This paper explores the foundation of the financial accounting model. We examine the properties of the accounting equation as the principal algorithm for the design and the development of a System Dynamics model. Key to the perspective is the foundational requirement that resolves the temporal conflict that resides in a stock and flow model. Through formal analysis the accounting equation is redefined as a cybernetic model by expressing the temporal and dynamic properties of its terms. Articulated in that form the accounting equation is enabled to be defined as a dynamic stock and flow model expressing the two dimensions of the double-entry accounting system. With that formal foundation it is argued that the accounting model is capable to simulate financial dynamics as well as be integrated with models that express operational and world dynamics. Thus we prove that it is possible to design and build a dynamic business model that can meet requirements of management accounting (ex ante, before the fact) as well as financial accounting (ex post, after the fact). We conclude that the dynamic accounting model can be made relevant for strategic planning and control purposes and be integrated within a System Dynamics model designed for such purposes.
This paper extends recent systems approaches to US health reform to the international sphere and explicitly represents the political and economic dimensions of health policy. The worldviews of health care as an industry with user as consumer, a profession with user as patient, and a societal right with user as citizen. Historical institutionalism and agency theory in health policy are represented and integrated, with focus on the extent and interaction of hierarchical, market and network control mechanisms on key system performance goals. This work can inform simulating international comparisons of health systems evolution and explicitly representing their strife of less tangible political and vested interests, in order tounderstand, plan and test the acceptability of proposed health reforms in various countries and regions KEYWORDS: Health Policy, Health System Dynamics, Health Politics, Health Economics.
How long could an organization survive without its information systems working efficiently? Frequent changes of the systems to protect, significant delays between efforts and results, the large amount of involved variables and the difficulty to measure some of them make security management a challenge for current companies. Simulation models provide a virtual environment that can help analysing the dynamic balance between the affected key factors. These key factors include technical controls (Software and hardware elements to protect the system), formal controls (Procedures for guaranteeing an efficient use of technical controls) and security culture (Human factors that affect the compliance of the designed procedures).This paper presents a real modelling process, involving a university team and two companies. The paper includes information about the used methodology, the process and the preliminary results of the obtained model. This process has allowed concluding that the obtained benefits are very promising.
Though the size of System Dynamics models should be compact focusing on the main feedback loops determining system behavior one kind of model can become quite large: multi-national, multi-sectoral spatially differentiated models. The paper briefly presents such a model called ASTRA (=Assessment of Transport Strategies), which is developed in several versions over the past eight years.
The purpose of the paper is to describe an approach how such a system dynamics model despite its size can be calibrated to make it applicable for Europeanwide policy analysis of transport policies. The approach is designed as a sequential process involving an au-tomated tool combining a C-coded steering programme with the Vensim® optimizer to enable calibration of large numbers of similar equations that only differ by their pa-rametrization.
This paper continues a line of work that took up previously published stock-and-flow thinking studies and proposed to apply the model of implicit learning to the case. According to this model, novices have to elaborate personal experience by following rules. After previous trials, a set of such rules is proposed together with a group of challenges that allow to apply and to learn them. A conceptual model for representing the rules, the challenges, the learners and their learning itinerary are proposed. Then, the design for an on-line system for publishing and working with challenges and to monitor progresses is introduced. This software system is currently under construction and first data from its use will be presented at the conference
This paper suggests that the misperception of feedback individuals show may depend on the frame presented to them. A brief summary of Kahnemans work about heuristics is used to argue that the Beer Game may not be neutral: its very presentation may influence the cognitive processes and the observed performance. Some modifications to the Beer Game material and rules are proposed in order to make the feedback and delay structure more easy to grasp. Empirical work with the modified material is currently in progress.
This paper describes the innovative research approach of a project that has recently been funded by the Swiss National Science Foundation (SNF). The project aims at analyzing and accelerating managerial and organizational adaptation processes that foster the diffusion of pioneering energy efficient technologies in the building sector. Psychological, managerial, and economic theories as well as results of empirical investigations about antecedents of behavior choices will be synthesized into a simulation model for a middle-sized Swiss city. The model will shed light on dynamic interactions between behavioral factors (e.g., planning, decision making and routines of the relevant actors in the building sector) and contextual factors (e.g., technological innovations, public initiatives, and market conditions), thus explaining the diffusion of energy efficient buildings in a community. The objective of the paper is to discuss the chosen approach, to explore the nature of the topic and present first research heuristics.
The assessment of nuclear energy systems asks for a modeling of the worldwide nuclear reactor park including all supply chain details, i.e. the nuclear fuel cycle, demands for an integrated nuclear energy system model which also includes feedback loops representing physical feedbacks within the system as well as, and most prominently, socio-political feedbacks in the decision-making on the various available deployment pathways for nuclear energy. Despite the availability since the early 1960s of detailed model-codes for nuclear reactors covering physic, supply chain and economic aspects of nuclear energy, development of a truly system dynamics view on nuclear energy development only recently gained worldwide interest.
This paper will bring an overview on the role of nuclear fuel cycle centres which have recently regained interest in the light of a perceived growing importance of nuclear energy in the worlds energy provision and the inherent proliferation concerns this might entail. Using the DANESS nuclear energy system dynamics code, ANL performs a comprehensive study on various nuclear energy deployment scenarios in six world-regions and the potential role that such regional nuclear fuel cycle centers may play in facilitating such nuclear development while respecting proliferation concerns. The paper will conclude by stressing the importance of a system dynamics perspective in addressing such nuclear energy system deployment scenarios.
Many organizations today use a bell-curve for performance evaluation process. They reward a small percentage of top performers, encourage a large majority in the middle to improve, and lay-off the bottom performers. Companies believe that such pay-for-performance system encourages employees to perform better. The question we explore in this paper is: does the system increase the overall performance of the company over time?
We observe that pressure, if maintained below a certain level, can lead to higher performance. However, with lay-offs, constant pressure demoralizes employees, leading to drop in performance. As the company shrinks, the rigid distribution of bell-curve forces managers to label a high performer as a mediocre. A high performer, unmotivated by such artificial demotion, behaves like a mediocre. Further, managers begin to reward visible performance over the actual. Finally, the erosion of social capital could cripple the company.
We recommend the use of a semi-bell-curve where someone who performers like a top performer is rewarded as one. Further, we recommend balancing pressure and morale. We recognize that such a balance is very difficult to strike, and can be successfully achieved only by decoupling to some extent the performance evaluation process from the issue of lay-offs.
