Vis enkel innførsel

dc.contributor.authorMikalef, Patrick
dc.contributor.authorBoura, Maria
dc.contributor.authorLekakos, George
dc.contributor.authorKrogstie, John
dc.date.accessioned2020-01-21T13:18:15Z
dc.date.available2020-01-21T13:18:15Z
dc.date.created2019-12-18T14:29:22Z
dc.date.issued2019
dc.identifier.isbn978-0-9966831-8-0
dc.identifier.urihttp://hdl.handle.net/11250/2637259
dc.description.abstractWith big data analytics growing rapidly in importance, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Early empirical evidence suggests that big data analytics can enhance a firm’s performance; yet, there is a lack of understanding on complementary organizational factors coalesce to drive performance gains, under what conditions they are more appropriate, as well as how they can complement a firm's dynamic capabilities under turbulent and fast-paced market conditions. To address this question, this study builds on the big data analytics capability literature and examines the fit between big data analytics resources and governance practices, dynamic capabilities, and environmental conditions in driving performance gains. Survey data from 175 chief information officers and IT managers working in Greek firms is analyzed by means of fuzzy set qualitative comparative analysis (fsQCA). Results show that that different configurations of resources, practices, and external factors coalesce to drive performance gains. We show that there are multiple configurations that can lead in high and low levels of performance.nb_NO
dc.language.isoengnb_NO
dc.publisherAssociation for Information Systemsnb_NO
dc.relation.ispartofAMCIS 2019 PROCEEDINGS
dc.titleConfigurations of Big Data Analytics for Firm Performance: An fsQCA approachnb_NO
dc.typeChapternb_NO
dc.description.versionpublishedVersionnb_NO
dc.identifier.cristin1762593
dc.description.localcodeThis article will not be available due to copyright restrictions (c) 2019 by Association for Information Systemsnb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel