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Artificial Intelligence-Powered Tools for Personalized Product Recommendations in E-Commerce: The Role of User Satisfaction on Online Purchase Decisions

dc.contributor.authorMischin, Julia
dc.contributor.authorDeirmentzoglou, Georgios A
dc.contributor.authorDaskou, Sofia
dc.contributor.authorVlassi, Eirini
dc.date.accessioned2025-11-14T07:32:52Z
dc.date.available2025-11-14T07:32:52Z
dc.date.issued2025-06-25
dc.identifier.urihttp://hdl.handle.net/11728/13246
dc.description.abstractSince their inception, e-commerce platforms have been continuously innovating to enhance the user experience. The application of artificial intelligence (AI) in various areas of digital marketing, especially in personalization tactics, is a key part of online businesses digital transformation. The growing use of AI-powered tools has had a significant effect on consumer behavior and is therefore becoming an emerging area that merits empirical and theoretical exploration. AI-powered person alization influences consumer experiences and decision-making. However, as the use of AI tools in e-commerce has grown rapidly in recent years, more research is needed in this area. This study, is a quantitative online survey of 182 German e-commerce users, investigating the role of user satisfaction on online purchase decisions. The data analysis shows that satisfaction in using AI-powered tools has a significant posi tive impact on online purchase decisions. This finding highlights the importance of implementing AI-powered chatbots and product recommendation systems in online stores.en_UK
dc.language.isoenen_UK
dc.publisherSpringer Natureen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectArtificial intelligenceen_UK
dc.subjectPersonalized product recommendationsen_UK
dc.subjectUser satisfactionen_UK
dc.subjectOnline purchase decisionen_UK
dc.subjecte-commerceen_UK
dc.subjectDigital marketingen_UK
dc.titleArtificial Intelligence-Powered Tools for Personalized Product Recommendations in E-Commerce: The Role of User Satisfaction on Online Purchase Decisionsen_UK
dc.typeArticleen_UK
dc.doihttps://doi.org/10.1007/978-3-031-90054-9_15en_UK


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