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dc.contributor.authorConboy, Kieran
dc.contributor.authorMikalef, Patrick
dc.contributor.authorDennehy, Denis
dc.contributor.authorKrogstie, John
dc.date.accessioned2020-02-28T12:20:29Z
dc.date.available2020-02-28T12:20:29Z
dc.date.created2019-12-02T19:46:25Z
dc.date.issued2019
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/11250/2644379
dc.description.abstractWhile the topic of analytics is rapidly growing in popularity across various domains, there is still a relatively low amount of empirical work in the field of operations research (OR). While studies of various technical and business aspects of analytics are emerging in OR, little has been done to address how the OR community can leverage business analytics in dynamic and uncertain environments – the very place where OR is supposed to play a key role. To address this gap, this study draws on the dynamic capabilities view of the firm and builds on eight selected case studies of operations research activity in large organisations, each of which have invested significantly in analytics technology and implementation. The study identifies fourteen analytics-enabled micro-foundations of dynamic capabilities, essentially highlighting how organisations can use analytics to manage and enhance their OR activities in dynamic and uncertain environments. This study also identifies six key cross-cutting propositions emerging from the data and develops a roadmap for future OR researchers to address these issues and improve the use and value of analytics as enablers of organisational dynamic capabilities.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleUsing business analytics to enhance dynamic capabilities in operations research: A case analysis and research agendanb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.volume281nb_NO
dc.source.journalEuropean Journal of Operational Researchnb_NO
dc.source.issue3nb_NO
dc.identifier.doi10.1016/j.ejor.2019.06.051
dc.identifier.cristin1755724
dc.description.localcode© 2019. This is the authors’ accepted and refereed manuscript to the article. Locked until 2.72021 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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