The aim of this paper is to propose an extension of System Dynamics approach for modeling systems to systems described by higher index DAEs (Differential Algebraic Equations). Existing implementations of Forresters methodology are commonly based on fixed step integration methods such as Euler or n-order explicit Runge-Kutta. The main reason for using fixed step integration schemes is their simplicity of imple-mentation as well as the the simplicity of modeling environments based on these integration schemes. On the other hand using fixed step integration can lead to incorrect results especially when equations are stiff. The problems with adequate integration schemes can be overcome by using variable stepsize integration methods such BDF or implicit Runge-Kutta. Since these methods require jacobians of right-hand sides of equations these numerical methods must be supported by procedures for evaluating jacobians either by finite difference, or by automatic differentiation (in order to keep the simplicity of modeling environment). Once we have variable stepsize integration procedure we can attempt to extend Forresters approach to systems described by fully implicit DAEs the paper shows how it can be achieved.
Cigarette smoking presented the most significant public health challenge in the United States in the 20th Century, and remains the single most preventable cause of morbidity and mortality in this country. A number of System Dynamics models exist to inform tobacco control policies. We reviewed them and discuss contributions. We developed a theory of the societal lifecycle of smoking, using a parsimonious set of feedback loops to capture historical trends and explore future scenarios. Previous work did not explain the long-term historical patterns of smoking behaviors. Much of it used stock-and-flow to represent the decline in prevalence in the recent past. With noted exceptions, information feedbacks were not embedded in these models. We present, simulate, and discuss our feedback-rich concept model. A formal analysis shows phenomena composed of different phases of behavior with specific dominant feedbacks associated with each phase. We discuss the implications of our society's current phase. We conclude with simulations of what-if scenarios. We expanded this body of work to provide an endogenous representation of the century-long societal lifecycle of smoking, because System Dynamics models must contain information feedback to be able to anticipate tipping points and to help identify policies that exploit leverage in a complex system.
In a supply chain system, movements in the end-customer demand is amplified throughout the chain as one moves from the lowest echelon (retailer) to upper echelons (wholesaler, distributor, factory). It is reported that this amplification, which is known as the bullwhip effect, can significantly be reduced by sharing the end-customer demand information. In this paper, we first introduce a four-echelon supply chain model, add penalty variables to it, and simulate the model under two conditions; with and without sharing the end-customer demand information. We observe similar results as reported by other researchers; sharing the end-customer demand information has a strong effect in decreasing the amplification, which also results as decreased penalty values. We then introduce a new approach that requires sharing of further information and run the model with the new decision making heuristic based on this new approach. According to the simulation runs, the decision making heuristic suggested in this paper results in further improvement.
The advent of a depopulating society has become apparent in Japanese economy. There is a rising concern that a declining population diminishes Japanese economic growth. This concern is much more significant in regional economies, in which aging workers in the basic industry or an excessive population decline have been longstanding problems, than the national economy. I have developed a quantitative method for population and economic forecasting to examine the current status of a declining population. Linking the population estimates, which are consistent with the population census, to the macroeconomic model with gross domestic product by industry, we are able to examine the effect of a depopulating society on the regional economy. The simulation of this model reveals following future pictures: industries, which are dependent on domestic demand, will decline and per capita income will increase for the while. A declining population has an impact not only on macroeconomic outcomes but also on microeconomic aspects inside the region. Many core areas in the economic growth are losing their positions. I will also point out that the interdependency between core areas and peripheral areas has started changing.
The purpose of this study is to analyze the impact of informal communication networks on the implementation process of innovations within organizations. Therefore, a System-Dynamics model is built to simulate and analyze implementation-specific dynamics that influence implementation effectiveness. The findings of this study suggest that senior management of an organization can use its limited resources more effectively by focusing on employee groups that are connected to each other and by isolating excluded groups from other groups that are not influenced by senior management. In addition, managers should only apply pressure on groups until a specific tipping point is reached after which the innovation diffuses by itself within the respective group. Major limitations of the study are that only one network structure was examined and that all groups are considered to be homogeneous.