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.
Athletes face tremendous pressure to perform, and, when conventional means prove insufficient for performance improvement, some turn to performance enhancing drugs (PEDs). The present paper uses system dynamics to examine one example: the use of anabolic androgenic steroids in Major League Baseball (MLB), which operates in the United States and Canada. The authors provide an explanation of a detailed causal loop diagram of the problem, along with a stock and flow model, based on the Bass Diffusion Model, of part of the problem. They provide a few policy recommendations based on model runs.
This paper/poster explores the role and contribution of dynamic models in reverse logistics processes. The purpose of reverse logistics processes within a manufacturing supply chain is to disassemble or reutilize products, or their components, in order to generate value. The first part of the paper describes the general process involved in reverse logistics as found in the supply chain management literature. The second part of the paper presents three dynamic models that represent the main factors driving product returns: The green factor or consumer sensitivity towards environmental issues; the regulatory factor or governmental requirements; and the profit factor or business opportunities. The third part of the paper combines the three factors behind products returns in order to create a general dynamic model of reverse logistics. Emphasis is placed on two major issues: The non-linear relationships involved in reverse logistic processes and business opportunities as the main driver of reverse logistics. The last section of the paper centers on the similarities and differences of dynamic models that aim to simulate forward logistics and reverse logistics. While forward logistics are centered in concepts such as assembly and bullwhip effect, reverse logistics models emphasize disassembly and funnel-like behavior.
When final customer demand exceeds available supply, retailers often hedge against shortages by inflating orders to their suppliers. As several retailers compete for scarce supply, the amplification in orders lead to excess supplier capacity, high inventory variability, low capacity utilization, and financial and reputation losses for suppliers and retailers. While the amplification in orders caused by the competition for scarce resources has been described in the literature almost a century ago (Mitchell 1924), there is little research quantifying the impact of such order amplification by retailers.
The performance analysis of a general productioninventory control system under uncertain demand is presented. In the model, the production order releases are determined based on the information feedback on the forecasted demand, work-in-process discrepancy and inventory discrepancy. Stability conditions are obtained in terms of the control parameters that manage the rate at which the above discrepancies are corrected. The service and cost performances of the system in terms of order fill rate, item fill rate and average system cost are analyzed for various values of the control parameters within the stability region. Additional safety stock is considered to help achieve a desired level of service (desired order fill rate). Results based on numerical simulations are presented and their implications are discussed.
In this study, by using system dynamics approach we aim to investigate the profitability of a company if it is engaged in remanufacturing, which is the most advanced form of product recovery. Our motivation is to find out whether investing in remanufacturing is advantageous for a company/sector in terms of long term profitability and, what should be the quality and price levels of the remanufactured and newly manufactured products. The model shows that a company involved both in new and remanufactured versions of the same product, endogenously generates interesting customer-base dynamics. Different from the studies in the literature that deal with micro level models, we analyze the effects of being involved in remanufacturing of electronic products on the profitability of the firm at macro level, by taking into account the government incentives for the firms that perform product recovery.
Service operations depend intensively on human resources because of their interaction with customers and suppliers and thus, training becomes a must in order to ensure higher performance. Knowledge Management (KM) may be looked as a framework for training programs since it addresses knowledge conversion from explicit and tacit knowledge. This paper proposes that dynamic simulation might be used as a tool to analyze training programs effectiveness from a KM perspective. Thus, a SD model was built using data from a customer support service of a software-house in Brazil. Three scenarios were considered, relying on the number of trainings per month. The main contribution of this work lies on shedding light over the intangible effects of tacit and explicit knowledge that support the effectiveness of training programs over organizational performance.
This paper addresses the challenge of identifying adequate theoretical starting points for problem oriented simulation studies of socio-technical transitions towards near fossil free energy services e.g. for housing and transportation. The identification of adequate starting points for simulation studies is becoming increasingly important for the generalization of simulation results as well as for theory refinement. We found that the Multi-Level Perspective (MLP) offers a helpful language for a modelling experiment based in a feedback perspective. This allows scientific conceptualization of a socio-technical transition challenge departing from an inter-subjective and hence scientific starting point. In addition feedback modelling appears to be a promising mathematical analysis approach that helps to substantiate the MLP. We have seen that the insights of the simulation experiment corroborate basics assumptions of the MLP concerning multi-level alignment processes but also discriminates the decisive determinants and governance mechanism that explain radical innovation and subsequently the creation of path dependency.