Present fuel prices trigger a renewed interest in the energy debate. The paper extends the debate
beyond the present boundaries with a descriptive model that maps two parallel processes on earth: (1)
the stocks & flows of energy, developing between the earths main energy source: the sun, and its main
energy sink: outer space, and (2) the accumulation of a collective memory on earth in the form of
genetic information in living organisms (DNA), and in the increasing number of Bytes of information
created by humans. The model makes it possible to think through the parallel developments of
energy and information, and of the parallel growth of activities that goes with it. It also provides a tool
to distinguish the stocks and flows of energy that drive the economic activities on earth. This may help
the debate to go beyond the stage were all energy remains equated to non-renewable resources, just
like it was equated to horse power in the past.
The purpose of this paper is to show that a simple systemic model is able to imitate the behavior of a complex economy as the Brazilian one.The main identified features of the Brazilian economy are:1) the short term growth rate is influenced in an important way by the effective demand; in the medium term, however, the growth is restricted by real factors such as the capital stock and the capacity to import ; 2) attempts of growing above the rate allowed by those restrictions accelerate the inflation rate or provoke unbalance in the balance of payments; 3) in both cases, the government is forced, earlier or later, to adopt restrictive monetary policies to reduce the final demand growth rate, reducing the domestic absorption of resources; 4) an important leverage point to reach a sustainable growth path is to create conditions for a consistent increase of the exports. 5) the growth of exports in the medium term, however, requires significant investments in competitiveness acquisition, without which the country will be limited to sell products in international markets already saturated such as the one of commodities and, therefore, with limited growth potential.
The issue of the growing federal debt and whether it will be serviceable in the years to come is addressed. Can the U.S. federal government continue to expect its tax revenues to rise to the occasion? Will the retirement of seventy-seven million baby boomers result in diminished federal revenue after the year 2010? Will the changing tax structure reduce federal revenues? Will these circumstances lead in-turn to an incapacity of our federal government to service its burgeoning national debt, now nine trillion dollars? Are there probable disaster scenarios that policymakers must navigate using judicious policy choices? Is it time to start drastically cutting the federal budget? These are the questions that get addressed by the simulation models we will present.
Various attempts have been made to construct dynamic simulation models of the system archetypes. This paper examines the eroding goals archetype and hypothesizes that achieving classical archetypal behavior over time requires the inclusion of structures that are technically outside the common description/definition of the archetype. Four dimensions of managerial decision-making sensitivity are introduced into the model in order to achieve the expected dynamic behaviors described in the literature.
This paper develops a model to understand self-organizing markets. This kind of markets is characterized by a highly skewed distribution of firms size, so a way to explain them is by introducing increasing returns to the growth of the firm. In this paper, besides, I show how urn theory can be used to formalize the model suggested in this paper.
This paper analyzes the reactive management approach used in the Las Vegas Valley to manage particulate matter (PM) pollution, demonstrates that system dynamics concepts can improve the current strategy, and proposes a more proactive approach to management. Two decision support systems (DSS) were compared for this analysis: the current, linear proportional rollback model and a system dynamics model attempting to capture the essential feedback structure causing the problem. A retroactive policy analysis, beginning in 1960, was performed to analyze the benefits and tradeoffs of a more proactive management strategy. The analysis showed that including a system dynamics perspective does improve the validity of the model and the usefulness of the DSS for policy analysis. Preliminary analysis shows that a proactive approach to management may lead to more effective policy options and greater flexibility in managing this problem but may have prohibitively high initial and/or sustained costs in some cases.
The current avian influenza in Asia, Africa, and Europe has sparked discussions of a new human pandemic influenza perhaps hitting the world. While the current influenza is not spread by human-to-human contacta necessary characteristic for a human pandemicthere is a potential that it may become so. Since the pandemic does not currently exist, it is not known what characteristicssuch as infectiousness and death ratethe disease will exhibit. The study conducted by the Critical Infrastructure Protection Decision Support System (CIPDSS) explores the possible mitigation strategies and their effect on the US economy. Results show that while many people may be infected, the economic costs for the US are relatively low compared to past economic perturbations.
Global warming has emerged as the dominant environmental problem of our time. The next fifty years will be a period of growing accumulation of greenhouse gasses (GHG) in the atmosphere and rising temperatures. It could also be a period in which the nations of the world adopt more stringent policies to control the emissions of carbon dioxide (CO2) and other GHG. If emissions are cut sufficiently, it is possible to stabilize GHG within the first half of the century. The risks of global warming could be reduced, but not eliminated. This paper describes recent applications of system dynamics to improve our understanding of climate change, and it looks ahead to the potential contributions in the future.
This paper explores the dynamics of population levels in Mayan lands from the Late Preclassic to First Contact, roughly 500 BC - 1500 AD. It starts with a simplified version of the Limits to Growth model and adds the effects of warfare on available production. Drawing also from the 1976 MIT paper "A Case Study of the Classic Maya Collapse (D-2429), this paper explores how humans can politically intensify resource shortages into universal disaster.
Management of a product development pipeline involves starting and steering several promising projects through a sequence of screens known as stages/gates. Only projects with payoffs above a predetermined threshold survive each screen. We model a two-stage product development pipeline as an aging chain with a co-flow. The co-flow structure tracks the number of projects and the corresponding net present value (NPV) of payoff. Managers at each stage must decide on capacity utilization, subject to a trade-off between throughput and value creation rate. Our simulation study mimics a range of relevant decision scenarios by varying the number of starts, screen thresholds, and managerial biases while adjusting utilization. Results illustrate that screening can eliminate the backlog bullwhip effect in the pipeline. Allied statistical analysis indicates a non-linear relationship between the number of starts and the value created at end of the pipeline. An increase in the screening threshold, in either stage, increases the average value of the projects but reduces the total value created. We also show that a managerial bias towards reducing backlog, instead of improving utilization, affects the average NPV negatively but does not affect the total value created at the end of the pipeline.
Intensive pig farming in Centre China leads to the centralization of excreta .Chinese government has allocated lots of funds to construct biogas engineering for resource utilization of bio-energy in recent years. But investigation shows most of farms in rural areas discharge the residual product of anaerobic digestion directly due to the lack of consumers and funds, which has caused severe environmental pollution, and also endangered the development of farms themselves. In this paper, we have constructed a practical pig farming excreta recycle treatment model via a case study of the Lanpo intensive pig farming ecology system, and have conducted simulations with the corresponding dominant archetype. The results show that policies of encouraging more farmers to utilize biofuel, separating anaerobic digester effluent from irrigating water, developing the winter fallow cropland and the hilly land and governments fund and technology supporting may help shift the system toward sustainability.
