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.

The use of technology in assisting educators to use student data in well-devised ways to enhance the instruction received by students is gaining headway and the support of federal dollars across the nation. Since research has not provided insight as to whether or not reading coaches are using data technology tools with teachers, this mixed methods study sought to examine what behavioral intentions reading coaches have in using data technology tools with teachers, what variables may influence their behavioral intentions, and what trends may emerge in their views about using technology data tools with teachers. A mixed methods approach was deployed via a survey embedded in an email, and data from 61 Florida reading coaches from elementary, middle, and high schools in a large urban school district were examined using an adaptation of the Technology Acceptance Model (TAM). The results showed that collectively all reading coaches have a high level of behavioral intentions towards using a data technology tool with teachers. The study also showed that elementary, middle, and high school reading coaches vary in their degree of behavioral intentions in using a data technology tool based on different variables. Trends in data showed that reading coaches think data technology tools are helpful, but that trainings are needed and that technology tools should be user-friendly. Discussion is provided regarding the implications of the study results for all stakeholders.