Over the past few decades, many studies of corruption have been carried out. These studies have mainly focused on specific characteristics such as: economic issues, legal issues, and social propositions. In this article we have described the concept of modeling corruption in Pakistan using a Causal Loop Diagram (CLD). Corruption represents a very dangerous social phenomenon observed in many parts of the world. However, its manifestation in a developing country is an especially destructive agent against human development. The System Dynamics (SD) approach has been extended in the past several years through its application to new problems such as modeling state instability, supply chain management, and analysis of different nation building policies. The main objective of this study is to develop a theoretical framework which can be used to study corruption dynamics by means of SD. The methodology employed is a case study. Semi structured interviews with key stakeholders such as: government ministries, donor agencies, judiciary, police departments, non-governmental organizations and the general public are done. On the basis of literature and social theory we have developed three preliminary CLD models of corruption. The data for the qualitative system dynamics analysis comes from 30 interviews conducted in (Islamabad) Pakistan.
This paper explores the Agile software development methodology to discover the essence that has enabled it to prosper and grow since the declaration of the Manifesto for Agile Software Development in 2001. Examined is the role of feedback in the Agile methodology and its relationship to single and double loop learning.
The desire to better understand the transmission of infectious disease in the real world has motivated the representation of epidemic diffusion in the context of quantitative simulation. In recent decades, both individual-based models and aggregate models (such as System Dynamics) are widely used in epidemiological modeling. This paper com-pares the difference between aggregate models and individual-based models in the context of Tuberculosis (TB) transmission, considering smoking as a risk factor. The merits and impact of capturing individual heterogeneity is examined via representing Bacillus Calmette-Gurin vaccination and reactivation in both models. The simulation results of the two models exhibit distinct discrepancies in TB incidence rate and prevalence. Results also suggest that, at the level of practical application, individual-based models offer significantly greater accuracy and easier extension, especially when representing a decreasing reactivation rate, waning of immunity and heterogeneous individual at- tributes. Another experiment sought to evaluate the impact of network structure on TB diffusion. Simulations are conducted under three widely used network topologies, namely random, scale-free and small world. The results reveal large differences between results of individual-based models and aggregate models, which further give insights into the difference between these two model types in the context of practical decision-making.
Over the next several decades, population trends sweeping across the world will challenge cultural traditions, health systems capacity, and social infrastructure. As average age of populations increase, health care needs change from acute to chronic. Of all the causes of age-related dependency, dementia presents a particular problem: the elderly with dementia have extensive care demands and, as their dementia progresses from mild and moderate to severe, institutionalization becomes more likely. Our research applies system dynamics methodology to estimate future population-level severity of dementia and the challenges of age-related dementia to family and community infrastructure.
Indonesia, through a state-owned aircraft industry named PT. Dirgantara Indonesia (PTDI), is trying to develop its national capacity in aerospace industrial technology. The strategy being thought to realize this objective is to build the aerospace supply chain industries through which the Small & Medium Enterprises (SMEs) can take a role in the global aerospace supply chain industries in the near future. As a main focus for this purpose, the Quality Management Systems (QMS) like AS 9100 has to be internalized in the SMEs; because, in reality, the Indonesian SMEs have not yet been experiencing with the quality requirement. Therefore, it is important to simulate the QMS learning process in the SMEs through an outsourcing collaboration between PTDI and SMEs. To simulate the learning process, a system dynamics model of knowledge development is constructed based on the inter-organizational learning dynamic model developed by Otto and Richardson (2004). A modification of the original model is made to accommodate an assistance mechanism for SMEs learning process in order that the QMS knowledge and experience of SMEs is adequate enough prior to the outsourcing partnership with PTDI. This study shows that the assistance is very important for SMEs those have not adequate prior knowledge and experience in QMS to increase their knowledge level.
This paper presents a soft landing model and a related control heuristic. The aim of this modeling effort is to represent the process of landing a spacecraft on the surface of a celestial body. This problem is known as the soft landing problem because crashing the spacecraft to the surface should be avoided. At the same time, long landing period necessitates extensive use of fuel, which should also be avoided. Consequently, the main goal in soft landing problem is to land the spacecraft as gently and as fast as possible. We adapted a control heuristic from the mass-spring damper model. According to the initial simulation runs, the adapted heuristic is successful in landing the spacecraft.
