Learning from architectural theory about how cities work as complex and evolving spatial systems

Abstract

Abstract This article seeks to advance a key element of the methodological framework for evolutionary economic geography (EEG)—the conceptualisation of ‘urban space’. Drawing on recent theories from architecture and urban data science, it argues that the networked and topological qualities of urban built environments have been neglected in the EEG discipline, and yet they play an important role in how cities work as ‘complex evolving systems’. The article explores different ways in which the spatial configuration of cities influences urban economic evolution, drawing on Bill Hillier’s theory of space syntax and a case study from Greater Manchester. It concludes that when urban street systems are disrupted this can potentially become one contributing factor in why places become economically ‘left behind’.