Schedule overrun is a major problem that disturbed software project team. How to solve this problem? For most software project managers, the first reaction is to work overtime. There is no doubt overtime can alleviate this problem to some extend, but is it an effective way all the time? If not, when shall we give up overtime and change to other ways? This paper analyzed those problems in detail and gave some conclusions in the end. That is for a software project team which has reached its overtime limit, further overtime can only result in much longer completion date. Thus the best overtime policy is to first set a proper scheduled completion date, then try to find the minimums project completion time. The overtime range related to this minimums project completion time will be the critical point to stop further overtime.
There is a strange phenomenon in medicine market of china: abuse of a lot of expensive medicine such as antibiotic, while the low price medicine disappearing in market, and the medicine price is going higher and higher to pay for by patient. This is indeed a disaster in health care system of China. In this paper, we set up a system dynamics model to demonstrate the deep mechanism: this is mainly due to medicine price policy; afterwards, a serials policy is proposed to handle this disaster.
The U.S. Transportation Security Administration (TSA) is collaborating with a team of system dynamics modelers from the national laboratories to build a model of their security checkpoint operations at US commercial airports for the purpose of proactively identifying high-leverage opportunities for investment to improve system performance. To elicit a broad range of expertise and opinions to develop our understanding of the systemic issues facing TSA as they strive to improve their security checkpoint operations, we conducted more than 30 interviews with headquarters and field-operations staff and hosted a 2-day group model building exercise. In this paper, we use both causal-loop diagrams together with a description of the results of the group model building exercise to present a rich articulation of the issues facing TSA in managing their security checkpoints. We also show how the complex interrelationships among various factors ultimately impact the effectiveness and efficiency of the aviation security checkpoint.
Modeling for enhanced understanding of complex systems with policy-oriented implications sometimes requires that several different levels of aggregation be considered and formally included. In the system dynamics tradition, different levels of aggregation are not normally combined, leaving certain classes of problems outside of the traditional use of system dynamics models. Agent-based models can capture a very fine-grained level of detail of the system under study but lack the ability to parsimoniously and clearly link behavior to structure. This paper presents a domain in which a combined approach seems to be adequate. Additionally, two alternatives to dealing with the problem of integrating data from different levels of aggregation using system dynamics and agent-based models are discussed.
Several classical system dynamics models, such as models of disease spread, and technology adoption,
are built under assumption of a homogeneous population. These assumptions have been recently
challenged by recent results showing that the degree distributions of many social and natural networks,
such as the so-called scale-free networks, exhibit long-tailed degree distributions. This paper adopts a
system dynamics approach to replicate preferential attachment, one of the network dynamics
mechanisms known to produce power-scale distributions. We then study the diffusion processes on
these networks, e.g. epidemics, product adoptions. We consider a basic compartment model
(Susceptible- Infected) and apply scale free network topology in place of the random network topology
that is traditionally assumed. The resulting model is used to assess the effect of the topology on the
diffusion of attributes throughout the network.
The Health Policy Special Interest Group will have a wide-ranging discussion about its members' work in the area of chronic illness. Topics will include diabetes, mental illness, cardiovascular disease (CVD)and its risk factors, and health planning as it relates to chronic illness. Members will discuss their experience in applying SD in these areas, new insights developed as a result of using SD and impact that was achieved, and further opportunities they see for SD to help improve thinking and policymaking about chronic illness. The session will conclude with a very brief HPSIG business meeting. All interested ISDC attendees are encouraged to join us!
This paper develops a model-based analysis of the effects of various capacity incentive systems on new investment in the Korean electricity market. The restructuring process in Korea allocated power generation to six firms, competing within a wholesale market, albeit strictly on a cost basis. Because of this cost-based pool, capacity payments were also introduced to encourage new investment. However, it is an open question whether the current fixed capacity payment scheme is enough to secure resource adequacy and consideration is being given to alternative mechanisms such as the use of LOLP. Using a detailed market simulation model, based on system dynamics, we compare these approaches in terms of how they may influence the investors decisions and thereby determine the system reserve margin. The simulation results suggest that there may be serious problems is staying with the current fixed capacity payments in order to achieve resource adequacy. In contrast an LOLP based capacity mechanism may, in the longer term, increase the reserve margin compared to a fixed capacity payment. More generally, this paper indicates how crucial the effective modeling of the investment behavior of the independent power producers is for adequate policy support, even if they only constitute a fringe in a substantially centrally influenced market.
Electronic networks of practice can help an organizations discover and share knowledge more effectively by facilitating learning both from within the organization as well as from entities outside the organization. In those instances where firms have linkages with outside organizations, however, the acquisition and sharing of knowledge takes place free from the constraints of hierarchy and local rules. These networks can be characterized as loosely structured, and generally self-organizing, which are made up of individuals who voluntarily participate in the creation and sharing of knowledge. Building networks without formal boundaries is a challenging task for any organization. This is because those responsible for building them must not only have to encourage the use of the new tools, but also refrain from intervening too often. The objective of this paper is to conceptualize a simulation model, with which we can test the effects of structural interventions in electronic network of practice. Simulation results indicate that: (a) too much structure (rules, regulations, and group commitment) can result in a decline of network attractiveness; (b) lack of structural interventions can lead to a network that only attracts those people who prefer an environment without any form of control.
In this study we use system dynamics to evaluate possible development scenarios of agricultural sector in Latvia. Growth and balancing forces of agricultural economic are investigated along with dynamics of capital, land and labor allocation. Resource stocks are considered from two perspectives: a) breakdown between crop and livestock farming activities b) allocation between commercial and self-subsistence farms. Total production output and per-capita income of the population employed in the sector are chosen as key development indicators. Impact and efficiency of public support policies for agriculture are discussed.
Previous research suggests that decision makers have the tendency to keep on investing in losing courses of action. The present study focuses on de-escalation and proposes causal loop diagrams as a technique to decrease escalating commitment in a failing action. The effectiveness of causal loop diagrams is also contrasted with the effect of receiving a list of important factors. Causal loop diagrams were found to decrease commitment as compared to having no decision aid. However, no significant difference was found between causal loop diagrams and a list of important factors as a de-escalation technique.
Elderly patients use more medications given the prevalence of co-morbidities putting them at risk of experiencing medication errors. A highly anticipated strategy is the implementation of health record solutions, namely a mix of shared electronic health records and personal health records. This intervention provides information for all individuals involved in the medication use system (patients, carer, doctors and pharmacists) and enables them to make more informed decisions throughout the medication use process (prescribing, dispensing, administering, monitoring of medications). However, it is difficult to direct the design of such an integrated health record solution that takes into consideration contextual factorsand its impact on, existing interventions and society. Traditional methods such as random controlled trials lack the capacity to capture the scale of the problem and are inadequate in terms of time frames, cost, resources required, and non-applicability of trial settings. Multi-scale simulations can represent the systems different spatial and temporal resolutions providing a logical and consistent framework for dynamic analysis and a means to design and test health record policies to cover a range of possible futures in a risk-free environment.