This paper introduces system dynamics approach to the domain of psychiatric research. We have tried to develop a computer simulation model based on theoretical findings and facts known to clinicians and looked for an answer to the problem of different cortisol reactivity between major depression and PTSD patients with respect to trauma severity, length and proposed genetically based differences in hippocampal volume. Modeling PTSD and depression in one structure is to our knowledge the first attempt to grasp these widely spread disorders with substantial societal and clinical burden. Even though the current model structure is simplified, proposed approach has a powerful predicting potential in clinical practice and social policy. Model structure and model equations are in Appendices 1 and 2.
With increasingly volatile oil prices, unprecedented US dependence on imported petroleum, and growing environmental concerns, the creation of economically sustainable markets for alternative fuel vehicles (AFVs) is vital. However most efforts to supplant the current transportation system have failed or had limited success. The diffusion of AFVs is complex, being both enabled and constrained by powerful positive feedbacks arising from scale and scope economies, experience curves, network effects and complementary assets. While such feedbacks are sometimes discussed, dominant mental models among both policy makers and academics may underestimate the strength of these feedbacks and the fact that they also operate to advantage the current dominant technology. The result has been a series of overly-optimistic forecasts for the extent and speed of diffusion for AFVs and EDVs, and insufficient investment in standards and policies to help such vehicles over the tipping point to self-sustained adoption. We describe a model we have developed a suite of behavioral dynamic, spatially disaggregated models with a broad scope and its key actors. We demonstrate, through various thought experiments, that higher oil prices, while important in speeding EDV adoption, are less effective than many expect, due to a range of compensating feedbacks that enable internal combustion-gasoline technology to adapt.
This paper examines challenges and opportunities for policy actions that transform healthy living behaviour. We examine how policies and other decisions, made by various types of actors (i.e. consumers, industry, agriculture, government, NGOs, and global institutions) evolve as they interact and collectively shape nutritious food markets over time. Such a transformation is characterized by multiple feedbacks and long-term delays, and involving disjointed public and private level interactions, produces counterintuitive behaviour. To develop an in-depth understanding of the major challenges and identify high-leverage strategies in transitioning away from low nutrition / high motivational (LN-HM)-based food system we have developed a behavioral dynamic model with a broad scope. Key actors in the models include consumers, producers, and policy-makers. In this paper we describe the model and carry out simulation experiments designed to examine barriers to self-sustaining market shifts between supply and demand factors. Collective action among producers to improve nutrition, while important in achieving nutritional change, builds up slow and is failure prone, due to a range of compensating supply and demand feedbacks. We analyze and discuss the role of cross-product category substitution, the contextual role of consumer switching dynamics, and a variety of initiatives, including those oriented around marketing and R&D. We conclude by discussing the importance of coordination and commitment across actors and model extensions.
Language dynamics in multi-language societies is a growing field of study. Most extant research focuses on the dynamics of language death in multilingual societies. However, empirically, languages form more complex patterns, including survival in local clusters. This paper lays the foundation for a model to explain the process by which dominated languages sustain themselves. The key mechanism we explore in this paper is the social-network effect that affects single or multiple language adoption. In particular we hypothesize an important role of bilangualism. To analyze this we extend existing, stylized, models that predict one single dominant language. We simulate the competition of two language groups who interact through a bilingual population. We include factors such as language status and ease of learning. The model is tested against the empirical case of Quebec from 1931 to 2006. We explore the importance of bilingual parents raising their children as bilinguals or unilinguals according to the relative attractiveness of each language. We find that this factor, while not critical in explaining qualitative patterns, is instrumental to replicate more accurate patterns. We conclude by developing a hypothesis of how spatial disaggregation of the network effects may explain the local cluster survival of dominated languages.
The stock management (SM) problem is of high relevance for a broad range of decision makers in society, business, and personal affairs. Although in some areas highly sophisticated models and control concepts have been developed, human stock management performance is lamentable. One recent explanation for this failure is offered by a stream of research, which finds evidence for widespread and persistent deficits in understanding how flows accumulate in stocks. This misunderstanding of accumulation (MoA) is proven even among well-educated adults. This research uses laboratory experiments to test the hypothesis that the better people understand accumulation, the higher is their performance in SM tasks. Correlation and univariate regression analysis show that MoA indeed contributes to explaining performance differences in stock management. However, the effect is moderate and vanishes almost completely when intelligence and economic knowledge are included as control variables in a multiple regression model. The value of this paper lies in explicitly testing the relation of MoA and SM, whose existence is widely taken for granted. Future research could explore a broader set of control variables and should increase the number of cases to allow for advanced theory testing using, for example, structural equation modelling.
