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dc.contributor.authorBurger, K
dc.contributor.authorWhite, L
dc.contributor.authorYearworth, M
dc.date.accessioned2019-03-19T13:20:24Z
dc.date.issued2019-03-27
dc.description.abstractThe growth of technology-rich data-driven decision environments is seen by some as a challenge to the future relevance of Operational Research. Extant research remains unspecific about the distinct contribution that Operational Research can make in environments that are influenced by big data, data science and analytics. This paper explores the possibility that these environments hold the potential for a new integrative Operational Research offering, which we conceptualise as Smart Operational Research. In developing this proposal, we combine automated co-occurrence analysis of a corpus of literature with human-driven data interpretation to identify instantiations of hybrid decision-making. We then bring theory and practice together to outline the Smart Operational Research framework with the overall aim to enhance actionable insight and positive results for Operational Research practitioners.en_GB
dc.identifier.citationVol. 277 (3), pp. 1137-1150.en_GB
dc.identifier.doi10.1016/j.ejor.2019.03.027
dc.identifier.urihttp://hdl.handle.net/10871/36571
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)en_GB
dc.subjectDecision processesen_GB
dc.subjectHybrid practice theoriesen_GB
dc.subjectDecision-supporten_GB
dc.subjectHybridityen_GB
dc.subjectCo-occurrence mappingen_GB
dc.titleDeveloping a Smart Operational Research with Hybrid Practice Theoriesen_GB
dc.typeArticleen_GB
dc.date.available2019-03-19T13:20:24Z
dc.identifier.issn0377-2217
dc.descriptionThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.en_GB
dc.identifier.journalEuropean Journal of Operational Researchen_GB
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dcterms.dateAccepted2019-03-19
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-03-19
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-03-19T12:01:33Z
refterms.versionFCDAM
refterms.dateFOA2019-03-21T13:23:22Z
refterms.panelCen_GB


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© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Except where otherwise noted, this item's licence is described as © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)