This paper is a concept paper about a suggestion proposed by Nathan Forrester, in the last year conference to extend eigenvalue analysis to nonlinear models. His idea was to consider higher order terms of the Taylor series expansion when approximating nonlinear models. In this paper, we demonstrate the feasibility of Nathan's idea. The main contribution of this paper is to devise a pragmatic approach to solve the resulting equations of Taylor series expansion. This pragmatic approach is based on our novel concept of 'smoothed Jacobian' matrix, which is computed from both the ordinary Jacobian matrix and the set of Hessian matrices. Recall that the elements of the ordinary Jacobian matrix represent slopes of relationships, while the elements of the Hessian matrices represent curvatures of relationships. So by integrating the elements the ordinary Jacobian with the elements of the Hessian matrices, we are actually smoothing the slopes given the knowledge about curvatures. Consequently we are smoothing the time trajectories of eigenvalues and eigenvectors in nonlinear models.
Building upon previous work in the field of system dynamics, a generic model of multiple improvement programs is outlined. The model is used to create insightful stories on success and failure in process improvement initiatives. The simulation experiments reveal that plants should strive for implementation patterns that focus on programs exhibiting higher organizational complexity rather than technical complexity. Furthermore, the simulation analyses provide insights in the interplay between organizational learning, program commitment, and process improvement. The value of the conducted approach lies in the explicit investigation of the impact of varying improvement program patterns on plant performance.
This paper revisits the use of trend forecasting in driving policy in social systems by comparing it with
derivative control in classical control theory. While both processes involve use of trend to determine
policies for achieving reliable performance, the outcomes of the former have considerable variability while
those of the later can create improvement in performance with certainty. The similarities and differences
between the two processes are discussed and guidelines suggested for improving the efficacy of trend-
forecasting in policy design in social systems.
In the modern information based society, failure of software systems can have significant consequences. It has been argued that increased attention to testing activities during the software development process can mitigate the probabilities of system failure after implementation. However, in order to justify investments in improved testing, the economic impacts of improper testing should be identified. In this paper, we propose a systematic approach to the evaluation of the economic impacts of software testing. The main factors affecting software testing are identified, and a computer simulation model is developed to investigate different testing scenarios. Usefulness of the suggested approach is demonstrated through several exploratory simulations. The results prove the utility of the System Dynamics modelling approach in building better understanding of the impact of software testing. Implications for software development practitioners, researchers, customers of software products and software support organisations are also discussed.
The complexity of modern networked systems has negative consequences in the form of intended and unintended security incidents. Information security is not the first field to grapple with such challenges. In safety, incident learning systems (ILS) have been used to control high risk environments. Many of these systems, such as NASA's Aviation Safety Reporting System, have demonstrated considerable success while others have failed. Prior to implementing ILS in information security, it is prudent to learn from experiences gained in safety. We use System Dynamics to investigate how factors such as management commitment, incentives, recriminations and resources affect a safety incident learning system. We find that the rate of incidents is not a suitable indicator of the state of the system. An increasing or decreasing incident rate may both be caused by either increased or decreased security. Other indicators, such as the severity of incidents, should be used.
In this paper, we propose a new approach to network bandwidth estimation based on System Dynamics modelling. The paper discusses existing approaches to bandwidth estimation and network capacity planning. Limitations of these approaches are presented and the case for using System Dynamics is made. Applicability of the proposed approach is demonstrated through a real world network planning project for a distributed logistics application. A practical computer simulation model was developed to predict bandwidth requirements for the projects network. This model provides system planners with the ability to test different possible scenarios in order to make informed decisions about the system architecture. We show through practical results of the simulation runs and the insights gained during the process that the System Dynamics approach offers an effective solution to the problem of network bandwidth estimation and system planning. The paper concludes with a review of the results and pointers for further research.
We will explore how to value using modern financial techniques the development of new alternative energy technologies (AETs) given uncertainty. Uncertainty in developing AETs derives from: (1) the reduction in installation cost of new generation capacity as experience with the technology is gained, i.e. the learning curve (2) oil and natural gas price cycles; and (3) other macroeconomic and geopolitical forces, particularly the behavior of national oil companies (Aramco, PDVSA, PEMEX, etc.). Evaluating a new AET properly requires representing these uncertainties as well as an investment valuation approach that works well under high uncertainty. In particular, we propose to adapt the real options methodology to value the potential return from developing AETs using stochastic system dynamics models representing the uncertainty in both the learning curve and the fossil fuel price cycles.
Laboratory experiments of commodity markets have used the Cobweb design to investigate market dynamics. The predicted cycles of the Cobweb theory did not occur. Arango (2006) adds complexity and realism to the Cobweb model and observes stronger fluctuations and autocorrelation. He shows that these fluctuations are quite symmetric and similar to the behaviour observed in one category of markets. However the fluctuations are different from the asymmetric price behaviour observed in other commodity markets. We hypothesise that asymmetries could be caused by non-linear demand, different from the linear demand curve used by Arango. Consequently we replicate his experiment using a demand structure with constant price elasticity and dynamic adjustment. Similar to Arango, the supply side is complicated by capacity lifetimes and investment delays across treatments. Compared to the previous results, this experiment gives rise to larger fluctuations and stronger asymmetries
The role of Intellectual Property Management in facilitating the agricultural transformation process in developing countries is unknown and discussed in a very controversial way. This paper conceptualises a framework for assessing the impact of Intellectual Property Management on the seed sector in West Africa. At the core of such assessment is a system dynamics model that describes the dynamics of a seed value chain. We use data from interviews with multinational seed companies, research institutions and private sector actors in Ghana for developing a conceptual simulation model and for specifying the impact assessment framework. Different scenarios are to be established to test a variety of Intellectual Property policies. The interviews we conducted suggest that there is local demand for such an overview analysis and the discussions we had about our approach indicated an immediate contribution to the understanding of the entire seed system.
This paper presents the first phase of a work in progress which aims at building a System Dynamics model around two theories concerning internal conflict. In particular the model will asses the particular case of Colombia. The different theories around the economics and causes of war can be separated in two trends. The first one argues that wars are economically motivated, and the real objective of armed groups is the quest for money; this theory is characterized under the term greed. On the other side, there are the social, political and historical factors that allow and facilitate the emergence of armed groups (grievances). This investigation aims to develop a better understanding of the complex interactions around the Colombian conflict, considering both theories and seeks to build a better comprehension of this conflict in order to study how to generate development during an internal conflict.
