Temporal and spatial distribution of spending in the city using bank cards transactions

dc.contributor.authorde las Obras-Loscertales, Julia
dc.contributor.authorGarcía Palomares, Juan Carlos
dc.contributor.authorRamiro-Fariñas, Diego
dc.contributor.authorHernández Martín-Caro, María Soledad
dc.contributor.authorGutiérrez Puebla, Javier
dc.date.accessioned2026-03-02T14:32:54Z
dc.date.available2026-03-02T14:32:54Z
dc.date.issued2026-02-27
dc.description.abstractDespite the economic, social, and symbolic importance of urban consumption, its study has been constrained by the lack of sources with sufficient spatial and temporal resolution until the emergence of new Big Data sources. However, most studies rely on static analyses, limiting spatiotemporal understanding. Using bank card transactions, this study examines the temporal, spatial, and spatiotemporal distribution of consumption in the city of Madrid, by consumer type and commercial sector. Likewise, through the use of time series clustering techniques and Sequence Alignment Analysis, different types of consumption spaces have been identified according to the daily spending patterns and the sequence of the predominant commercial sectors, respectively. The results reveal different hourly distributions by the day of the week, as well as varying spatial distributions by sector, consumer type, and time of day. By jointly analysing temporal rhythms and sectoral sequences, the study moves beyond conventional classifications of urban commercial areas, allowing the definition of spatial typologies that highlight of consumption peaks, the predominant commercial sector at different times, and behaviour during the night and weekends are of great importance in characterising these spaces. The study demonstrates that analysing bank card transaction data and incorporating a spatiotemporal approach provides insights for urban managers and planners.
dc.description.departmentDepto. de Geografía
dc.description.facultyFac. de Geografía e Historia
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.citationde las Obras-Loscertales, J., García-Palomares, J.C., Ramiro-Fariñas, D., Hernández Martín-Caro, M.ªS., & Gutiérrez, J. (2026). Temporal and spatial distribution of spending in the city using bank cards transactions. Boletín de la Asociación de Geógrafos Españoles,(108). https://doi.org/10.21138/bage.3704
dc.identifier.doi10.21138/bage.3704
dc.identifier.officialurlhttps://bage.age-geografia.es/ojs/index.php/bage/article/view/3704/1111113249
dc.identifier.urihttps://hdl.handle.net/20.500.14352/133671
dc.journal.titleBoletín de la Asociación de Geógrafos Españoles
dc.language.isoeng
dc.page.final33
dc.page.initial1
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-148339OB-I00/ES/ANALISIS DEL DINAMISMO DE LA CIUDAD A PARTIR DE DATOS DE ALTA RESOLUCION ESPACIO-TEMPORAL Y UNA PERSPECTIVA SOCIAL/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-127499OB-I00/ES/ANALISIS DE LA MOVILIDAD TURISTICA A PARTIR DE BIG DATA GEOLOCALIZADO: EL IMPACTO DE LA PANDEMIA DEL COVID19/
dc.relation.projectID511/2023/10901- Servicio de apoyo a la explotación y análisis estadístico del gasto en la ciudad de Madrid
dc.relation.projectIDFPU21/04291
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu911.3:33
dc.subject.keywordconsumption
dc.subject.keywordBig Data
dc.subject.keywordspatiotemporal patterns
dc.subject.keywordMadrid
dc.subject.ucmGeografía
dc.subject.ucmGeografía humana
dc.subject.ucmGeografía económica
dc.subject.unesco2505 Geografía
dc.titleTemporal and spatial distribution of spending in the city using bank cards transactions
dc.typejournal article
dc.volume.number108
dspace.entity.typePublication
relation.isAuthorOfPublicationb25b5524-305e-4aa0-a30e-5b15a398806c
relation.isAuthorOfPublication0b4c21b2-a5c3-4dfb-8088-c1ba13c4dd17
relation.isAuthorOfPublication.latestForDiscoveryb25b5524-305e-4aa0-a30e-5b15a398806c

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