A social network-based approach for analyzing interproject risks in large-scale programs

Managing risks in large-scale programs involves navigating the complexities of interrelated projects and diverse stakeholder involvement, which traditional project-level risk management approaches often fail to address. This study presents an advanced social network analysis (SNA)-based methodology for interproject risk management, incorporating a weighted network model that simultaneously considers both the number and strength of project connections. This approach's key innovation is the use of a tunable parameter, which balances the relative importance of connection strength and connection quantity, providing a more nuanced understanding of the interdependencies between projects. Based on the dimensions of project interdependence and stakeholder involvement, the proposed approach enhances program risk management efficiency by classifying risks into four categories - primary, interdependent, multistakeholder, and negligible - and suggesting tailored response strategies. The methodology is validated through an empirical case study of the Expo 2020 construction program, demonstrating its capacity to accurately detect and categorize program risks. The study's main theoretical contribution is its novel integration of SNA into program risk management, introducing weighted network models to quantify project interdependencies and stakeholder interactions.