This paper presents findings from the use of a simulation learning environment to teach college students about principles of accumulation. The simulation package is part of an ongoing study testing the utility of systems simulations for teaching students about the complex systems relationships in environmental studies and science. We have conducted paired experiments over the past five semesters in a team-taught, college-level Introduction to Environmental Science course using system dynamics simulations. We have progressively refined the systems learning objectives, simulations, and assessments. The focus that has emerged from this research is the need for building systems understanding about the dynamics of accumulations. While most students are able to define and identify everyday examples of accumulations, they have difficulty understanding relationships between flows and accumulations in any but the simplest cases. The pattern-matching tendency is strong. In this paper we present a simulation developed specifically to address simple issues of accumulation and discuss lessons we have learned about best practices for discovery learning in this setting.
This poster presents a web-based simulation learning environment for facilitating discovery learning about accumulations. It was designed to complement an Introduction to Environmental Science course at the college level, but will eventually be available as a stand-alone package. The primary learning objective is to develop the users understanding of the relationship between inflows, outflows, and accumulations, as well as the effect of changes in inflow and outflow rates. Results from the use of this simulation in freshman Environmental Science classes will be presented in another paper. Here we describe the domain and discovery learning objectives, storyboard, and interpretive scaffolding of the simulation learning package, and present insights from user feedback on the design. We plan to have a demonstration version of the simulation available at the conference.
Joining the European Union big opportunities in the international markets have opened for Latvia. Paper purpose is to investigate influence of international integration processes on development of economy of Latvia. Latvia's incoming in EU increased the amount of received means from structural and cohesion funds, removed the trading barriers, increases foreign investments, reduced unemployment and increased labor migration. In the paper the system dynamics model, which describes integration of the Latvian economy into EU, is developed. In the model international financial flows connected with Latvia and EU; import, its relation to internal producing; and migration processes are considered. Model functioning is measured considering various scenarios of situation development. The developed model can be used not only in the analysis of Latvias economic integration in the EU, but on its basis it is possible to create models of regional cohesion in Europe.
This paper explores the dynamics of energy reduction policy setting for data centers in the face of new metrics and related regulation. With these new metrics there is a potential for management to establish policies that achieve the specific metric target while sub-optimizing the total energy reduction opportunity. This paper will address the question of whether new insight can be gained by using a system dynamics approach versus static return on investment forecasting. The first part of this paper will describe the unique dynamics of energy consumption in a data center and the application of one particular metric used to indicate energy consumption efficiency. The second part of this paper proposes a model that represents the interconnected behavior of data center energy consumption and metric based policy implementation. This approach is compared to static methods and the insights gained from taking a systems approach.
In this study, a dynamic simulation model for thyroid hormone system is constructed. The objective of this work is to first generate the dynamics of the hormones involved in thyroid hormone system in healthy body, and then to adapt the model to portray the dynamics of certain common thyroid disorders. The ultimate aim is to provide a platform to conduct scenario analyses without risking patients health. Thyrotropin-releasing hormone (TRH), thyroid-stimulating hormone (TSH), thyroid hormones, weights of hypothalamus, pituitary and thyroid gland are the basic variables in the model. Scenario experiments are simulated and outputs consistent with the data in literature, both qualitative and quantitative, are obtained. As future work, the model will be extended to cover more disorders and the parameter values will be more realistically calibrated.
The objective of this study is to investigate a very common phenomenon in an important emerging country, namely the spike in demand at the end of the sales period, known as the hockey stick phenomenon. The analysis will encompass the causes as well as the impacts of this phenomenon, in a way that allows alternative policies to be proposed that are able to provide a better financial result for the agents involved. Data collected from a Brazilian branch of a large multinational in the non-durable consumer goods industry and in semi-structured interviews conducted face-to-face with executives of 26 clients. After internal and external validation of the model, scenarios were generated to identify causes, impacts and alternative policies. The findings showed that the phenomenon negatively impacted the manufacturers financial performance in the long term and indicated requisite changes able to eliminate it. The study showed that companies should not assume the hockey stick phenomenon to be an exogenous problem; it showed that there are alternative policies; and it provided ideas regarding ways to carry out the change process. This is the first empirical study on the hockey stick phenomenon, a problem that affects diverse companies in emerging countries.
CO2 emission of industrial facilities is a major cause of climate change that affects the ecosystems, human beings and environment. Capture, Transport and Storage of CO2 (CTSC) is a novel technology of mitigating the impacts of climate change. The uncertainties concerning long term reliability of CTSC technology give rise to the significance of risk assessment for CTSC activities.
