UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The nested structure of urban business clusters

Cottineau, C; Arcaute, E; (2020) The nested structure of urban business clusters. Applied Network Science , 5 , Article 2. 10.1007/s41109-019-0246-9. Green open access

[thumbnail of 10.1007_s41109-019-0246-9.pdf]
10.1007_s41109-019-0246-9.pdf - Published Version

Download (4MB) | Preview


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 bound or geographically consistent. In this paper, we cluster spatial economic activities through a multi-scalar approach following percolation theory. We consider both the industrial similarity and the geographical proximity of 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.

Type: Article
Title: The nested structure of urban business clusters
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s41109-019-0246-9
Publisher version: https://doi.org/10.1007/s41109-019-0246-9
Language: English
Additional information: Copyright © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Geoindustrial clusters, Multi-scalar analysis, Business, Greater London, Microdata, Percolation theory
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/10087180
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item