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Regions from the ground up

A network partitioning approach to regional delineation

Bibliographic Data

ID21248005
AuthorsRuth Hamilton (0000-0002-0855-9533, University of Sheffield), Alasdair Rae (0000-0003-0136-7659, University of Sheffield, corresponding author)
Year2020
Volume47
Issue5
Pages775-789
Publication date2020-06-01
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning B Urban Analytics and City Science (JOURNAL)
Journal identifiersISSN: 2399-8083 • E-ISSN: 2399-8091
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/2399808318804226
OpenAlexW2897560692
LanguageEN
Citations received5
References cited20

In this paper, we consider the question of what is ‘in’ a region, from an economic perspective, based on commuting data. This follows a long line of studies on labour market delineation, including the widely used ‘travel-to-work area’ approach. Using Combo, a network partitioning algorithm, we analyse commuting data from the 2011 UK Census in order to define a discrete set of regions. Our aim is twofold: to contribute to methodological advances in regional delineation, and to produce results that have real-world utility. Following the introduction, we review previous work, before describing our data and methods. Our approach produces 17 new ‘regions’ for Scotland, in contrast to the existing set of 32. Our view is that algorithmic approaches to regional delineation have much to offer in a policy setting, but this must be tempered by the fact that regions, however defined, are inherently political constructs

Census · Data mining · Data science · Data set · Econometrics · Economics · Geography · Operations research · Population · Regional science · Sociology · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Mathematics · Regional Economics and Spatial Analysis · Urban Transport and Accessibility · Artificial Intelligence

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Citations per year0.83
Citation span2020 - 2025 (6)
Highly citedNo

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