When referring physicians decide to refer their patients to specialist care, they rarely, if ever, make a referral decision with the benefit of having access to all of the desirable information. It is therefore highly unlikely that the referring physician will make the optimal choice of specialist for that particular referral. A specialist selection optimization algorithm was developed to guarantee that the “right specialist” for each patient’s referral was chosen. The specialist selection optimization algorithm was developed based on feedback from over 120 users of the e-referral program. The developed algorithm was simulated, tested, and validated in MATLAB. Results from the MATLAB simulation demonstrate that the algorithm functioned as it was designed to. The developed algorithm provides referring physicians with an unprecedented level of support for their decision of which specialist to refer their patient to.

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A Decision Support System for the design and planning of soil conservation systems on a watershed scale was conceived and applied to southwestern Quebec. The system integrated Geographical Information System, distributed parameter hydrologic modeling and Expert System technologies. Maps of appropriate soil conservation practices were produced for two small rural basins representative of the study region. The effect of the selected practices on runoff and sediment was assessed using the ANSWERS model. Erosion sites were targeted using a once-in-25 year design storm. It was observed that small portions of the study basins produced large amounts of eroded sediment. The expert system was designed to select appropriate conservation practices for the 1-ha cells which had more than one ton of erosion as a result of the design storm. The results demonstrated that the selected conservation practices would reduce sediment yield and average erosion rates by 50% in each of the study basins.

Groundwater plays an important role in water supply to rural communities. This statement is supported by the survey conducted at clinics within the Limpopo Province where the majority of aquifers in the area can be classified as Sole Source aquifers, supplying 50 % or more of domestic water in the absence of any reasonable alternative. The water quality study also concluded that the impact from on site sanitation on the groundwater system is significant given that 44 % of water samples of clinics with their own water supply classified as either poor or dangerous quality according to DWAF criteria and poses a significant health risk to susceptible individuals. Groundwater quality should therefore be protected with an emphasis on prevention as in most cases groundwater pollution is difficult to reverse and remediation is often a lengthy and expensive exercise. Although South Africa has all the legal tools to promote sustainable development, financial considerations are usually the driving force behind technology selection and not social or environmental aspects. The aim of this research is to develop an environmental impact assessment methodology and decision support framework that will aid in the selection of the most appropriate on site sanitation technology for a given area integrating environmental, economical and social criteria. The decision support framework developed in this study had a strong stakeholder component, involving stakeholders in the decision making process from the conception of the project through to the resolution of actions. Providing objective information about the performance of options, coupled with an opportunity to participate in the decision-making process, increases the awareness and commitment of the community. Field testing of the decision support framework produced good results and sensible recommendations were made with regard to alternative selection. / Thesis (Ph.D. (Geography and Environmental Studies))--North-West University, Potchefstroom Campus, 2007.

When the data warehouse concept was first introduced by IBM as a part of their new information system in 1988, the first step in the field of modern decision support systems or business intelligence was taken. Since then, academics, practitioners and solution developers have put a considerable effort in introducing new trends of these systems. Each new trend has roots in what enterprises demand from these systems. The advances in Web technologies and social media, has led to introduction of new trends such as Cloud BI and Big Data which are both cost-effective and also have the potential to take advantage of semi-structured and unstructured data within organizations. This paper deals with these new trends and the influences of organizational demands and new technologies and tools on them. A deep literature review deals with four major BI trends in detail. (Data warehouse, Business Performance Management (BPM), Cloud BI and Big Data). Two case studies from local Business intelligence developers are carried out in order to explore the influences mentioned above. As the result of this study, a model is proposed that addresses the elements that affect the BI trends, both in organizational and technological perspectives. It is observed that despite the fact that lots of new trends have been introduced in the past years (e.g. Cloud BI and Big Data), it does not necessarily mean that older trends are becoming obsolete. Data warehouses and BPM systems are still being used vastly in the industry. However, the later trends can be offered to clients that have the demand for them. The results imply that Cloud BI is mainly suitable for companies with low initial budgets and Big Data can be adopted by organizations that want to exploit their social data sources. The mere fact that both implied trends are built upon their preceding ones, has transformed data warehouses and BPM approach the ground work for any new trends to come.

When referring physicians decide to refer their patients to specialist care, they rarely, if ever, make a referral decision with the benefit of having access to all of the desirable information. It is therefore highly unlikely that the referring physician will make the optimal choice of specialist for that particular referral. A specialist selection optimization algorithm was developed to guarantee that the “right specialist” for each patient’s referral was chosen. The specialist selection optimization algorithm was developed based on feedback from over 120 users of the e-referral program. The developed algorithm was simulated, tested, and validated in MATLAB. Results from the MATLAB simulation demonstrate that the algorithm functioned as it was designed to. The developed algorithm provides referring physicians with an unprecedented level of support for their decision of which specialist to refer their patient to.

For many years, supply chain research focused on operational aspects and therefore mainly on the optimisation of parts of the production and distribution processes. Recently, there has been an increasing interest in supply chain management and collaboration between supply chain partners. However, there is no model that takes into consideration all aspects required to adequately represent and measure the performance of a collaborative supply chain. This thesis proposes a model of a collaborative supply chain, consisting of six constituents, all of which are required in order to provide a complete picture of such a collaborative supply chain. In conjunction with that, a collaborative supply chain performance indicator is developed. It is based on three types of measures to allow the adequate measurement of collaborative supply chain performance. The proposed model of a collaborative supply chain and the collaborative supply chain performance indicator are implemented as a computer simulation. This is done in the form of a decision support environment, whose purpose is to show how changes in any of the six constituents affect collaborative supply chain performance. The decision support environment is configured and populated with information and data obtained in a case study. Verification and validation testing in three different scenarios demonstrate that the decision support environment adequately fulfils it purpose.

Groundwater plays an important role in water supply to rural communities. This statement is supported by the survey conducted at clinics within the Limpopo Province where the majority of aquifers in the area can be classified as Sole Source aquifers, supplying 50 % or more of domestic water in the absence of any reasonable alternative. The water quality study also concluded that the impact from on site sanitation on the groundwater system is significant given that 44 % of water samples of clinics with their own water supply classified as either poor or dangerous quality according to DWAF criteria and poses a significant health risk to susceptible individuals. Groundwater quality should therefore be protected with an emphasis on prevention as in most cases groundwater pollution is difficult to reverse and remediation is often a lengthy and expensive exercise. Although South Africa has all the legal tools to promote sustainable development, financial considerations are usually the driving force behind technology selection and not social or environmental aspects. The aim of this research is to develop an environmental impact assessment methodology and decision support framework that will aid in the selection of the most appropriate on site sanitation technology for a given area integrating environmental, economical and social criteria. The decision support framework developed in this study had a strong stakeholder component, involving stakeholders in the decision making process from the conception of the project through to the resolution of actions. Providing objective information about the performance of options, coupled with an opportunity to participate in the decision-making process, increases the awareness and commitment of the community. Field testing of the decision support framework produced good results and sensible recommendations were made with regard to alternative selection. / Thesis (Ph.D. (Geography and Environmental Studies))--North-West University, Potchefstroom Campus, 2007.