Social-Network Analytics of Construction Supply Chain

Growing disruptions, uncertainties, and complex risks such as pandemics, extreme weather, and geopolitical conflicts imperil the under-examined construction supply chain, a network that occupies a pivotal nexus in the broader economy. Therefore, it is vital to map its relationships and pinpoint where disruptions concentrate, and recovery can be accelerated. Guided by three research questions on network emergence, positional vulnerability, and how pressures steer technology adoption, this exploratory study maps how construction supply chain networks both create and alleviate operational strain. To address this problem, this study combines empirical, semi-structured interviews with social network analytics. Purposive and snowball sampling yield semi-structured interviews that span all major supply chain roles. Thematic coding translates reported interactions into nodes and edges of a complex network and groups challenges into thematic categories. Furthermore, degree, betweenness, and eigenvector metrics outlined structural vulnerabilities and leverage points. The results show how six main challenge categories (comprising 16 open codes) concentrate systematically at specific network positions. Relationship and contract issues accumulate at high-centrality brokers (degree centrality 0.818) while external pressures affect peripheral suppliers. Technology adoption preferences emerge from structural roles, with central coordinators seeking predictive analytics and peripheral actors prioritizing traceability systems in networks with moderate density (0.591). The research provides a replicable framework for identifying structural vulnerabilities and designing position-based interventions in construction supply chains. The network-theoretic framework opens new research directions for dynamic network analysis, multi-project supply webs, and stakeholder-centered technology integration strategies.