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Scope and System Dynamic Modeling - Essay Example

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This essay stresses that the thesis delimits itself to the estimation of the environmental impact caused by a global manufacturing entity operating in another country. Three global manufacturers are used as  case studies in the research, namely, Toyota, Volkswagen and Nokia in China…
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Scope and System Dynamic Modeling
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Scope The thesis delimits itself to the estimation of the environmental impact caused by a global manufacturing entity operating in another country. In such a context, they conventionally leave substantial environmental impact behind while the shareholder value is returned back to the country of origin. Three global manufacturers are used as case studies in the research, namely, Toyota, Volkswagen and Nokia in China. In order to investigate the positive and negative environmental impacts of these companies to China, a software called ‘Vensim’ was used to construct a system dynamic model and simulation of the model for the different case studies. Moreover, it is anticipated that the model will be unable to tell the whole story behind the topic. Therefore, only impacts of interest are selected and included in the model. With the green house effect rising to alarming levels over the past decade, it seems worhtwhile to investigate the relationship between CO2 emission and global manufacturing in the current model. In addition, monetary relations between the multinationals and the host country which include taxation, contribution to Gross Domestic Product from global manufacturing and gross profit of the multinationals are likewise include in the model. Change in living standard and creation of employment from global manufacturing are also integrated into the model for better understanding between these global multinationals and the host country. Finally, all impact integrated in the model are only those which are deemed to have direct environmental impact. Other effects which do not have as substantial impact are therefore excluded. System dynamic model The Vensim software is used to simulate a system dynamics model of the situation being studied. Running "what if" simulations to test certain policies on such a model can greatly aid in understanding how the system changes over time. Brainstorming phase: In the brainstorming phase, a ‘perfect’ model is the primary goal. Such a ‘prefect’ model will require the inclusion of every possible component with respect to the topic of interest. As a prerequisite, a causal loop diagram must be drafted before constructing the system dynamic model. A causal loop diagram is a diagram that aids in visualizing how interrelated variables affect one another. The diagram consists of a set of nodes representing the variables connected together. The relationships between these variables, represented by arrows, can be labelled as either positive or negative. The following is the first draft of the causal loop diagram. Fig. 18 (Causal relationship diagram- first draft) Figure 18 shows numerous causal relationships between each component. However for a ‘perfect’ system dynamic model, the components included in the causal relationship diagram is still far from being complete. In order to construct the system dynamic model, it is required that all the information behind the causal relationships be examined. Due to limited time and resources, constructing a ‘perfect’ mode is infeasible and it is more logical to delimit the scope of the project instead. On the basis of the project scope, the following system dynamic model is constructed. However, it must be noted that this model is not the final version. Fig. 19 (System dynamic model – The first draft) Figure 19 depicts a clear idea between different causal components. It is constructed mainly based on the project scope and availability of accurate data. However, there are significant information required in the dynamic model which are unavailable; therefore the dynamic model is still required for fine-tuning with careful consideration of the availability of information. Dynamic model (Final version) Fig. 20 (System dynamic model – final version) The final version of the system dynamic model strictly follows the scope of the project. The dynamic model has 2 inputs and 5 outputs. The input of the model is "Production Rate" and "Sale Revenue". On the other hand, the output of the model is "Number of Employee", "CO2 emission", "Income Tax Paid", "Company Net Profit" and "% contribute to China GPD 2006". All information required in the dynamic model are thus obtained for simulation. In the following content, a detailed explanation of the components (different types), causal relationships between all components, and equations behind the dynamic model are discussed. Model components: In order to describe the cause-effect relationships in the model, three essential features are presented. These include 2 levels and 4 decision functions (drawn as valves) that control the rates of flow between levels and information channels that connect the decision functions to the levels. Levels The levels are the accumulations within the system. They are "Amount of Product" and "Company Net Profit". Levels are the present values of those variable that have resulted from the accumulated different between inflows and outflows. Namely, levels are the time integrals of the net flow rates. And a level may have any number of inflow or outflow channels. Decision Functions (drawn as valves in the dynamic model): The decision functions (also called rate equations) are the statements of policy that determine how the available information about levels leads to the current rates. All decisions pertain to impending action and are expressible as flow rates. A rate equation may appear as a simple equation that deteremins, in some elementary way, a flow in respones to the condition of one or two levels. On the other hand, a rate eqution may be described by a long and elaborate sequence of computations that progresses through the evaluation of a number of intermediate concepts. Flow rate From the discussion of levels, the nature of flow rates has emerged. Rates define the present, instantaneous flows between levels in the system. The rates correspond to activity, while the levels measure the resulting state to which the system has been brought by the activity. The rates of flow are determined by the levels of the system according to rules defined by the decision functions. In turn the rates determine the levels. The levels determining a particular flow rate will often include the level from which the flow itself comes. Causal relationship between components: There are two kinds of causal links, positive(+)and negative(−). Positive causal links means that the two nodes move in the same direction, i.e. if the node in which the link start decreases, the other node also decreases. Similarly, if the node in which the link starts increases, the other node increases. Negative causal links are links in which the nodes changes in opposite directions (an increase cause a decrease in another node, or a decrease cause an increase in another node). Amount of product CO2 emission CO2 emission per product Expenditure Income tax paid Number of employee Production rate per person Sale revenue % contribute to China GDP2006 Amount of product   +   + + +   +   CO2 emission +   −             CO2 emission per product   −               Expenditure +                 Income tax paid +                 Number of employee +           −     Production rate per person           −       Sale revenue +               + % contribute to China GDP2006               +   Fig 21 (Relationship matrix between components) Equation behind the dynamic model: The dynamic model is formed based on the theory of system dynamic modeling. A computer software called Vensim is used as an application tool for carrying this out. In order to simulate the dynamic model in Vensim, equations must be set up accordingly for all components in the dynamic model. Equations used in the software are based on system dynamic modeling theory and the protocol of Vensim software. A detailed explanation of every component is presented in the following section. Production Rate "Production Rate" pertains to the rate of production growth annually. According to the theory of system dynamic modeling, "Production Rate" is classified as an auxiliary. The following equations are used for "Production Rate" in the dynamic model. Equations are anchored on the sales history and sales forecast of Toyota, Volkswagen and Nokia. Equation Toyota =if then else(time Read More
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