Since modeling and risk management must be viewed as a tool to improve business performance, data and modeling tools are required to support financial risk quantification and capital allocation. Market developments and enhanced regulations require new techniques in order to improve Asset and Liability Management..Despite the importance of risk evaluation, lack of reliable public information, the singular probabilistic behavior of the return (or the loss) of market and credit risks and the underlying nature of the business leads to a complexity that is difficult to handle without a combination of methods and techniques that could together give a systemic view of the problem. Based on a research over a 10 year data base, a methodology will be detailed to quantify financial risks based on the combination of methods and techniques such as parametric v@r, historical and monte carlo simulations, Bayesian inference and game theory. The aim of the paper is to put together the techniques and describe the usefulness of each one in order to develop a SD policy model that can use many insights and informations from them.
The paper includes the first day of a wider dialogue à la Plato about systems, under a System Dynamics perspective. Socrates, discussing in the Agora with a young ante litteram manager, practices the art of maieutics in order to elicit and clarify the basic concepts about systems.
This paper shows that the tools of system dynamics theory can be methodologically useful to provide new insights into art and cultural economics. Specifically, it develops a model of how the reward system in art markets works and cause imbalance allocation of revenues and recompenses. With this, it also proves that system dynamics it is useful to model self-organizing systems.
Using the tools of system dynamics and urn theory, this paper formalizes the theory of expansion economies to explain the globalization of the firms. In order to exploit economies of expansion, manufacturing firms tend to expand their economic activities to different locations, regions and countries. As firms expansion process is an increasing return mechanism, system dynamics and urn theory can explain path dependence and self-organizing size distribution of global firms.
Technology is often heralded as a tool to reduce greenhouse gas (GHG) emissions despite a rising global population and increasing global affluence. Cloud computing - a popular
A simple system dynamics model was used to explore the potential benefits of using regret analysis to develop sensible government energy policies. Regret analysis evaluates the relative impact of unexpected futures to design policies that reduce the risk of losses rather than trying to optimize benefits. It is very useful when it is impossible to assess or agree on the probabilities of future events and, especially, those events that can have a large impact on the system behavior.
Cyber attacks pose a major threat to modern organizations. The effectiveness of cyber defense can likely be enhanced if programs are implemented that allow organizations that face similar cyber threats to share information and resources. To begin to understand the potential for cooperation to improve cyber security, we modeled a simple cooperative structure that allows resource sharing between two organizations whose defense teams do a significant amount of redundant work. This model is a first step toward understanding the social and operational issues involved in implementing a program of cooperative cyber defense between organizations.
This paper expands upon a qualitative study done by Beck and Stave (2011) investigating how to understand the dynamics underlying urban quality of life and sustainability. In the original study, we examined the factors and feedbacks that governed migration in and out of urban areas. Quality of life (QOL) was assumed to be the short term motivator behind migration, while sustainability determined the long term livability of a city. Past studies on these topics all have a common thread: sustainability and QOL both pertain to peoples relationship to capital. In this study, we illustrate how these forms of capital interact with a citys population to create in migration and out migration behavior based on the attractiveness of its capital stocks. We monitor the accumulation of different forms of capital to evaluate sustainability and use the distribution of capital as proxy for quality of life. Finally, we provide our experience in validating the model using historic population trends of three American cites.
The purpose of this paper is to propose a dynamic hypothesis for shipyard learning. From this dynamic hypothesis was developed a system dynamics model that served as a basis for the definition of guidelines that could serve as a basis for policy design in a real shipyard that seeks learning in productivity.
High copper prices, the prospect of a transition to a more sustainable energy mix and increasing copper demands from emerging economies have not let to an increased attention to the base metal copper in mineral scarcity discussions. The copper system is well documented, but especially regarding the demand of copper many uncertainties exist. In order to create insight in this systems behaviour in the coming 40 years, an Exploratory System Dynamics Modelling and Analysis study was performed. Three different models have been developed representing different views on copper supply and demand. The behaviour of these models shows crisis-like behaviour for the copper price, and often a declining consumption of refined copper. Six different policy options have been explored, individually and in combinations, for their robustness in counteracting undesirable behaviours. The results of these tests are that emphasising recycling, and the development of strategic reserves are potentially helpful.
The German Chapter advances networking and collaboration among system dynamicists in Germany. The Chapter has 113 members per end of April 2011 (of which 5 are corporate members) and keeps more than 280 interested researchers, managers, and students updated through its e-mail newsletter. System Dynamics colloquia and roundtables are regularly organized in various German cities (Frankfurt/Main, Munich). These events provide a basis for meeting fellow system dynamicists and for discussing modeling projects. On May 26-27, 2011, the Chapter's 5th Annual Meeting is held in Wolfsburg. This event brings together modelers from the scientific and corporate world, and by combining talks, presentations, and modeling exercises, it offers a formidable and appreciated platform for establishing links within the community as well as for actively advancing SD skills. More information on the activities of the German Chapter is available from our website at http://www.systemdynamics.de (in German).
