A network-based prediction of retail stores commercial categories and optimal locations

Abstract

I study the spatial organization of retail commercial activities. These are organized in a network comprising "anti-links", i.e. links of negative weight. From pure location data, network analysis leads to a community structure that closely follows the commercial classification of the US Department of Labor. The interaction network allows to build a 'quality' index of optimal location niches for stores, which has been empirically tested.

4 pages, 3 figures, Phys Rev E Rapid Comm, accepted

References in corpus (4)

• Finding and evaluating community structure in networks
• Defining and identifying communities in networks
• Detecting fuzzy community structures in complex networks with a Potts model
• Characterization and Modeling of weighted networks

Cited by in corpus (19)

• Community detection in networks with positive and negative links
• Modeling urban street patterns
• Analysis of community structure in networks of correlated data
• Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement
• Understanding mobility in a social petri dish
• Co-evolution of density and topology in a simple model of city formation
• Patterns of residential segregation
• Urban retail dynamics: insights from percolation theory and spatial interaction modelling
• Predicting the temporal activity patterns of new venues
• Store Location Selection via Mining Search Query Logs of Baidu Maps
• Spatio-temporal analysis of micro economic activities in Rome reveals patterns of mixed-use urban evolution
• Multiple Partitioning of Multiplex Signed Networks: Application to European Parliament Votes
• Multiplicity and Diversity: Analyzing the Optimal Solution Space of the Correlation Clustering Problem on Complete Signed Graphs
• Whole-Graph Representation Learning For the Classification of Signed Networks
• Topological Properties and Temporal Dynamics of Place Networks in Urban Environments
• Tracking Urban Activity Growth Globally with Big Location Data
• Symmetry-breaking phase transition in a dynamical decision model
• Modelling Cooperation and Competition in Urban Retail Ecosystems with Complex Network Metrics
• Modelling Urban Dynamics with Multi-Modal Graph Convolutional Networks