Towards a new urban geography of expenditure: Using bank card transactions data to analyze multi-sector spatiotemporal distributions

• Published in: Cities Vol. 131; p. 103894
• Main Authors: Carpio-Pinedo, José, Romanillos, Gustavo, Aparicio, Daniel, Martín-Caro, María Soledad Hernández, García-Palomares, Juan Carlos, Gutiérrez, Javier
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2022
• Subjects: Big data; Economic geography; Madrid; Retailing; Shopping centers; Spatial analysis; Transactions data; Shopping centers; Transactions data; Economic geography; Madrid; Spatial analysis; Big data; Retailing
• ISSN: 0264-2751; 1873-6084
• DOI: 10.1016/j.cities.2022.103894

The spatial distribution of commercial activities is vital to support healthy lifestyles and to achieve livable public spaces and environmental, social and economic sustainability in our cities. However, commercial activities require a constant flow of expenditure for their own viability. As a result, understanding the spatial and temporal distribution of expenditure is fundamental, although the lack of detailed, complete data sources has impeded this task until now. Bank card data paves the way for a new urban geography of expenditure, thanks to its fine spatial and temporal granularity along with the uniform coverage of all commercial sectors. In this paper, we analyze temporal, spatial, and spatiotemporal distributions of expenditure at the intraurban scale of the city of Madrid (Spain), combining spatial statistical tools (Getis-Ord General for global autocorrelation and Getis-Ord Gi* hot spot analysis for local autocorrelation) with k-means cluster analysis and spatiotemporal tools (Time Series Clustering analysis and Temporal Hot Spot Analysis). Our analysis confirms the strong center-periphery gradient described in previous literature, but with a CBD integrated by distinct specialized areas. The paper demonstrates that bank card data has a great potential to support a new geography of expenditure that could strengthen decision-making in planning and retailing. [Display omitted] •Bank card data supports novel, improved, geographical analysis of expenditure.•Spatial and temporal granularity gain detail, also disaggregated by sector.•Center-periphery gradient patterns, but a greater complexity within the CBD.•Spatiotemporal analyses uncover areas with similar expenditure across time.