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dc.contributor.authorKristoffersen, Eivind
dc.contributor.authorMikalef, Patrick
dc.contributor.authorBlomsma, Fenna
dc.contributor.authorLi, Jingyue
dc.date.accessioned2021-07-20T09:04:28Z
dc.date.available2021-07-20T09:04:28Z
dc.date.created2021-06-21T12:24:46Z
dc.date.issued2021
dc.identifier.citationTechnological Forecasting and Social Change. 2021, 171, .en_US
dc.identifier.issn0040-1625
dc.identifier.urihttps://hdl.handle.net/11250/2764800
dc.description.abstractDigital technologies are growing in importance for accelerating firms’ circular economy transition. However, so far, the focus has primarily been on the technical aspects of implementing these technologies with limited research on the organizational resources and capabilities required for successfully leveraging digital technologies for circular economy. To address this gap, this paper explores the business analytics resources firms should develop and how these should be orchestrated towards a firm-wide capability. The paper proposes a conceptual model highlighting eight business analytics resources that, in combination, build a business analytics capability for the circular economy and how this relates to firms’ circular economy implementation, resource orchestration capability, and competitive performance. The model is based on the results of a thematic analysis of 15 semi-structured expert interviews with key positions in industry. Our approach is informed by and further develops, the theory of the resource-based view and the resource orchestration view. Based on the results, we develop a deeper understanding of the importance of taking a holistic approach to business analytics when leveraging data and analytics towards a more efficient and effective digital-enabled circular economy, the smart circular economy.en_US
dc.language.isoengen_US
dc.publisherElsevier Ltd.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleTowards a business analytics capability for the circular economyen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume171en_US
dc.source.journalTechnological Forecasting and Social Changeen_US
dc.identifier.doi10.1016/j.techfore.2021.120957
dc.identifier.cristin1917228
dc.description.localcodeThis is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.source.articlenumber120957en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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