The nested structure of urban business clusters

• Published in: Applied network science Vol. 5; no. 1; pp. 1 - 20
• Main Authors: Cottineau, Clémentine, Arcaute, Elsa
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 07-01-2020; Springer Nature B.V; Springer; SpringerOpen
• Subjects: Business; Clusters; Complexity; Computer Appl. in Social and Behavioral Sciences; Computer Science; Data Analysis, Statistics and Probability; Economics and Finance; Geography; Geoindustrial clusters; Greater London; Humanities and Social Sciences; Microdata; Multi-scalar analysis; Percolation theory; Physics; Regional development; Simulation and Modeling; Greater London; Percolation theory; Microdata; Multi-scalar analysis; Geoindustrial clusters; Business
• ISSN: 2364-8228; 2364-8228
• DOI: 10.1007/s41109-019-0246-9

Although the cluster theory literature is bountiful in economics and regional science, there is still a lack of understanding of how the geographical scales of analysis (neighbourhood, city, region) relate to one another and impact the observed phenomenon, and to which extent the clusters are industrially coherent or geographically consistent. In this paper, we cluster spatial economic activities through a multi-scalar approach making use of percolation theory. We consider both the industrial similarity and the geographical proximity between firms, through their joint probability function which is constructed as a copula. This gives rise to an emergent nested hierarchy of geoindustrial clusters, which enables us to analyse the relationships between the different scales, and specific industrial sectors. Using longitudinal business microdata from the Office for National Statistics, we look at the evolution of clusters which spans from very local groups of businesses to the metropolitan level, in 2007 and in 2014, so that the changes stemming from the financial crisis can be observed.