Spatial extent and classification of retail agglomerations

Les Dolega

Chapter 8 in Big Data Applications in Geography and Planning, 2021, pp 93-106 from Edward Elgar Publishing

Abstract: Town centres form the core of many urban areas and are characterized by clustering of various types of socio-economic activities with retail and related services being fundamental. They can be viewed as complex systems that constantly evolve, and therefore their composition and spatial extent is likely to expand or contract over time. Although it has been argued that depicting retail agglomerations for a national extent, is challenging, the classification of shopping destinations and delineation of their spatial extent is essential to gaining a better understanding of the relationship between use of retail space and changing consumer behaviour. These challenges have been approached as follows: Firstly, a new automated method for identification of retail agglomerations within Great Britain was proposed. By employing new forms of data at individual business level and application of a bespoke DBSCAN method over 3,000 retail centres have been identified. Secondly, delineation of catchment areas for those retail centres based on a mixed-method approach linked to their function. A Huff spatial interaction model was used to obtain catchment extends for convenience retail destination and drive times method for the higher order comparison retail destinations. Finally, to address the shortcomings of the early attempts to classify clusters of shopping activity that were closely linked to a measure of hierarchical status and involved two-dimensional scoring of retail centres from “high†to “low†, a new multidimensional typology of retail and consumption spaces was developed. Non-hierarchical clustering techniques were used to develop an understanding of consumption spaces in terms of four dimensions derived from the literature: a centre’s composition, its diversity, size and function, and its economic health. There seems to be a consensus that such more comprehensive classifications that capture the interrelationship between supply and demand for retailing services, would help to deliver more effective insights into changing role of retailing and consumer services in urban areas across space and through time and will have implicationns for a variety of stakeholders

Keywords: Economics and Finance; Geography; Innovations and Technology; Research Methods; Urban and Regional Studies (search for similar items in EconPapers)
Date: 2021
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