This paper presents a case study of an analysis of a Corrective Maintenance process to realize performance improvement. The Corrective Maintenance process is supported by SAP, which has indicated the performance realisation problem. System Dynamics is used in a Group Model Building process to structure the problem and to develop a dynamic business model with which the process is analysed. This is performed by the evaluation of changes in external factors and interventions in the process on performance indicators compared to a reference run. The case study has shown that modelling this maintenance performance problem is possible with System Dynamics, but the method is more suitable on an aggregated level. Although the results of this simulation study are significant, one of the conclusions is to not automatically assume that System Dynamics is suitable for problems that are structured with Group Model Building. It is recommended to select another modelling method after the problem is structured, if that method is more suitable.
The study represents an exploration of the Italian energy situation, which is characterised by huge energy imports, strong dependence on fossil fuels, and carbon emissions well above the Kyoto target. Certainly, in such a situation, given the nuclear energy ban of the Italian 1987 referendum, renewable energy could help the country. Nonetheless, its high costs could be an obstacle that strongly limits its expansion. One of the main results of the analysis performed with the IRED (Italys Renewable Energy Development) model is that an increase of the renewables share up to 20% in 2020 represents a striking change in the structure of the Italian electricity system, which, under certain conditions, is not feasible. Italy faces a sort of triangular challenge, involving fossil fuel prices, renewables production costs, and carbon prices. The trends in these variables will decide the destiny of renewables in the country.
Public documents identify broad strategies for reducing the burden of cardiovascular disease in the U.S., but they do not specify how best to allocate limited resources. Such specific guidance is lacking in part because of gaps in data on intervention costs and effect sizes, but also because the many factors contributing to cardiovascular risk interact through pathways and stock-flow structures that defy simple calculation. The U.S. Centers for Disease Control and Prevention (with support from the National Institutes of Health) is using SD modeling to better understand these complexities and to evaluate potential intervention strategies in terms of their impacts on adverse events and costs over the coming decades. The project considers interventions that might be undertaken at a city or county level, including interventions to improve health care, physical activity, nutrition, mental health, tobacco control, and indoor and outdoor air quality. Construction of the model has involved working with subject matter experts as well as collaborating with the Austin/Travis County, Texas, health department, which has gathered a broad spectrum of local data on population health and interventions over the past several years. This collaborative effort is helping to translate the science of cardiovascular disease into a form that is policy relevant and that can help many communities do a better job of allocating their public health resources.
A system dynamics model is composed of many variables. These variables simplify complex phenomena and provide a description of a systems current state or problems. Basic variables that describe the real-world urban development can be established from the elements that make up a citys different dimensions such as industry product, population growth and vacancy rate. The urban development framework takes a system-based approach by systemizing the citys internal elements. The systemic variables then provide not only a clear reflection of the interactions between all of the sub-systems but also how they relate to the overall system. It is therefore very important to select the appropriate variables. Most variables of system dynamics models are, however, set up by the designer, served as a subjective and unscientific approach. This study therefore applies the Fuzzy Delphi Method to the selection process of system variables to increase the confidence of the model. This was accomplished by first examining the system relationships as well as the intent and meaning of the sub-system variables to be created. After establishing the criteria for variable selection, an empirical case study was used to devise the evaluation variables for each sub-system.
Micro-lending has been introduced as an effective antipoverty tool in recent decades. However not all of micro-lending institutes are successful both in accomplishing their mission and in loan recovery. According to World Banks focus note (2006), less than a quarter of its projects that funded micro-lending were judged successful. This paper describes a specific type of micro-lending (Grameen way of micro-lending invented by Mohammad Yunus, Nobel Peace Prize winner 2006). Then it summarizes the differences of conventional bank and Grameen Bank. Also this paper illustrates the important loops that make the Grameen successful both in the loan recovery and in accomplishing its mission. The final contribution of this paper is to develop a system dynamics model to test some Grameen policies that researchers believe are the key elements of Grameens success. I find support for the fact that small loan size which is designed to match the clients knowledge maximizes Grameens capital. Also the model finds that investing some portion of Grameens capital, giving loan to groups of people and choosing appropriate interest rate are crucial for Grameen Bank.
This paper presents an analysis of systems thinking interventions in educational settings. Although these interventions have been implemented in K-12 classrooms since the mid 1980s, there is still no clear definition of systems thinking or identification of the best method to test the effectiveness of interventions or methods for teaching systems thinking The goal of this paper is to answer the question: how can we best assess the effectiveness of systems thinking interventions in education? This question begs three sub questions: (1) what is systems thinking, (2) what systems thinking interventions are being used in education, and (3) how have the effect of interventions been measured? The purpose of answering these questions was to propose methods for assessing systems thinking interventions. The analysis of systems thinking interventions in the classroom yielded an initial set of guidelines for measuring and raising a persons level of systems thinking.
The Canada's Air Force (CAF) has been faced with a challenge of retaining skilled, qualified, and trained members. It is common that every year approximately 10 to 15 percent of members from almost all occupations leave the CAF at various ranks. Due to such consistent loss of members, shortage of members has been causing a multi-dimensional undesirable impact (such as work overload, imbalance between work and family life, delays in training and promotions) on the existing members. The researchers at the CAF have identified factors such as low pay and benefits, undesired postings, work overload, and more engagements in non-job related activities. This research explores the underlying structure that drives attrition rates. A formal simulation model is developed that replicates the attrition problem of the CAF. The development of the model uses the data collected through interviews of subject matter experts, and reports of previous work carried out by the CAF staff. The parameters of the model are calibrated based on numeric data of last seven years. The model results are quite promising and consistent in replicating the historical data. The simulation model presented here demonstrates the capability of evaluating the relative benefit of polices aiming at controlling the attrition rate.
The scientific community agrees global climate change caused by anthropogenic sources of greenhouse gas emissions (GHG) is occurring, and the projected rise in average global temperatures as a result of climate change could lead to serious consequences for human health, economies and the environment. The transportation sector is a significant source of CO2 emissions, and in the United States accounts for 28 percent of GHG emissions. Because of transportations considerable contribution, the federal government and states have explored and continue to consider ways to lower CO2 emissions from this sector. Biofuels in particular are a popular option for addressing climate change and two main types of biofuels policies have received much focus recently for their potential to reduce GHG emissions from the transportation sector: the renewable fuels standard (RFS) and the low carbon fuels standard (LCFS). It is important to analyze and compare these two policies with regard to their potential contribution to the overarching goal of reducing CO2 emissions. By assessing the RFS and LCFS specifically for the state of Minnesota, this project seeks to address the question: How can Minnesota maximize the contribution of biofuels to CO2 emissions reductions through state-level policy?
