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Title: Driving and inhibiting factors in the adoption of open source software in organisations
Author: Greenley, Neil
ISNI:       0000 0004 5354 2225
Awarding Body: University of Hertfordshire
Current Institution: University of Hertfordshire
Date of Award: 2015
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The 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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (D.B.A.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: adoption ; usage ; information technology governance ; driving factors ; inhibiting factors ; theory of planned behaviour ; force field analysis ; open source software ; organisations ; pragmatism ; mixed methods ; fisher exact test ; non-parametric