Social Network Analysis in Economic and Technology Policy
Modern economic systems and technological innovation ecosystems are increasingly understood as complex adaptive systems.
Processes such as the restructuring of global value chains (GVCs), the convergence of digital technologies, and the transition toward carbon neutrality operate through multilayered interdependencies that are difficult to explain using linear causal models. In this context, Social Network Analysis (SNA) and, more broadly, network science have emerged as important tools for policy analysis. These approaches help reveal relational structures among actors and the patterns of flows — of knowledge, capital, and resources — that traditional methods often fail to capture.
This article reviews recent research cases in the fields of economic and technology policy to illustrate how SNA methodologies are being applied to address policy challenges. The discussion focuses on both methodological innovations and empirical findings. In particular, the review highlights notable studies across four thematic areas: global trade and value chains, energy transition and sustainability, digital technology and innovation ecosystems, and industrial clusters and financial networks.