Big Data Analytics and Firm Performance: A Systematic Review

dc.date.accessioned2019-09-10T13:37:53Z
dc.date.available2019-09-10T13:37:53Z
dc.date.issued2019-07-01
dc.description.sponsorshipGefördert durch den Publikationsfonds der Universität Kassel
dc.identifierdoi:10.17170/kobra-20190910680
dc.identifier.urihttp://hdl.handle.net/123456789/11310
dc.language.isoeng
dc.relation.doidoi:10.3390/info10070226
dc.rightsUrheberrechtlich geschützt
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectbig data analyticseng
dc.subjectbusiness analyticseng
dc.subjectfirm performanceeng
dc.subjecttechnology adoptioneng
dc.subjectsystematic revieweng
dc.subject.ddc330
dc.titleBig Data Analytics and Firm Performance: A Systematic Revieweng
dc.typeAufsatz
dc.type.versionpublishedVersion
dcterms.abstractThe literature on big data analytics and firm performance is still fragmented and lacking in attempts to integrate the current studies’ results. This study aims to provide a systematic review of contributions related to big data analytics and firm performance. The authors assess papers listed in the Web of Science index. This study identifies the factors that may influence the adoption of big data analytics in various parts of an organization and categorizes the diverse types of performance that big data analytics can address. Directions for future research are developed from the results. This systematic review proposes to create avenues for both conceptual and empirical research streams by emphasizing the importance of big data analytics in improving firm performance. In addition, this review offers both scholars and practitioners an increased understanding of the link between big data analytics and firm performance.eng
dcterms.accessRightsopen access
dcterms.creatorMaroufkhani, Parisa
dcterms.creatorWagner, Ralf
dcterms.creatorIsmail, Wan Khairuzzaman Wan
dcterms.creatorBaroto, Mas Bambang
dcterms.creatorNourani, Mohammad
dcterms.source.identifierISSN 2078-2489
dcterms.source.issueIssue 7
dcterms.source.journalInformationeng
dcterms.source.pageinfo226
dcterms.source.volumeVolume 10

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