Show simple item record

dc.contributor.authorMoodley, Raymond
dc.contributor.authorChiclana, Francisco
dc.contributor.authorCaraffini, Fabio
dc.contributor.authorCarter, Jenny
dc.date.accessioned2019-10-07T10:06:05Z
dc.date.available2019-10-07T10:06:05Z
dc.date.issued2019-10-03
dc.identifier.citationMoodley, R., Chiclana, F., Caraffini, F. and Carter, J. (2019) A product-centric data mining algorithm for targeted promotions. Journal of Retailing and Consumer Services, 101940en
dc.identifier.issn0969-6989
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/18560
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractTargeted promotions in retail are becoming increasingly popular, particularly in the UK grocery retail sector where competition is stiff and consumers remain price sensitive. Given this, a targeted promotion algorithm is proposed to enhance the effectiveness of promotions by retailers. The algorithm leverages a mathematical model for optimizing items to target and fuzzy c-means clustering for finding the best customers to target. Tests using simulations with real life consumer scanner panel data from the UK grocery retailer sector shows that the algorithm performs well in finding the best items and customers to target whilst eliminating "false positives" (targeting customers who do not buy a product) and reducing "false negatives" (not targeting customers who could buy). The algorithm also shows better performance when compared to a similar published framework, particularly in handling "false positives" and "false negatives". The paper concludes by discussing managerial and research implications, and highlights applications of the model to other fields.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectAssociation rule miningen
dc.subjecttargeted marketingen
dc.subjectclusteringen
dc.titleA product-centric data mining algorithm for targeted promotionsen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1016/j.jretconser.2019.101940
dc.peerreviewedYesen
dc.funderNo external funderen
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2019-08-27
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record