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

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dc.contributor.authorCarpio Pinedo, Jose
dc.contributor.authorRomanillos Arroyo, Gustavo
dc.contributor.authorAparicio, Daniel
dc.contributor.authorHernández Martín-Caro, María Soledad
dc.contributor.authorGarcía Palomares, Juan Carlos
dc.contributor.authorGutiérrez Puebla, Javier
dc.date.accessioned2023-06-22T10:55:13Z
dc.date.available2023-06-22T10:55:13Z
dc.date.issued2022-08-10
dc.descriptionCRUE-CSIC (Acuerdos Transformativos 2022)
dc.description.abstractThe 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.
dc.description.departmentDepto. de Geografía
dc.description.facultyFac. de Geografía e Historia
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)//AEI/ 10.13039/501100011033
dc.description.sponsorshipComunidad de Madrid
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/74129
dc.identifier.doi10.1016/j.cities.2022.103894
dc.identifier.issn0264-2751
dc.identifier.officialurlhttps://doi.org/10.1016/j.cities.2022.103894
dc.identifier.urihttps://hdl.handle.net/20.500.14352/71888
dc.issue.number103894
dc.journal.titleCities
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectID(PID2020- 116656RB-I00)
dc.relation.projectIDINNJOBMAD-CM (H2019/HUM-5761)
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.keywordEconomic geography
dc.subject.keywordSpatial analysis
dc.subject.keywordBig data
dc.subject.keywordTransactions data
dc.subject.keywordRetailing
dc.subject.keywordShopping centers
dc.subject.keywordMadrid
dc.subject.ucmAnálisis Multivariante
dc.subject.ucmComercio
dc.subject.ucmEconomía regional
dc.subject.ucmGeografía económica
dc.subject.ucmGeografía
dc.subject.ucmGeografía humana
dc.subject.ucmGeografía regional
dc.subject.ucmSistemas de información geográfica
dc.subject.unesco1209.09 Análisis Multivariante
dc.subject.unesco5304.03 Comercio exterior
dc.subject.unesco5401 Geografía Económica
dc.subject.unesco2505 Geografía
dc.subject.unesco5403 Geografía Humana
dc.subject.unesco5404 Geografía Regional
dc.titleTowards a new urban geography of expenditure: Using bank card transactions data to analyze multi-sector spatiotemporal distributions
dc.typejournal article
dc.volume.number131
dspace.entity.typePublication
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relation.isAuthorOfPublicationb25b5524-305e-4aa0-a30e-5b15a398806c
relation.isAuthorOfPublication0b4c21b2-a5c3-4dfb-8088-c1ba13c4dd17
relation.isAuthorOfPublication.latestForDiscovery7af12201-dd9c-4deb-8f3e-16bacc43e6dd
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