The delayed era of network economics: ongoing opportunities for dynamic socio-economic network models

Abstract

Network science has transformed fields ranging from biology to sociology, yet its integration into economics remains limited and uneven. In this paper, we argue that despite the recognized relevance of network models for capturing interdependencies among economic agents, their uptake within economics has been slow–and in some areas, even declining. Drawing on bibliometric data from the Web of Science, we document this trend and identify structural barriers that hinder wider adoption. To address these gaps, we propose a set of actionable steps: creating open platforms for model sharing, revising economics curricula to include network theory and computational methods, and establishing new venues for interdisciplinary dissemination. By doing so, we aim to position dynamic socio-economic network models as essential tools for understanding complex economic phenomena, ranging from market contagion to systemic risk, in an increasingly interconnected world.