In this work we develop a SD model for a make-to-order (MTO) three-stage capacitated production/inventory system. We employ a production order release mechanism affiliated with the automated pipeline inventory and order based production control system (APIOBPCS) policies family. The production rates at each stage are defined under alternative policies. One of the policies considers the human behavior in the decision making process. The robustness of the alternative policies is investigated through the dynamic response of the system under step and pulse changes in demand. Finally, the efficiency of the alternative policies is examined by means of six performance criteria.
The paper analyzes the geographical diffusion of system dynamics in academia using information on the affiliations of authors who have contributed to the System Dynamics Review. The paper develops and interprets a set of descriptive indicators that allow the identification of sustainable adoptions of system dynamics in a particular country. Longitudinal analyses indicate difficulties in the diffusion process and point at policies potentially advancing the further dissemination of SD.
This paper explores the events that engulfed Northern Rock plc, a UK publicly listed company, during the latter part of 2007. The background to those events that took place is illustrated together with their consequences for Northern Rock. A model of the Northern Rock liquidity situation is produced and tested using the System Dynamics paradigm and methodology. The resultant model is verified and validated with reference to known behaviour and data. Hypotheses are constructed resulting in conclusions which centred on the need for co-operation between the Tripartite Authorities and Northern Rock together with a need for active, coordinated management action. Within the limitations of the model different means of coping with banking credit problems are illustrated and remedies postulated. The model presented could be further developed to produce recommendations for automatic triggering of interventions. A variant of the model could be adapted to model contagion risk. These, together with others, are areas for further work. Methodological conclusions are that the model correctly exhibits linear behaviour if not actively managed, that the model contains both continuous and discrete elements, that there is scope within the model to adapt it for use as a teaching/study aid in finance and/or System Dynamics.
Rework cycle is at the heart of modeling projects, one of the major application areas of system dynamics. In this paper we introduce a new formulation for rework cycle in which multiple defects may exist in a task. We compare the performance of this formulation with three others, two adopted from the system dynamics literature and one agent-based formulation. This comparative study illustrates the impact of assumptions about the nature of defects and the homogeneity of tasks on behavior of alternative models and provides information necessary for selecting rework cycle formulations effectively. The new formulation we introduce allows for capturing significant schedule over-runs due to a few tasks, with multiple defects, that may cycle through rework process multiple times. Its perfect mixing assumption, however, over-estimates final project quality. Sensitivity analysis informs the robustness of results to multiple project parameters. We discuss the implications for selecting robust formulations in modeling project dynamics.
Advances in artificial intelligence and optimal control provide increasingly better algorithms for controlling dynamical systems. These algorithms can be applied for policy design in system dynamics models. In this paper we introduce some basic solution concepts and apply the Q-learning algorithm to a simple dynamic model from system dynamics literature to demonstrate potential value of such cross-fertilization. We also extend a state aggregation and partitioning algorithm that may increase the efficiency of basic reinforcement learning models in application to continuous time and space problems. Simulation analysis demonstrates the value of this approach and offers guidelines for future research.
Many important dynamically complex issues are also characterized by a large number of stakeholders. Stakeholders often have different (incompatible) world views, value systems, lifestyles, interests, and perspectives. One way to deal with this diversity in System Dynamics modeling is to use different (cultural) profiles. Cultural Theory offers five profiles that could be used to take this diversity explicitly into account in System Dynamics modeling. This will be illustrated with a System Dynamics modeling study concerning the development of a residential district in which cultural profiles are explicitly taken into account.
Social capital plays an important role in enhancing the efficiency of political institutions and the economic performance of nations. Malaysia is a multiracial country wuth a population of 22.2 millions. The four main ethnic communities are the Malay, Chinese, Indian and the indigenous people of Sabah and Sarawak. The indigenous people account for only about 12 per cent of the population but they comprise of nearly 37 ethnic groups and sub-ethnic groups. As such the importance of maintaining close social bond which encompasses national unity and integration is an important social agenda needed for a successful transformation of the Malaysian economy both economically and politically. This study attempts to assess the level of unity and integration among the diverse ethnic communities of Malaysia on the basis of the hard economic variables extracted from the 1991 and 2999 Population and Housing Census Reports of Malaysia and a sample survey on the social capital of the ethnic communities. A System Dynamics model which integrates both the hard economic variables and the perceived social capital of the ethnic communities is constructed to simulate the scenarios based on different policy options of the government, in terms of affirmative action plan. From the results obtained, strategies are suggested to address issues relating to unity and integration in Malaysia.
This study constitutes a methodological inquiry in a larger research context on transition dynamics, and it focuses on the issue of actor heterogeneity in modeling such processes. On the one hand heterogeneity at the actor level (i.e. heterogeneity among actor groups, heterogeneity among actors in a particular group, etc.) seems to be a very important source for complexity in the observed dynamics, on the other hand introduction of that heterogeneity into the models has a cost of losing some potential of the models to lead to insight development, since they become hard to comprehend in the detail level needed to incorporate mentioned heterogeneity. Hence, as a sub-topic in our wider research objectives regarding transitions, we conducted an experiment on the potential consequences (i.e. gains and losses) of ignoring or recognizing the actor heterogeneity. Three models of the same historical transition case with different types of actor heterogeneity are used in the experimentation procedure. The conclusions include direct outcomes of the experiments, as well as experience of the authors during the process of constructing these three different models that bring about differing challenges.
The field of health and social care in the UK has been very receptive to systemic thinking in recent years and has been extensively and successfully modelled. This paper describes two trends in health care thinking in the UK which build upon this receptivity and are creating market pulls for whole systems ideas. These are the related areas of health needs analysis and service-line reporting, two concepts that are in search of a language and methodology to help deliver their potential. The paper describes how system dynamics is being applied to both these trends. The work is creating a natural progression for communicating system dynamics models and improving their impact on the thinking of clinicians and managers, particularly in mental health as epitomized by the
Within an organization, the employee population is the source of potential malevolent insiders. To investigate the evolution of the insider within an organization, we are developing a model of the employee life cycle. The employee life cycle model is designed to define and analyze interactions of the employee population with insider security protection strategies. The model was exercised for an example scenario that focused on human resources and personnel security activities, specifically, pre-hiring screening and security clearance processes. This modeling effort provides a framework to understand important interactions, interdependencies, and gaps in insider protection strategies. This work is part of a larger effort to develop the basis for an integrated systems-based process for designing and evaluating effective insider security systems.
