Conducting Trade Area Analysis Using Mobile Data: The Case of Michigan’s Super-Regional Shopping Centres

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dc.contributor.authorAzmy, Ali
dc.contributor.authorAversa, Joe
dc.contributor.authorHernandez, Tony
dc.date.accessioned2023-12-26T18:47:23Z
dc.date.available2023-12-26T18:47:23Z
dc.date.issued2024-01-03
dc.identifier.doihttps://doi.org/10.24251/HICSS.2024.676
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other0b2c378b-30f7-46fd-9520-6f48e6b2c748
dc.identifier.urihttps://hdl.handle.net/10125/107061
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectGeospatial Big Data Analytics
dc.subjectmobile location data
dc.subjectshopping centers
dc.subjectspatial big data
dc.subjecttrade area analysis
dc.titleConducting Trade Area Analysis Using Mobile Data: The Case of Michigan’s Super-Regional Shopping Centres
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractThe increasing availability of spatial big data has revolutionized data analytics and provided valuable insights into consumer behaviour. Spatial big data has enabled retailers to optimize product assortment, pricing, site selection, and trade area analysis. Mobile location data has further enhanced the analysis of individual consumer mobility patterns, offering a more detailed understanding of movement in various contexts. However, using mobile location data for trade area analysis in retail remains understudied. This study aims to fill this gap by employing advanced methods of trade area analysis using mobile location data. Two research questions guide the study: 1) How effective is mobile location data in modelling shopping centre trade area activity? and 2) How reliable are the derived metrics in reflecting changes in trade area consumer traffic patterns during and after the global COVID-19 pandemic? By addressing these questions, this study enhances our understanding of the potential of mobile location data for trade area analysis in retail. It provides insights into consumer behaviour dynamics during the pandemic.
dcterms.extent8 pages
prism.startingpage5611

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