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dc.contributor.authorLawan, Mahmud
dc.contributor.authorOduoza, Chike
dc.contributor.authorBuckley, Kevan
dc.date.accessioned2020-06-23T14:14:51Z
dc.date.available2020-06-23T14:14:51Z
dc.date.issued2020-11-19
dc.identifier.citationLawan, M.M., Oduoza, C.F. and Buckley, K. (2020) Conceptual model for cloud computing adoption in upstream oil & gas sector, Procedia Manufacturing, 51 (2020), pp. 953-959.en
dc.identifier.issn2351-9789en
dc.identifier.doi10.1016/j.promfg.2020.10.134
dc.identifier.urihttp://hdl.handle.net/2436/623283
dc.description© 2020 The Authors. Published by Elsevier. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1016/j.promfg.2020.10.134en
dc.description.abstractCloud computing is a paradigm which offers IT services such as storage, network and processing power via the internet. The technology has gained popularity in recent years with adoption in different sectors due to the numerous benefits it offers such as scalability, flexibility and cost reduction. Although some are quick adopters, others are considered cautious adaptors. The upstream oil and gas industry fall under the latter category due to some challenges with regards to adoption decision. Migrating to a cloud platform depends on a number of factors. A clear understanding of these factors is necessary to enable decision makers in the industry to be more proactive and appropriately guided in their plan towards adoption. Therefore, this study aims to identify the factors that may influence cloud adoption in the industry. A literature review was conducted in order to propose an integrated model, which is a combination of the Technology environment organisation (TOE) framework, institutional theory, and diffusion of innovation. The model groups the factors into three fundamental categories. In addition, the study reports benefits of the cloud technology in the upstream oil and gas sector, challenges hindering adoption, as well as approaches by earlier researchers to support cloud migration in the industry.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S2351978920319910en
dc.subjectcloud computingen
dc.subjectadoptionen
dc.subjectupstream oil and gas industryen
dc.titleProposing a conceptual model for cloud computing adoption in upstream oil & gas sectoren
dc.typeConference contributionen
dc.identifier.journalProcedia Manufacturingen
dc.date.updated2020-06-18T17:10:40Z
dc.conference.name30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021)
dc.conference.locationAthens, Greece
pubs.finish-date2020-06-18
pubs.start-date2020-06-15
dc.date.accepted2020-06-01
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW23062020COen
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-11-19en
refterms.dateFCD2020-06-23T14:14:23Z
refterms.versionFCDVoR
refterms.dateFOA2020-12-31T00:00:00Z


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