A Modified DBSCAN Clustering Method to Estimate Retail Center Extent

This research introduces a new method for the identification of local retail agglomerations within Great Britain, implementing a modification of the established density based spatial clustering of applications with noise (DBSCAN) method that improves local sensitivity to variable point densities. The variability of retail unit density can be related to both the type and function of retail centers, but also to characteristics such as size and extent of urban areas, population distribution, or property values. The suggested method implements a sparse graph representation of the retail unit locations based on a distance‐constrained k‐nearest neighbor adjacency list that is subsequently decomposed using the Depth First Search algorithm. DBSCAN is iteratively applied to each subgraph to extract the clusters with point density closer to an overall density for each study area. This innovative approach has the advantage of adjusting the radius parameter of DBSCAN at the local scale, thus improving the clustering output. A comparison of the estimated retail clusters against a sample of existing boundaries of retail areas shows that the suggested methodology provides a simple yet accurate and flexible way to automate the process of identifying retail clusters of varying shapes and densities across large areas; and by extension, enables their automated update over time

Integrating the who, what, and where of U.S. retail center geographies

Retail is an important function at the core of urban areas, occupying a key role in determining their economic prosperity, desirability, and vibrancy. Efforts to understand the geographies of retail centers, the cores of retailing in urban areas, have a long academic tradition, often studied through either rich local case studies, or when geographically more expansive, are constrained by limited detail. New data in United States detailing the location and uses of retail creates a significant opportunity to develop a more complete and comprehensive overview of the national retail system, at a high spatial resolution. This research is rooted in a pragmatic effort to provide the first and most comprehensive model of U.S. retail center geographies, through development of an integrated, conceptual, and empirically grounded framework, using data from SafeGraph, to examine where they are located, what characteristics they have, and who uses them. The resulting geographies are of great interest, creating significant potential in the monitoring of the national retail system as it continues to evolve in response to wider structural challenges. Furthermore, by integrating these three geographies (where, what, and who), we establish a conceptual framework that yields substantive insights about the relationships between each of them, and argues that understandings of U.S. retail center geographies are more comprehensive and useful when considering the who, what, and where together

Beyond retail: New ways of classifying UK shopping and consumption spaces

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

Local European cultivars as sources of durable scab resistance in apple

The Vf resistance gene has been widely used in apple breeding programmes to control Venturia inaequalis, the causal agent of scab, the major apple disease. Since the appearance of new strains that are able to overcome this major gene, research in Europe has been focused on durable resistance. The objective of one task of the European DARE project was to find cultivars which show a broad spectrum of resistance to the different scab races. This collaborative work involved 6 partners who tested 36 cultivars with various local scab inocula collected in the participating countries and with 8 monoconidial strains belonging to known races or isolated and characterized in the frame of the DARE project. Tests were performed each year from 1998 to 2001. Symptoms were assessed using macroscopic scoring scales. Some microscopic observations were performed; these resulted in a better knowledge of the host/pathogen interaction. Very diverse and complex resistance behaviours were found: the cultivars which showed the widest range of resistance were mostly local cultivars and some newly selected hybrids combining major genes and partial resistance. It would be worthwhile to include these individuals as parents in apple breeding programmes to improve the durability of scab resistance. Some methodologies and strategies to reach this goal will be proposed

An open source delineation and hierarchical classification of UK retail agglomerations.

Town centres and high streets typically form the social and commercial cores of UK cities and towns, yet, there is no uniform definition of what a town centre or high street is. In this study the spatial delineations of retail agglomerations are generated using open-source data for England, Wales, Scotland and Northern Ireland. The extent and boundaries of these physical retail areas are identified based on the density and connectivity patterns of individual retail units over space. A high resolution hexagonal grid is superimposed over spatial clusters of retail points and a network-based algorithm used to identify mutually exclusive tracts. Agglomerations are then pruned and fine-tuned according to a series of heuristic rules. Our retail agglomerations represent local commerce areas with shopping amenities and are assigned to a hierarchical classification ranking from the largest Regional Centres, Major Town Centres and Town Centres, down to Small Local Centres and Retail Parks. The classification into one of eleven hierarchies is based on a combination of relative rank in the local area and absolute size of retail units within the area. These retail agglomeration boundaries, hierarchical classification and lookups form an open-source spatial data product available for wide use and research implementation

Performance within a recession: The converging trajectories of retail centres in the UK

Using retail-centre aggregated microeconomic data for over 65,000 retail and service units in the UK, we explore the differential influence of the 2007/8 economic recession on the performance of retail centres. For the first time in the context on town centre/high street analyses of performance, we employ growth and convergence models to examine whether centres with different vacancy rates in the pre-recession period converged in the recession period that followed. The results indicate that the recession had higher negative influence on those centres that experienced lower retail vacancy rates in the pre-recession period, leading to convergence in retail vacancy rates. Despite the negative effect of recession in the UK retail market, the results show that there were some retail centres which were resilient to the effects of recession. Finally, there is evidence that the location and the size of retail centres moderate the convergence path. © 2018 The Author(s). Regional Science Policy and Practice © 2018 RSA

Beyond retail: new ways of classifying UK shopping and consumption spaces

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

Measuring the spatial vulnerability of retail centres to online consumption through a framework of e-resilience

This paper presents e-resilience as a framework for assessing the extent to which retail centres have spatially differentiated vulnerability to the impacts of online consumption. This extends the conceptual model of resilience as applied to retail, and is operationalised through a novel methodology that develops two indices that balance both supply and demand influences. We describe the creation of a composite e-resilience indicator, and then calculate it for retail centres across England. Our findings suggest a geographic polarising effect, with least vulnerable centres identified as large and more attractive or as smaller local destinations with a focus on convenience shopping. Mid-sized centres were typically shown to be the most exposed, and are argued as having a less clearly defined function in contemporary retail. Such findings have wide policy relevance to stakeholders of retail interested in the future configuration of sustainable and resilient provision