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A new geodemographic classification of commuting flows for England and Wales

Hincks, Stephen, Kingston, Richard, Webb, Brian and Wong, Cecilia 2018. A new geodemographic classification of commuting flows for England and Wales. International Journal of Geographical Information Science 32 (4) , pp. 663-684. 10.1080/13658816.2017.1407416

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Abstract

This paper aims to contribute to the area of geodemographic research through the development of a new and novel flow-based classification of commuting for England and Wales. In doing so, it applies an approach to the analysis of commuting in which origindestination flow-data, collected as part of the 2011 census of England and Wales, are segmented into groups based on shared similarities across multiple demographic and socioeconomic attributes. K-means clustering was applied to 49 flow-based commuter variables for 513,892 interactions that captured 18.4 million of the 26.5 million workers recorded as part of the 2011 census of England and Wales. The final classification resulted in an upper-tier of nine ‘Supergroups’ which were subsequently partitioned to derive a lowertier of 40 ‘Groups’. A nomenclature was developed and associated pen-portraits derived to provide basic signposting to the dominant characteristics of each cluster. Analysis of a selection of patterns underlying the nine-fold Supergroup configuration revealed a highly variegated structure of commuting in England and Wales. The classification has potentially wide-ranging descriptive and analytical applications within research and policy domains and the approach would be equally transferable to other countries and contexts where origindestination data is disaggregated based on commuter characteristics.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Geography and Planning (GEOPL)
Additional Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher: Taylor & Francis
ISSN: 1365-8816
Date of First Compliant Deposit: 16 November 2017
Date of Acceptance: 16 November 2017
Last Modified: 25 Nov 2020 07:23
URI: http://orca-mwe.cf.ac.uk/id/eprint/106642

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