Department of Logistics

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https://scholar.sun.ac.za/handle/10019.1/71

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Browsing Department of Logistics by browse.metadata.advisor "Havenga, Jan"

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    Ensuring sufficient capacity of logistical infrastructure for future growth
    (Stellenbosch : Stellenbosch University, 2014-04) Gebhardt, Albertus Johannes; Havenga, Jan; Stellenbosch University. Faculty of Economics and Management Sciences. Dept. of Logistics.
    ENGLISH ABSTRACT: This study explore how forecasting techniques can be combined in linear programming (LP) as a tool to optimise the parameters of forecasting methods in order to ensure sufficient capacity of logistic infrastructure exist for future growth. This study will use greenfield and brownfield projects from Sasol, a petrochemical company from South Africa, to test the methodology on. The methodology followed in the study was to firstly look at previous literature studies on logistical infrastructure and how to create sufficient capacity. Secondly, understandings of supply chain planning principles in general as well as supply chain planning in context of Sasol were investigated. Thirdly, different forecasting methods like; qualitative include judgemental, life cycle, Delphi method, market research etc. and quantitative methods including time series and causal methodologies had been investigated. Fourthly, decision making tools to incorporate multiple forecasts were investigated to understand why Sasol decided to use i2. Fifthly, the current capital project approach in Sasol had been investigated to fully understand where room for improvements would be possible. Finally the theory from the study was applied on two different projects in Sasol, one greenfield and one brownfield project. The results found that by using sound supply chain planning methodologies, sound supply chain design principles and multiple forecasts being combined by using LP decision making tools a better decision can be made with regards to logistical infrastructure investment as well as ensuring sufficient logistical infrastructure capacity. The two case studies have shown that this approach is flexible enough, apart from a few minor changes and can be adopted for both scenarios and that great results can be achieved. Logistical infrastructure could be optimised due to collaboration and the overall costs and performance of a supply chain improved.
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    A model for the sustainability of local suppliers in the South African automotive value chain
    (Stellenbosch : Stellenbosch University, 2011-12) Nitschke, Christian; Havenga, Jan; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.
    What factors influence the economic sustainability of local suppliers in emerging markets in the automotive value chain? The answer to this question is not only influenced by the direct and indirect customers of the automotive component suppliers, but it is also influenced by factors on the macro-, meso- and micro-levels of the supplier‟s environment. In order to investigate the research objective, the South African automotive industry is chosen as a case study in the global automotive value chain. The literature review indicates that variables that influence the economic sustainability of suppliers can be found on the global and regional levels of the automotive industry, as well as on the industry and corporate value chain levels. As the theory does not offer a holistic approach for a problem solution, the identified factors are assembled in a conceptual model that measures the economic sustainability of automotive component suppliers with respect to financial dimensions. The conceptual model is structured according to the macro-, meso- and micro-level influences, and also recognises the impact of governance structures on the government, market, industry and corporate levels. The suggested conceptual model is subsequently tested for totality and alignment with industry features using qualitative methods and is furthermore validated by using quantitative modelling data from primary research in the supplier component industry. The analysis of the quantitative data shows that the majority of factors influencing the economic sustainability of local component suppliers can be found on the micro- and meso-levels (corporate value chain and industry value chain), whereas the qualitative data implies that economic sustainability is mainly influenced by factors on the macro- and meso-levels (industrial policy and labour market). This finding shows that there is a discrepancy between the measurable influences and the automotive component suppliers‟ perception of the research problem. Nevertheless, it can be stated that the conceptual model, as supported by the stakeholder group, can be used for further research. Alongside the development of the conceptual model, the industry data is used for a discussion about the status of the South African automotive component supplier industry in order to point out strengths and issues as well as to identify factors that should change or improve to enable a viable future for suppliers.