Abstract: Cloud computing technology provides institutions improved access to information that will subsequently result in enhanced outcomes and increase savings on costs. There are also associated benefits like high flexibility, and scalability in coping with the high demand in the world. With cloud computing, it is now possible to get a share of offshore hardware, which is advanced in capabilities and features. The healthcare sector, just like other sectors, is getting services through cloud infrastructure and capabilities. The readily available resources when they are needed, are some of the benefits that come with the use of cloud computing. However, most institutions in Kenya have not adopted cloud computing, and thus, not achieved the envisioned benefits of cloud computing. The objective of this study was to determine framework for adoption of cloud computing in national referral hospitals in Kenya. The IBM Model of 2011 was used as a basis for the development of the framework. The study was carried out in Kenyatta National Hospital, and Moi Teaching and Referral Hospital. The research adopted a case study design that was quantitative in approach. The study had a target population of 3200 from the Moi Teaching and Referral Hospital, and 6000 from Kenyatta National Hospital. Moi Teaching and Referral Hospital, and Kenyatta National Hospital were taken as the two distinct stratum. Stratified random sampling then simple random sampling was used to obtain the respondents. A sample size of 368 was used. This sample size was proportionately divided to give Moi Teaching and Referral Hospital 129 respondents and Kenyatta National Hospital 239 respondents. A questionnaire that was both open-ended and closed-ended was used for collecting data. The data that was collected was cleaned, coded and analyzed with the aid of the Statistical Package for Social Science program. Both descriptive and inferential statistics was used to analyze the data. A response rate of 60% was achieved. Three factors were tested. These included management support, user preparedness, and technical support. Multiple regression results showed a significant positive effect of management support on adoption of cloud computing (β= .247, p<.05). Results indicated a positive significant effect of technical support on adoption of cloud computing (β=.333, p=<0.05). User preparedness was also found to have a significant positive effect on adoption of cloud computing (β= .455, p<0.05). Regression results gave a coefficient of determination R2=.918 which means 91.8% of the variation in adoption of cloud computing can be explained by management support, technical support and user preparedness combined. It was therefore concluded that management support, technical support, and user preparedness are the critical factors that determine the adoption success of cloud computing in an organization. The research findings are useful to Kenya referral hospitals because it was used as major decision-making tools when assessing cloud computing adoption. In addition to this benefit, it will add to the knowledge in adoption of cloud computing in the health care sector. The output of the research was through the development and validation of a framework.
Keywords: Management Support, Technical Support, User Preparedness, Framework, Cloud Computing. Title: Framework for Adoption of Cloud Computing in National Referral Hospitals in Kenya Author: Philip Kipkirui Bittok ISSN 2350-1022 International Journal of Recent Research in Mathematics Computer Science and Information Technology Paper Publications
Data Warehousing As a Decision Support Tool for Effective University Governance
Abstract: This paper addressed the problem of the inability of University management to take correct and effective decisions bothering on day to day running of the institution.
Information is generated from daily transactions carried out at the various sub units of the institution. This information exists in different data formats in computer applications stored at each sub unit. Obtaining a coherent, consistent and accurate information for decision making because of this heterogeneous existence of data in different locations, becomes difficult for management. This difficulty is avoided by building a centralized and integrated information repository using a single format for quicker analysis, trends and patterns discovery.
An SQL Server 2008 database management system (containing integration services, analysis services and reporting services), is used to carry out the data Extraction, Transformation and Loading (ETL) processes to build the data warehouse.
This data warehouse enables online analytical processing (OLAP), trends and patterns discovery for decision making.
Keywords:Data warehouse, Decision making, ETL, OLAP, Patterns, Trends. Title: Data Warehousing As a Decision Support Tool for Effective University Governance Author: Akinjobi J. ISSN 2350-1022 International Journal of Recent Research in Mathematics Computer Science and Information Technology Paper Publications
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