Beyond retail: New ways of classifying UK shopping and consumption spaces. (January 2021)

• Record Type: Journal Article
• Authors: Dolega, Les; Reynolds, Jonathan; Singleton, Alex; Pavlis, Michalis
• Is Part Of: Environment & planning. Volume 48:Number 1(2021)
• Page Start: 132
• Page End: 150
• Publication Date: 2021-01
• Subjects: Retail -- typology -- town centres -- cluster analysis; City planning -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.11605
• DOI: 10.1177/2399808319840666
• Languages: English
• ISSNs: 2399-8083

Abstract

Early attempts to classify shopping activity often took a relatively simple approach, largely driven by the lack of reliable data beyond fascia name and retail outlet counts by centre. There seems to be a consensus amongst contemporary scholars, commercial research consultancies and retailers that more comprehensive classifications would generate better-informed debate on changes in the urban economic landscape, as well as providing the basis for a more effective comparison of retail centres across time and space, particularly given the availability of new data sources and techniques and in the context of the transformational changes presently affecting the retail sector. This paper seeks to demonstrate the interrelationship between supply and demand for retailing services by integrating newly available data sources within a rigorously specified classification methodology. This in turn provides new insight into the multidimensional and dynamic taxonomy of consumption spaces within Great Britain. First, such a contribution is significant in that it moves debate within the literature past simple linear scaling of retail centre function to a more nuanced understanding of multiple functional forms; and second, in that it provides a nationally comparative and dynamic framework through which the evolution of retail structures can be evaluated. Using non-hierarchical clustering techniques, the results are presented in the form of a two-tier classification with 5 distinctive 'coarse' clusters and 15 more detailed and nested sub-clusters. The paper concludes that more nuanced and dynamic classifications of this kind can help deliver more effective insights into changing role of retailing and consumer services in urban areas across space and through time and will have implications for a variety of stakeholders.