Prediction of Propensity for Enterprise Cloud Computing Adoption

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dc.contributor.authorKyriakou, Niki
dc.contributor.authorMaragoudakis, Manolis
dc.contributor.authorLoukis, Euripidis
dc.contributor.authorThemistocleous, Marinos
dc.date.accessioned2016-12-29T01:50:40Z
dc.date.available2016-12-29T01:50:40Z
dc.date.issued2017-01-04
dc.description.abstractCloud computing (CC) can offer significant benefits to enterprises. However, it can pose some risks as well, and this has led to lower adoption than the initial expectations. For this reason, it would be very useful to develop ‘predictive analytics’ in this area, enabling us to predict which enterprises will exhibit a propensity for CC adoption. In this direction, we investigate the use of six well-established classifiers (fast large margin Support Vector Machine, Naive Bayes, Decision Tree, Random Forest, k-Nearest Neighbor, and Linear Regression) for the prediction of enterprise level propensity for CC adoption. Having as our theoretical foundation the Technology – Organization – Environment (TOE) framework, we are using for this prediction of set of technological (concerning existing enterprise information systems), organizational and environmental characteristics. Our first results, using a dataset collected from 676 manufacturing firms of the glass, ceramic and cement sectors from six European countries (Germany, France, Italy, Poland, Spain, and UK) through the e-Business W@tch Survey of the European Commission, are encouraging. It is concluded that among the examined characteristics the technological ones, concerning the existing enterprise systems, seem to be the most important predictors.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.596
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41758
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAdoption
dc.subjectCloud Computing
dc.subjectERP Systems
dc.titlePrediction of Propensity for Enterprise Cloud Computing Adoption
dc.typeConference Paper
dc.type.dcmiText

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