An enterprise information system, e.g. a system for Enterprise Resource Planning or Customer Relationship Management, is important for any organization to carry out its business activities. Even when the upstream activities of selection or development of such a system, its installation and appropriate user training are carried out effectively, the subsequent use of the system does not always result in meeting the expectations to carry out the work of the enterprise. Published literature is rich in covering the initial acceptance and adoption of such information systems, but is rather sparse in covering the dynamics of post-installation use of the systems. This is particularly so for the critical time period immediately after the system is installed when enterprises have the opportunity to take corrective actions, if needed. Our system dynamics model is an initial attempt to capture the complex dynamic interactions among the characteristics of the organization, business processes, users, the enterprise information system, and interventions by the organization. Our results show that the model can be used to understand the impact of organizational characteristics and interventions on profiles of system use and work done via the system after an enterprise information system is successfully installed.
The obesity trends in the U.S. and many other countries are alarming. Models that can assess the potential impact of alternative interventions are much needed in turning the obesity trend. The purpose of this research is to study the dynamics of obesity in the United States over time to build a generic system dynamics model that can be used for obesity policy analysis at multiple levels. The model is multi-level in the sense that it builds on individual level models for both childhood and adulthood to capture the energy balance and weight change throughout the life of individuals, and aggregates individual level models to population level trends. We discuss the application of simulated method of moments to the calibration of this model. This approach enables community, state, or national policy analysis building on a calibrated model and offers promising methodological advances in model calibration in the field of system dynamics.
This paper builds on a previously proposed approach where fuzzy logic is used to incorporate linguistic variables in system dynamics modeling. The motivation for this approach is to include vague yet dynamic variables that are combined in a meaningful way. The essence of our approach requires the definition of membership functions as representations of the degree to which specific variable attributes hold, the application of a max-min direct inference approach as a way to combine two or more fuzzy variables, and the use of a defuzzification method that captures (summarizes) the joint effect of the linguistic variables. The objective of this paper is to study the implications of using two alternative defuzzification methods (largest of maximum and center of area) and to highlight various interpretation and modeling challenges associated with each defuzzification method. For illustrative purposes we use a variant of a sales and service model that is based on the concepts of product diffusion, backlog accumulation and personnel adjustments and their respective existing modeling representations in the literature. In summary, based on our findings, by substituting the Max-Min operator and eliminating inconsistencies among the fuzzy rules, the defuzzified values behave reasonably for both defuzzfication methods.
Dissemination of system dynamics to project management practitioners is not as widespread as its use for project management theory building within the system dynamics community. This article presents a decision support and training project model built for a global consulting and engineering company. The simulation model comprises the most important work phases within the detail engineering phase of a large investment project in three offices. The model was validated using data from several past projects and in workshops with the company. A user interface was built to aid dissemination and use of the model. The purpose of the model is the bottleneck analysis and simulation of an ongoing engineering project, as well as the simulation of quality, scheduling, and profitability issues when outsourcing parts of the detail plant engineering.
Traditional independent project performance evaluations take time, disrupt business-as-usual, and report one-off performance based on the best data available at the time. The alternative approach for measuring project, programme or enterprise success performance tracking risks moving the focus of work from the technical end goal to the satisfaction of performance measures. In this research, we create and begin testing a method aimed at
Erythropoietic Stimulating Agents (ESAs), have been used in hemodialysis patients since 1988, largely eliminating the need for transfusions to correct the anemia of chronic renal failure. However, current ESA protocols lead to suboptimal anemia control. Questions about the safety of ESAs and clinically desirable hemoglobin levels remain open, despite a series of clinical trials. Moreover, ESAs are expensive: Medicare reimbursements for ESAs in 2008 approached two billion dollars. A process improvement project conducted at Mayo Clinic initiated in 2007 revealed that current ESA protocols lead to (undesirable) oscillations in hemoglobin levels. Recognizing the behavior as a system signature, we developed a bio-pharmacokinetic model of erythropoiesis. Using prior data for a specific patient, the model provides parameters for individualized ESA response profiles. Parameter values are then used to design dosing regimens that achieve the desired results. 650 patients are enrolled in this prototype information system. The percentage of patients who achieved target and stable hemoglobin levels has improved by 40%, ESA costs have been reduced by 35%, and anemia management resource requirements have been reduced by more than 50%. Indications that hospitalizations may have been reduced by 25% are currently under study. Commercial development is underway.
