels.
