Urban association rules: Uncovering linked trips for shopping behavior

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• dc.contributor.author Yoshimura, Yuji, 1977-
• dc.contributor.author Sobolevsky, Stanislav
• dc.contributor.author Bautista Hobin, Juan N.
• dc.contributor.author Ratti, Carlo
• dc.contributor.author Blat, Josep
• dc.date.accessioned 2021-07-09T09:19:30Z
• dc.date.available 2021-07-09T09:19:30Z
• dc.date.issued 2018
• dc.description.abstract In this article, we introduce the method of urban association rules and its uses for extracting frequently appearing combinations of stores that are visited together to characterize shoppers’ behaviors. The Apriori algorithm is used to extract the association rules (i.e. if -> result) from customer transaction datasets in a market-basket analysis. An application to our large-scale and anonymized bank card transaction dataset enables us to output linked trips for shopping all over the city: the method enables us to predict the other shops most likely to be visited by a customer given a particular shop that was already visited as an input. In addition, our methodology can consider all transaction activities conducted by customers for a whole city. This approach enables us to uncover not only simple linked trips such as transition movements between stores but also the edge weight for each linked trip in the specific district. Thus, the proposed methodology can complement conventional research methods. Enhancing understanding of people’s shopping behaviors could be useful for city authorities and urban practitioners for effective urban management. The results also help individual retailers to rearrange their services by accommodating the needs of their customers’ habits to enhance their shopping experience.
• dc.format.mimetype application/pdf
• dc.identifier.citation Yoshimura Y, Sobolevsky S, Bautista Hobin JN, Ratti C, Blat J. Urban association rules: Uncovering linked trips for shopping behavior. Environ Plan B Urban Anal City Sci. 2018;45(2):367-85. DOI: 10.1177/0265813516676487
• dc.identifier.doi http://dx.doi.org/10.1177/0265813516676487
• dc.identifier.issn 2399-8083
• dc.identifier.uri http://hdl.handle.net/10230/48139
• dc.language.iso eng
• dc.publisher SAGE Publications
• dc.relation.ispartof Environment and Planning B-Urban Analytics and City Science. 2018;45(2):367-85
• dc.rights Yoshimura Y, Sobolevsky S, Bautista Hobin JN, Ratti C, Blat J. Urban association rules: Uncovering linked trips for shopping behavior. Environ Plan B Urban Anal City Sci. 2018;45(2):367-85. Copyright © 2018 The Author(s). DOI: 10.1177/0265813516676487
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Shopping behaviors
• dc.subject.keyword Association rule
• dc.subject.keyword Transaction data
• dc.subject.keyword Barcelona
• dc.title Urban association rules: Uncovering linked trips for shopping behavior
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion