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dc.contributor.authorGreenley, Neil
dc.date.accessioned2015-08-20T14:18:54Z
dc.date.available2015-08-20T14:18:54Z
dc.date.issued2015-08-20
dc.identifier.urihttp://hdl.handle.net/2299/16332
dc.description.abstractThe aim of this research is to investigate the extent to which Open Source Software (OSS) adoption behaviour can empirically be shown to be governed by a set of self-reported (driving and inhibiting) salient beliefs of key informants in a sample of organisations. Traditional IS adoption/usage theory, methodology and practice are drawn on. These are then augmented with theoretical constructs derived from IT governance and organisational diagnostics to propose an artefact that aids the understanding of organisational OSS adoption behaviour, stimulates debate and aids operational management interventions. For this research, a combination of quantitative methods (via Fisher’s Exact Test) and complimentary qualitative method (via Content Analysis) were used using self-selection sampling techniques. In addition, a combination of data and methods were used to establish a set of mixed-methods results (or meta-inferences). From a dataset of 32 completed questionnaires in the pilot study, and 45 in the main study, a relatively parsimonious set of statistically significant driving and inhibiting factors were successfully established (ranging from 95% to 99.5% confidence levels) for a variety for organisational OSS adoption behaviours (i.e. by year, by software category and by stage of adoption). In addition, in terms of mixed-methods, combined quantitative and qualitative data yielded a number of factors limited to a relatively small number of organisational OSS adoption behaviour. The findings of this research are that a relatively small set of driving and inhibiting salient beliefs (e.g. Security, Perpetuity, Unsustainable Business Model, Second Best Perception, Colleagues in IT Dept., Ease of Implementation and Organisation is an Active User) have proven very accurate in predicting certain organisational OSS adoption behaviour (e.g. self-reported Intention to Adopt OSS in 2014) via Binomial Logistic Regression Analysis.en_US
dc.language.isoenen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectadoptionen_US
dc.subjectusageen_US
dc.subjectinformation technology governanceen_US
dc.subjectdriving factorsen_US
dc.subjectinhibiting factorsen_US
dc.subjecttheory of planned behaviouren_US
dc.subjectforce field analysisen_US
dc.subjectopen source softwareen_US
dc.subjectorganisationsen_US
dc.subjectpragmatismen_US
dc.subjectmixed methodsen_US
dc.subjectfisher exact testen_US
dc.subjectnon-parametricen_US
dc.titleDriving and Inhibiting Factors in the Adoption of Open Source Software in Organisationsen_US
dc.typeinfo:eu-repo/semantics/doctoralThesisen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnameDBAen_US
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