Cholesterol metabolism and other factors affecting its dynamics comprise a complex system. The goal of this study is to construct a system dynamics simulation model that can generate long term dynamics of cholesterol metabolism in healthy and hypercholesterolemic subjects, with respect to body weight, diet, and exercise. For both healthy and hypercholesterolemic subjects, the model generates realistic behavior patterns for different types of blood cholesterol and body weight. It is shown in this study that a person can have healthier cholesterol levels by changing her diet and/or doing more exercise. Also itâs observed that exercise is more effective than diet even in cases when the subject does not lose weight. In the case of hypercholesterolemic patients, the model effectively mimics the way typical drugs work and shows how the patient can reach healthier cholesterol levels.
Policy recommendations in public policy venues take on several forms. In some cases, they are well-crafted arguments in favor of a particular course of action. Strong policy recommendations will frame issues in a way that lead decision-makers towards a preferred set of solutions. This paper presents a codebook for developing causal maps from policy recommendation reports and texts. The codebook's strengths and weaknesses are discussed, as applied to a set of recommendations made to reduce flood damages and increase the quality of floodplain management in the U.S. This paper shows how the internal validity of causal maps constructed from qualitative data will be improved by developing codebooks that are reliable, consistent, and transparent.
The present research on the growth of enterprise information technology applications is to build an effective system dynamics model which can reveal the internal laws of the general process experienced by an enterprise integrating the application of modern information technology and management. Based on the literature review and surveys on more than two hundred companies, we sum up the mechanism among the information technology application and key impact factors. In accordance with the conventional modeling methods of system dynamics, a model has been built and tested. The model is also supported by the empirical evidence.
Feedbacks, nonlinearities, and time delays are at the heart of dynamic interactions of socio-economic and biophysical systems. Land use land cover change (LUCC) is a significant component of these dynamic interactions. Land change science community recognized the need to go beyond static depictions of feedback processes. This requires explicit focus on the embedded feedbacks within and across scales as influential, endogenous structural sources of the observed behavior patterns in integrated social and biophysical systems. We present an operational framework that takes its strength from its clear emphasis on nonlinear feedback interactions as drivers of LUCC. The framework addresses both micro- and macro-level processes by employing complementary use of system modeling and spatially-explicit discrete-choice modeling. We demonstrate the potential of the approach on a rapidly urbanizing region, Pearl River Delta (PRD) in South China. To this end, we employ our systemic framework and identify the most influential feedbacks and linkages impacting the urban land conversion over the course of urban and economic growth as experienced in PRD. We also discuss the potential of systems approaches and use of complementary methods in advancing land change science both in theory and in practice. Our remarks, invariably, have implications for sustainability science as well.
The purpose of the paper is to demonstrate, how a dynamic aging chain model can support strategic decisions in personnel planning. More specifically, we use a system dynamics model to improve the recruitment and training process in a large German service provider in the wider field of logistics. The key findings are that the aging chain of service operators within the company is affected by a variety of delays, for instance for training, promotion, and ordering of personnel, and that the structure of the planning process generates cyclic phases of personnel surplus and shortage. The discussion is based on an in-depth case study, which was conducted in the service company in 2008. Implications are that planning processes have to be fine-tuned to account for delays in the aging chain; the simulation model provides a tool for gaining insights into the problem and for improving the actual human resource planning process.
The present study undertakes a partial system dynamics (SD) translation of the contemporary biological and psychological conceptualizations of panic disorder (PD). It makes explicit the dynamic processes implicit in the narrative presentations in the literature. It serves as a facilitator for the discussion about PD for it provides an easy-to-understand and illustrative language for commoners to understand, and researchers of different fields to critically examine, the biological, psychological, social and cognitive aspects of PD.
Governments around the world have developed e-government programs hoping to obtain important benefits. However, many e-government projects fail to deliver their promises. Some of such failures are the result of a lack of understanding about the relationships among technologies, information use, organizational factors, institutional arrangements, and socio-economic contexts involved in the selection, implementation, and use of information and communication technologies (ICT), producing mismatches and unintended consequences. The paper proposes the use of institutional theory and dynamic simulation, particularly System Dynamics, as an integrated and comprehensive approach to understand e-government phenomena. The paper draws on the case of the e-Mexico program, particularly in the strategy to create web-based content to the citizen in the areas of education, health, economy and government. Using the same technological infrastructure and under the leadership of the same Federal Ministry, four different networks of government and non-government organizations engaged in the creation of Internet portals to create relevant content in these areas. Differences in institutional arrangements and organizational factors resulted on different technology enactments.
Many green practices are widely understood and known to bring benefits beyond reduced energy use. Yet, organizations often fail to implement them. What explains these failures? Past theory suggests that adoption and implementation will be most likely to fail when practices are difficult to recognize given current competencies or organizational structures, require complex knowledge, or when the organization faces short term pressures that force it to abandon implementation early. Here, we present a case study of an organization that fails to adopt an important best practice despite the fact that the benefits and steps toward implementation are well understood and external short term pressures are minimal. We find that instead, short term pressures are created entirely internally by the structure of relations across organizational boundaries, causing individuals to misperceive the best practice as a cost that can be put off rather than an investment with positive future returns. Thus, even the simplest of innovations and improvements can be stymied by dynamics internal to an organization.
In the report many methodological and technological approaches for creating Decision Support Systems for regional and federal authorities are presented. They are based on using new information technologies such as Data Warehousing, On-Line Analytical Processing, simulation modeling and others. The general structure of model complex for region social-economic development and its realization based on methods of system dynamics and modern technologies of simulation modeling are described.
The Latinamerican Chapter has the mission to help the SD-community grow in the Spanish speaking countries. Founded in 2003, it has Latinamerican members from Mexico to Chile, from Spain and a growing number of Spanish speakers living in other countries. Since 2003, the annual meeting allows practitioners to gather and newcomers to get in to touch; we have been in Mexico, Chile, Colombia and Argentina so far. Since 2005, the Spanish "Revista de Dinámica de Sistemas" publishes two numbers per year. The "sisTEMAS" newsletter and a mail list allow keeping in touch. During October, the 6th Latinamerican Conference took place in Santiago de Chile, organized by University of Talca, Adolfo Ibañez University, Diego Portales University and Andrés Bello University. During the 2008 Annual Meeting we met many Spanish-speaking members living outside the Spanish-speaking countries and the wider group continues to grow. This year's meeting will take place in Santa Marta, Colombia in November 2009 ( http://simon.uis.edu.co/eventosds2009/home/). It is an opportunity to talk about sponsorships and future joint activities and also to welcome new members. If you would like to join us please contact Gloria Perez Salazar ( gloria.perez@itesm.mx), Isaac Dyner ( idyner@unalmed.edu.co) or Martin Schaffernicht ( martin@utalca.cl).
