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dc.contributor.authorPappas, Ilias
dc.contributor.authorThapa, Devinder
dc.date.accessioned2021-09-30T05:53:10Z
dc.date.available2021-09-30T05:53:10Z
dc.date.created2021-09-29T15:05:03Z
dc.date.issued2021
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/11250/2786413
dc.description.abstractThis paper proposes a theoretical framework to identify the mechanisms by which actors perceive the affordances of big data analytics (BDA) and how institutional voids and supports enable or hinder the actualisation of those perceived affordances. In doing so, we contribute to identifying the missing link needed to understand the social innovation process in relation to BDA. The framework paves the ground towards understanding the institutionalization process of social innovation and its implications for research and practice.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titleBig Data Analytics Affordances for Social Innovation: A Theoretical Frameworken_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThis is the authors' accepted manuscript to an article published by Springer.en_US
dc.source.journalLecture Notes in Computer Science (LNCS)en_US
dc.identifier.doi10.1007/978-3-030-85447-8_13
dc.identifier.cristin1940698
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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