The purpose of this meeting will be to discuss the formation of a biomedical system dynamics special interest group (BPSD SIG). Medical research, medical education, and clinical practice each present a compelling need for deeper, actionable insight into the complex dynamics of biophysical processes at the level of the individual. Systems within the human body amenable to the disciplines of ST/SD range from the molecular to higher level complex physiological processes. Recent developments in embedding simulation models within clinical applications for individualized care have delivered significant results and clearly demonstrated the feasibility and value of biophysical modeling in healthcare. We would like to have a dialogue with meeting participants about topics of mutual interest and to receive feedback on a proposed action plan aimed at equipping healthcare professionals with the insights and skills to be gained from the application of ST/SD to individualized medicine.
2011: The UK Chapter has regular meetings in the UK, and annually at the international conference. In February we held the 2011 Annual Gathering, with theme of 'Doing (much) More with Less' - in both public sector and corporate settings. You can see the topics of all the great talks we had at the event at www.systemdynamics.org.uk and also view slide-show videos of them all. Congratulations to Peter Lacey who won the Steer-Davis Gleave prize for the best UK application of system dynamics, and Rhys Lewis who won the UK Chapter Student prize for his work on social housing. Our evening networking events have continued: three in 2010. If you are based in the UK and not already on our membership list (membership is free) then please do join on our website and see what we have to offer. There are between 80 and 100 members active in SD in the UK.
Quality criteria do not only relate to the products mere quality, but to the production and marketing process of the product as well. Customers often express their dissatisfaction with low ethical standards in this area by consumer boycotts. As there are complex relationships between financial aspects and compliance, a system dynamics model is used to unveil causal relationships and explain behavioral patterns. The model highlights the links between a companys dilemma situation and the effectiveness of a boycott for those demanding different corporate conduct. It also demonstrates possible levers for triggering different behavior.
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.
The average life expectancy of a company is sadly only 40-50 years. You would think that a company lifetime could easily surpass our lifetimes because many generations can work at a company and pass down its products, brands, know-how, competencies, customer base, etc. to successive generations. But ultimately companies die because they fail to adapt and change. One area of adaption that is the most difficult to navigate is when to start de-investing in the traditional markets that initially built the company, and to invest in building new markets. Too many companies get themselves caught in a trap of continual investment in their core markets, which are no longer growing and missing out on growth adjacencies that can fuel the companys next generation of growth. This paper will explore the reinforcing feedback loops and systemic delays that cause most companies to invest too much and too long in their traditional market and recommends a new R&D portfolio management process that breaks this cycle. Its critical that companies understand what drives long-term success and how to fund innovation and change in a methodical way.
Current research on river ecosystems in Taiwan is mostly focused on water conservancy, ecology, and afforested viewpoints. There is a lack of integrated strategy on urban river ecosystem management. This study aims to examine river quality based on ecological safety. By means of systems engineering technology, the related ecological safety operation mechanisms have been analyzed. Also, through the new Fuzzy Delphi expert survey, the index system of urban river ecological safety (IES) has been compiled in order to explore the variables. The key indicators affecting urban river ecology safety can be fully defined by sensitivity analysis in order to engage in effectiveness evaluation and to create a dynamic simulation model. The study results indicate that the strategic implementation of improved embankment vegetation structure, a reduction in the degree of river channelization, and the maintenance of a high degree of longitudinal connectivity of rivers can effectively enhance the urban river ecology risk prevention, strengthen the efficient use of resources, and promote the sound development of urban river ecology.
A practitioners perspective on the calibration of complex system dynamics models is described in the context of a specific project in which a large, complex business training simulation model was converted from one language into I-Think® and design flaws in the original implementation were corrected. The model utilized 57 inputs and provided 296 outputs. The fact that calibration interacts with verification and validation is acknowledged, as well as the fact that the calibration strategy required for large models may not scale practically to smaller models. In additional to traditional best practices such as units checking, sensitivity testing, transient testing and graphical comparison, the paper focuses on a) simplifying and isolating interactions via submodels, using shims, slowing down feedback loops, creating cause and effect maps, testing at submodel level, and checking qualitative variables; b) Redesigning along the way; c) carefully documenting throughout the process; d) knowing when to step away; and e) building/acquiring automated tools. Having a calibration strategy for a large model is essential. The time required to apply the recommended methods can be significant, but the benefits clearly outweigh these costs. Nevertheless, even experienced modelers often wait too long before initiating the necessary disciplines.