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dc.contributor.authorAkter, S
dc.contributor.authorFosso Wamba S,
dc.contributor.authorGunasekaran A,
dc.contributor.authorDubey R,
dc.contributor.authorChilde, Stephen J
dc.date.accessioned2016-10-03T10:16:24Z
dc.date.issued2016-12-01
dc.identifier.issn0925-5273
dc.identifier.issn1873-7579
dc.identifier.urihttp://hdl.handle.net/10026.1/5545
dc.description.abstract

The recent interest in big data has led many companies to develop big data analytics capability (BDAC) in order to enhance firm performance (FPER). However, BDAC pays off for some companies but not for others. It appears that very few have achieved a big impact through big data. To address this challenge, this study proposes a BDAC model drawing on the resource-based theory (RBT) and the entanglement view of sociomaterialism. The findings show BDAC as a hierarchical model, which consists of three primary dimensions (i.e., management, technology, and talent capability) and 11 subdimensions (i.e., planning, investment, coordination, control, connectivity, compatibility, modularity, technology management knowledge, technical knowledge, business knowledge and relational knowledge). The findings from two Delphi studies and 152 online surveys of business analysts in the U.S. confirm the value of the entanglement conceptualization of the higher-order BDAC model and its impact on FPER. The results also illuminate the significant moderating impact of analytics capability–business strategy alignment on the BDAC–FPER relationship.

dc.format.extent113-131
dc.languageen
dc.language.isoen
dc.publisherElsevier BV
dc.subjectCapabilities
dc.subjectEntanglement view
dc.subjectBig data analytics
dc.subjectHierarchical modeling
dc.titleHow to improve firm performance using big data analytics capability and business strategy alignment?
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000389090400009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue0
plymouth.volume182
plymouth.publication-statusPublished
plymouth.journalInternational Journal of Production Economics
dc.identifier.doi10.1016/j.ijpe.2016.08.018
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business/Plymouth Business School
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA17 Business and Management Studies
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2016-08-17
dc.rights.embargodate2018-2-21
dc.identifier.eissn1873-7579
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1016/j.ijpe.2016.08.018
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2016-12-01
rioxxterms.typeJournal Article/Review


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