Traditional agriculture is the main source of national food competes with imported products and mostly made by small producers. In recent decades, various policies have been implemented to support this type of farming, such as improving yields through new seed varieties. After trade opening in 1990, this was affected by import products, therefore was adopted mechanisms for protection and price stabilization. On the other hand, in this decade, public spending in infrastructure increased substantially vial. However, several studies show that the situation of small farmers in this agriculture has improved just slightly despite the fact that for example the policy of improving varieties has been successful in increasing yield improvement.
Singapore is one of the worlds most rapidly ageing nations, and the country is facing a number of health care policy issues, particularly including the care and treatment of ageing-related dementia. To help inform policymakers about dementia treatment and care, we constructed a System Dynamics model that addresses changing population characteristics, incidence and prevalence of dementia, and a population-level natural history of this pernicious condition. This article (a) describes how a discrepancy between measured census data (reference modes) and simulated population led to improved estimates of the population, (b) introduces a novel and generalizable means to simulate how the prevalence of mild, moderate, and severe dementia is likely to change over the next 20 years, and (c) provides comparisons between two means of prevalence estimation.
While there are many models of what would constitute effective health practice, the theories that people use to implement them are less well articulated. However, those charged with designing the implementation programmes for these models of health practice have internal mental models that comprise their theories of change and which guide their actions.
In this paper a novel non-smooth model for a national energy market and its extension to n-countries is proposed, showing several differences from the traditional smooth models. The study begins with the classical treatment of system dynamics theory and jumps to non linear dynamical systems theory finding mathematical results about its complexity. Such results are important in creating processes of integration energy policy between countries, as for example in the latinamerican region, because trough of bifurcations diagrams (from dynamical systems theory) is possible to know what are the all possible scenarios of the system giving robustness to the decision making.
This paper examines dynamics following introduction of nutritious food by a company well known for high-motivational and low-nutritious products. Employing a system dynamics model, we investigate how consumer dynamics affect uptake of the disruptive product. Our example is the burger chain McDonalds, which introduced salads, fruit and other healthier options in the early 2000s. Focusing on consumer choice, we analyze the process of newcomers trying McDonalds and either becoming core customers, or not. It is important to distinguish overall post-introduction commercial success, from sales of the new product per se. We examine conditions that separate commercial success (by drawing in new types of customers, whether these are the profitable ones or whether they simply accompany more burger-eaters), neutrality (in which existing customers simply change over), or failure (by alienating existing customers so that they abandon the company). We focus on the role of heterogeneity in products and consumers, and on interactions with network effects. We consider in detail the large and inertial installed base of pre-existing burger eaters, and the degree to which its dominance is hard to unseat, drawing parallels with reactions to other disruptive and 'progressive' products in industries ranging from consumer products to electric vehicles to utilities.
The advent of Internet and other communication technologies has drastically increased the volume of communication in human societies. One might hope that increased communication will lead to a higher degree of mutual understanding and resolution of conflicts. An opposing, and somewhat counter-intuitive, point of view is that the reduction in the cost of communication would make it easier for people to interact with other like-minded individuals despite geographic distance, thereby polarizing the society. In this paper, we study some of the basic dynamics underlying this problem. We develop an agent-based model to capture the dynamics of an online community where agents post stories and read and vote on others stories. We show that different combinations of parameters can lead to different macro-level behavioral modes in this model, and give anecdotal evidence from a large online community to support the predictions of the model. In particular, we identify four types of communities based on their dynamics: majority dominated, competitively polarized, converged, and diversified. We discuss the implications of each of these forms on the social welfare and the stability of the community.
The ECOWAS region (Economic Community of West African States) has big potential, but it faces major challenges in its development. To help support the decision making of regional and national leaders and bring a wide variety of stakeholders from all member states into policy debates, the ECOWAS T21 model was developed. The initial focus of the model was to test the consequences of regional integration of 1) free movement of people and commodities; 2) integrated energy, transport, and telecommunication infrastructures; and 3) creating a monetary union. When building and calibrating the model, another challenge was identified: fast population growth would make it difficult to improve the well being of the people in the region, even with successful implementation of regional integration. As a result, a family planning scenario was added. Results from the model show that a combination of regional integration and family planning policies generates the best results: smaller population, longer life expectancy, higher GDP, much higher per capita GDP, higher total government revenues, a lower poverty rate, a lower unemployment rate, more forest land, and higher per capita cereal production. However, any good policy could have its costs, such as higher oil demand and lower oil exports in this case.