Identification of robust retailing location patterns with complex network approaches

Abstract

The problem of location is the cornerstone of strategic decisions in retail management. This decision is usually complex and multidimensional. One of the most relevant success factors is an adequate balanced tenancy, i.e., a complementary ecosystem of retail stores in the surroundings, both in planned and unplanned areas. In this paper, we use network theory to analyze the commercial spatial interactions in all the cities of Castile and Leon (an autonomous community in north-western Spain), Madrid, and Barcelona. Our approach encompasses different proposals both for the definition of the interaction networks and for their subsequent analyses. These methodologies can be used as pre-processing tools to capture features that formalize the relational dimension for location recommendation systems. Our results unveil the retail structure of different urban areas and enable a meaningful comparison between cities and methodologies. In addition, by means of consensus techniques, we identify a robust core of commercial relationships, independent of the particularities of each city, and thus help to distinguish transferable knowledge between cities. The results also suggest greater specialization of commercial space with city size.