Structural equation modeling in cloud computing studies: a systematic literature review

buir.contributor.authorUçar, Erkan
buir.contributor.authorSevgi, Cüneyt
dc.contributor.authorPişirir, E.en_US
dc.contributor.authorUçar, Erkanen_US
dc.contributor.authorChouseinoglou, O.en_US
dc.contributor.authorSevgi, Cüneyten_US
dc.date.accessioned2020-02-10T11:49:36Z
dc.date.available2020-02-10T11:49:36Z
dc.date.issued2019
dc.departmentComputer Technology and Information Systemsen_US
dc.description.abstractPurpose – This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design. Design/methodology/approach – Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions. Findings – A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors. Originality/value – Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-02-10T11:49:36Z No. of bitstreams: 1 Structural_equation_modeling_in_cloud_computing_studies_a_systematic_literature_review.pdf: 1985686 bytes, checksum: 902d4e022e3146456d6c3fff7092f2d7 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-02-10T11:49:36Z (GMT). No. of bitstreams: 1 Structural_equation_modeling_in_cloud_computing_studies_a_systematic_literature_review.pdf: 1985686 bytes, checksum: 902d4e022e3146456d6c3fff7092f2d7 (MD5) Previous issue date: 2019en
dc.identifier.doi10.1108/K-12-2018-0663en_US
dc.identifier.issn0368-492X
dc.identifier.urihttp://hdl.handle.net/11693/53232
dc.language.isoEnglishen_US
dc.publisherEmeralden_US
dc.relation.isversionofhttps://dx.doi.org/10.1108/K-12-2018-0663en_US
dc.source.titleKybernetesen_US
dc.subjectSystematic literature reviewen_US
dc.subjectTechnology adoptionen_US
dc.subjectCloud computingen_US
dc.subjectStructural equation modelingen_US
dc.subjectContinuous technology usageen_US
dc.titleStructural equation modeling in cloud computing studies: a systematic literature reviewen_US
dc.typeReviewen_US

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