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The future of TV-shopping: predicting user purchase intention through an extended technology acceptance model

dc.contributor.authorRodríguez López, María Eugenia 
dc.contributor.authorHigueras Castillo, Elena 
dc.contributor.authorRojas Lamorena, Álvaro José 
dc.contributor.authorAlcántara Pilar, Juan Miguel 
dc.date.accessioned2026-02-25T07:43:23Z
dc.date.available2026-02-25T07:43:23Z
dc.date.issued2024-01
dc.identifier.citationRodríguez-López, M. E., Higueras-Castillo, E., Rojas-Lamorena, Á. J., & Alcántara-Pilar, J. M. (2024). The future of TV-shopping: predicting user purchase intention through an extended technology acceptance model. Technological forecasting and social change, 198, 122986. https://doi.org/10.1016/j.techfore.2023.122986es_ES
dc.identifier.issn1873-5509
dc.identifier.issn0040-1625
dc.identifier.urihttps://hdl.handle.net/10481/111481
dc.descriptionThis work was supported by Research Group ADEMAR (SEJ.241) of University of Granada, Spain. Funding for open access charge: Universidad de Granada / CBUA.es_ES
dc.description.abstractThe shoppable TV, which allows the purchase of products appearing in TV programmes directly, is a digital trend that is not implemented in most markets, but companies such as Amazon and NBC Universal have proposed the first sales systems. The aim of this research is to forecast the adoption intention of this technology by applying the Technology Acceptance Model. Structural equation modelling (PLS-SEM) has been applied to a sample of 283 participants. The results indicate that shopping enjoyment is particularly important in generating attitudes toward this type of consumption, and this increases the intention to use Shoppable TV.es_ES
dc.description.sponsorshipUniversity of Granada (ADEMAR: SEJ.241)es_ES
dc.description.sponsorshipUniversidad de Granada / CBUAes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectTechnology Acceptance Model (TAM)es_ES
dc.subjectTV-shoppinges_ES
dc.subjectEnjoy shoppinges_ES
dc.titleThe future of TV-shopping: predicting user purchase intention through an extended technology acceptance modeles_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.techfore.2023.122986
dc.type.hasVersionAMes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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