THESIS TITLE:  Grid Computing Adoptability Model For Collaborative Research in Universities


Student Name:  Nicholas Kipkurui Kiget



  1. Simon Karume, PhD
  2. Gilbert Barasa Mugeni, PhD
  3. Ikoha P. Anselemo



Grid Computing is a paradigm in distributed computing that is appropriate for collaborative research in universities. It is a technology which provides a platform on which computing resources from heterogeneous systems are brought together as needed by the users.  Grid Computing, therefore, provides a computing platform on which collaborating researchers requiring huge computing resources can work.  Though grid as computing technology portends great benefits to universities, especially to the developing countries, it has challenges in its adoption.  A number of universities are in the process of adopting this technology however appropriate model to make the process easily achievable is lacking.  This study focused on developing a grid computing adoption model for collaborative research in Universities.  The study had five objectives; first, was to find out how universities that participated n UNESCO-HP brain gain in HP catalyst initiatives engaged in collaborative research; secondly, was to determine the extent of grid adoption in the selected universities thirdly evaluate critical success factors for adoptability of grid computing for collaborative research; fourthly was to develop grid adoptability model for collaborative research in universities in developing countries; and fifthly was to develop a tool that could be used to assess level of adoption of grid computing in the universities.  The study based on post-positivist philosophy adopted mixed methodology and survey design.  The target population of this study was the universities in developing countries.  East Africa was used as a cluster zone and four Universities that participated in UNESCO-HP Brain Gain and HP Catalyst initiatives wee purposely selected as a sample.  The universities choses were Masinde Muliro Univrsity of Science and Technology and the University  of Nairobi in Kenya, Makerere University and Mbarara University of Science and Technology in Uganda.  The instruments used were structured questionnaires and interview guides which were administered to respondents in the selected universities.  Cronbach’s alpha test was carried out to ensure the reliability of the research instrument and the model was validated by the experts.  Both descriptive statistics such as frequencies, means, modes and standard deviations and inferential statistics particularly correlation and regression analysis were used for both quantitative and qualitative data.  While the findings showed that grid computing had not been fully adopted in the universities, six critical factors affecting its adoptability were established; perceived benefits,, perceived need, availability  of collaborative research, availability of computational resources, policies and staff training on collaborative research and grid computing.  Another factor found to positively impact on grid computing adoption was the level of education of the researchers.  As an output of the study, an adoptability model was developed.  In addition, the model was used to develop an innovative tool that could be used to show the level of adoption of grid technology in universities

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