Feasibility study of off shore windfarm implementation in South Africa looking at technical factors
South Africa has been experiencing electrical power blackouts since 2008 to date. Because of the negative impacts on the economy, it is important to find an alternative power supply as a solution to these blackouts. This report proposes the use of Offshore Wind Farms (OWFs) as an additional power supply alternative in the renewable energy (RE) sector of the
country. This report mainly focuses on the technical feasibility study of Offshore Wind Farms (OWFs) installation in South Africa. The aim was to determine whether South Africa has enough wind resource that compares with OWFs currently installed in OWF-rich countries. China and UK, being two of the world’s top three countries with high OWF capacity, were compared to four potential installation sites in South Africa. Seven factors (also named criteria in the report) were studied and compared to one another using a decision-making matrix. Fuzzy Analytical Hierarchy Process (FAHP) using geometric mean value decision-making method was used. The FAHP Multi-Criteria Decision Making (MCDM) framework was developed to weight the seven criteria from primary data collected through questionnaires. The criteria weights were used to determine the score of each alternative and rank all six alternatives. From the results, it was observed that South Africa has the potential of making use of its rich offshore sites to produce alternative electricity and eradicate the problem of having power blackouts.
Henk van der Heever, Top Student: Masters in Engineering Management (MEM)
Application of cognitive work analysis to early stage requirements analysis for complex sociotechnical systems
The development of sociotechnical systems is often performed using the systems engineering approach of reduction and localised optimisation. The introduction of new technology may result in unexpected emergent behaviour that challenges existing processes and information flows with sociotechnical systems. If engineering efforts fail to account for this emergence, and the associated complexity, the resultant systems may fail to fully achieve the required utility. Cognitive work analysis provides a framework for analysing, modelling, and designing sociotechnical systems. This study proposes a validation workflow to aid systems engineering through the application of cognitive work analysis as part of the requirements analysis process. Work domain analysis is applied to a test case that implements new technology in a sociotechnical system. The resultant abstraction hierarchy models were evaluated for perceived utility. Analysts successfully applied the method and uncovered potential design emergence. The study confirmed the utility of the proposed method, which adds a valuable tool to the system engineering quiver.
Franco Barnard, Masters in Technology and Innovation Management (MTIM)
Software as a service adoption: A fuzzy approach to ranking the determinants
Software as a Service (SaaS) holds various benefits to organisations. Commonly to improve their access and use of information technology in a cost-effective manner. Within a South African context, SaaS solutions are not enjoying widespread adoption. This is arguably due to the associated challenges with moving on-premise solutions to SaaS solutions. Additionally, it is unclear which factors should be considered when moving towards SaaS. Therefore, investigating SaaS adoption and the important factors influencing such adoption can contribute to the beneficial use of SaaS technologies within South Africa. Therefore, the purpose of this study is to identify the factors that influence SaaS adoption by considering appropriate adoption models and ranking these factors according to their influence on an adoption decision. Central to the approach to achieve this goal was the combination of the Technology, Organisation and Environment (TOE) model with the diffusion of innovation (DOI) and the institutional (INT) theory. Accordingly, twelve significant adoption factors were identified and used to survey thirty experts from industry and academia with an information and communication technology-related focus. In addition, fuzzy Analytic Hierarchy Process (AHP) with linguistic preference relations (LinPreRa) was implemented to rank the submitted SaaS adoption factors in order of importance. The findings demonstrate the importance of the TOE model's technology (Trust, Relative Advantage, Security Risks, Complexity, Trialability) and organisational (Top Management Support, Organisations Size, Technology Readiness, Cost) context. The results also indicate the lesser importance of the environmental context (Coercive Pressure, Mimetic Pressure, Normative Pressure). The top five factors to consider in an adoption decision were also found to be Trust, Relative Advantage, Security Risk, Complexity and Trialability. Conversely, the aspects associated with the environmental context were ranked the lowest and hence could be assigned reduced priority during a SaaS adoption decision. Parallels and comparisons are also discussed by evaluating the responses received according to the demography of the research sample. In particular, the comparison between the software and product development industries are worth noting. For SaaS vendors, SaaS adopters and the research fraternity, this study holds merit. Vendors could incorporate the findings to better align themselves with the industry viewpoint on SaaS solutions. Organisations can use the findings to reduce uncertainty involved with making a SaaS adoption decision and, in so doing, better harness the benefits of SaaS solutions were sensible. For researchers, this study provides relevant literature helpful in expanding the scope of SaaS and cloud computing research within South Africa and relevant areas of future research. This study is unique from a South 25 September 2021 ii African perspective as it is not testing new hypotheses but rather applying existing theories in a descriptive study.