Infrastructure’s fundamental role in developed economies of enabling and mediating spatial flows of resources, goods, and services, is widely acknowledged and the provision of resilient, effective National Infrastructure (NI) systems has become a focus of many advanced economies. However, a quantification of the economic role of infrastructure systems remains elusive, as theories of economic growth and development still struggle to fully appreciate all aspects infrastructure systems in a socio-economy, which would require adequate treatments of the role of space/geography, matter/resources, energy/exergy, entropy/2nd law of thermodynamics, and information/knowledge.

The need for a comprehensive understanding of how infrastructure systems develop within the wider economy is further emphasised by the recognition of a set of challenges for Infrastructure service provision in advanced economies, such as socio-economic and climate change. Overcoming these multiple challenges requires a long-term strategic view on infrastructure provision and the processes of structural change within NI systems and leads away from the established way of planning and evaluating infrastructure systems in isolation and based on an understanding of the physical infrastructures towards an understanding of the co-evolution of infrastructures within a complex adaptive socio-economic system.
And while the recognition of the complex adaptive nature of infrastructure and economic systems is not new and many contributions have been made from fields such as ecological economics, evolutionary economics, econophysics, complexity theory and others to further the understanding of underlying relationships and dynamics the treatment of information and innovation in infrastructure systems is still overly simplistic.

In this study, we adopt a perspective that draws on, amongst other ideas, complexity science and Universal Darwinism and has been described as “A Third Window” (besides Newtonian and Darwinian perspectives) to look at the development of emergent structures in complex adaptive systems.