Vehicle production remained almost unchanged both before and after the financial crisis, with pre-2008 growth averaging 3.70 per cent and growth since 2008 averaging 3.47 per cent. Conversely, constraints in respect of steel production could also adversely affect the automotive industry. Trends in this sector are therefore important in determining the future supply of steel. Even with dampened demand for steel following the financial crisis, production growth remains strong in relation to other sectors.Īlthough the automotive sector is not the only destination for steel products, it is nonetheless important, constituting approximately 15 per cent of total global steel demand in 2007 (OECD, 2009). In contrast, world agriculture grew by less than half of this, at an average of 2.49 per cent per annum year on year. To put this growth in context, average growth of the steel industry was just over 5 per cent per annum between 19. This is in spite of low profitability threating to close certain plants (Bowler, 2016). Production grew by, on average, 6.35 per cent year on year between 19, and, although production has fallen since the financial crisis, growth has remained at 3.33 per cent on average per annum. This has continued in spite of the financial crisis. The effect of rising vehicular traffic meant that the global steel industry experienced significant growth in the past. This is the focus of the present research. The rise in vehicle traffic has implications for the availability of raw materials and requires further investigation. As a result, the author raises concerns over the "epidemic spread of vehicle traffic" (Gross, 2016:309). This has consequences for climate change, as well as for public health and safety, and gives rise to environmental concerns relating to acid rain and congestion. According to Gross, such growth is due largely to the growth in vehicle ownership in the developing world.
A recent article by Gross (2016) estimates that, by 2030, there will be two-billion automobiles on the roads, double the number in 2010. Key words: predator-prey, steel, vehicles, iron ore, system dynamics, neural network, Vensim This study indicates the potential advantages of using predator-prey models in modelling the supply chain in economics.
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Although the results are comparable over the short term (☑0 years), over the long term, results diverge, showing that forecasting steel-industry dynamics is complex and that further work is required to disentangle the drivers of supply and demand. The forecasting capabilities of the model are compared with the outputs from a neural-network model. The solution is not for marginal steel industries to close, but for steelmakers to adapt and move to less resource-demanding secondary steelmaking technology rather than focusing on primary steelmaking. We find that capacity constraints in the steel industry could limit the future supply of vehicles, a result exacerbated by the unsustainable use of iron ore reserves. A further prey, an additional upstream supply sector, namely the iron ore sector, is added to reflect the implications of scarcity and resource limitations for industrial development and economic prospects. In this paper, we use a predator-prey model to simulate intersectoral dynamics, with the global steel sector as the prey that supplies inputs and the automotive sector as the predator that demands its inputs. IIDepartment of Economics, University of Pretoria and South African Environmental Observation Network, Pretoria IDepartment of Economics, University of Pretoria Predator-prey analysis using system dynamics: an application to the steel industryĭouglas John Crookes I, * James Nelson Blignaut II
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