Net migration rate of -3.28 migrants/1000 population ranked Iran 145th in the world. Popular discourse about Iranian immigration focuses on the social and political freedoms associated with relocation. In the current research, the focus is on the authority of the educated people, their impacts on the society, their access to the power and the wealth which seems far negligible. The elites of Iran are no longer the educated people. Based on this assumption, a system dynamics approach is presented to study the long term effects of the emigration on Iranian society. Each emigrant develops themselves in the target country and attracts more emigrants. The success and satisfaction in the target country motivates the young generation to move than to change. The emigrants, when their number increases to millions, form a basement to attract more talented ones from the source country. Emigration of elites is more than a move of people; it has important negative effects on the country to produce wealth, to become industrialized, and to produce more talented
Inventory control is a fundamental activity in closed loop supply chains, particularly for remanufacturing processes. Several models have been developed in the literature where the aim is mostly to optimize cost or profit and to find the optimal order quantity for an integrated production and remanufacturing system. In this study, we explore a System Dynamics approach in order to model an inventory control system for a remanufacturing process in the context of a Closed Loop Supply Chain. Particularly, the return process is modelled through the influences relationships which several factors have on such process. The factors considered are residence time of the product with customer, service agreement with customers and customer behaviour in returning used products. The findings suggest that a reduction of residence time and an increase in the level of service agreement with customers, which in turn increases customer behaviour in returning used product, can lead to efficiency in inventory management for companies involved in remanufacturing process. In addition, we provide two simple case studies in support of these findings.
The aggregate profits of the airline industry have been dominated by a cyclical mode since before deregulation in the 1970s. In this paper we discuss several dynamics that combine to cause profit cycles: The misperception of the delay around capacity acquisition, the pro-cyclical ticket price setting policy and the countercyclical effect of industry congestion on passenger demand. By adding numerous endogenous feedbacks, extensions of previously used standard structures and wholly new structures we quantify the strength of these feedbacks, replicate the past behavior of the industry, and prescribe policies that can help to mitigate the cycle in airline industry earnings.
This study investigates the cause of a nearly twenty-five year decline in the percentage of U.S. born undergraduates earning engineering degrees. This dramatic decline has occurred despite incredibly high pay and low unemployment among engineers. On the surface this situation appears to violate the laws of supply and demand. A system dynamics model was created to represent the institutional forces and feedback loops present in the real-world system. This model internally represents the economic forces governing the choice to pursue science, technology, engineering, and mathematics (STEM) education, distinguishing features of quantitative knowledge that constrain its transmission, and factors determining the quality of STEM education in our schools. It is shown that high industry pay for STEM workers and low pay for STEM teachers can cause long-term self perpetuating labor shortages. The fact that mathematics performance has strong dependencies on past-knowledge exacerbates the situation. Policy proposals are simulated to test their ability to positively influence the system. The model is shown to exhibit tipping point behavior. Small reforms will have negligible impact while significant reforms could make the system move into a fundamentally better pattern of behavior, but only after considerable delays.
The stock and flow management (SFM) 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, the phenomena of excess stock and shortages are omnipresent. One recent explanation for these observations is offered by a stream of research, which finds evidence for widespread and persistent deficits in stock-flow thinking (SFT) capabilities even among well-educated adults. Building on this explanation, an attempt is made to test the hypothesis, that the better people understand accumulation, the higher will be their performance in SFM tasks. The results of a small sample pilot study indicate that the hypothesis of a one-dimensional cause-and-effect relationship between SFT and SFM performance has to be rejected. Therefore, Ackermanâs PPIK theory is introduced and used to formulate an elaborate causal model, which could be tested in future research.
This paper aims to support small medium enterprises (SMEs) in business planning through the use of system dynamics models. In particular, it has been hypothesized that through the use of a step-by-step system dynamics model building process SMEsâ entrepreneurs can better understand the net of cause-and-effect relationships underlying company financial and non-financial results. Such an approach also enables decision makers to improve their understanding about the figures portrayed in a balance sheet. In order to reach such a goal, this study has been carried out through the use of a case-study. The small company investigated is a leather handcraft operating in Indonesia. The paper makes explicit main feedback mechanisms underlying company customer base dynamics adoption process, production and inventory management policies, human resource management practice and machineries production capacity acquisition policy.
This paper attempts to explore the relevance of the systems thinking approach with the doctrine of dependent co-arising which is one of the central doctrines in the teaching of Buddha. The doctrine explains how one gets trapped into the vicious cycles of suffering and how one can come out of it. The main elements of the systems thinking such as complexity, cause and effect feedback loops, non-linearity, time-scale, endogenous perspective and experiential learning are inherent in the doctrine. One of the effective leverage points explained is the bodily sensation which can be used to transform the vicious cycles of suffering into the virtuous ones. The doctrine also gives clue how the mental model gets formed, and how it can be trained so that one can make spiritually informed and better decisions.
In this paper by means of a simple system dynamics model, we analyze the dynamics of housing affordability in the context of real estate market of Iran. To do this we define an affordability index according to Iran's economic situation and show that in the absence of effective financial infrastructures, this index declines over time. To confront this problem, we analyze supply-side and demand-side housing policies. Moving into industrial methods of construction and increasing the volume of the construction loans are among supply-side housing policies. Also focusing on macroeconomic policies to reduce economic fluctuations and risk of investments in other markets is among demand-side housing policies.
Guided by economic models suggesting that growth can be stepped-up by increasing resources for investment, developing country governments have often resorted to borrowing to supplement revenue hence the accumulation of public debt. The purpose of this paper is twofold. First, it is to develop a dynamic model that identifies the fundamental structure of the public debt accumulation process. Second, it is to identify the mechanisms that generate public debt and their relative contribution to public debt accumulation
This paper examines the ability of companies to change their organizational forms in an effort to obtain higher performance. We use the concept of fitness landscapes and we expand the notion of attributes to include not only the capabilities, but also the purpose organizations attempt to serve usually the market. We decouple the fitness a form represents from the actual fitness an organization that incorporates it will experience due to the effect of competition for a common objective, creating a dynamic landscape. The extended model incorporates the notion of feedback from the environment in a twofold manner: the structure of the underlying landscape and the interaction among rival organizations. On one hand, the feedback helps organizations into making decisions based on increased information and on the other hand, the outcome of those decisions is no longer entirely predictable. We examine two different rules of transformation, namely the local adaptation, and the distant adaptation. The results indicate that the proposed scheme can more accurately explain the variation observed in real environments than previous models. In addition, it can serve as a means of predicting the possible reforms of rival organizations on a common landscape.
The political dynamics associated with an election are typically a function of the interplay between political leaders and voters, as well as endogenous and exogenous factors that impact the perceptions and goals of the electorate. This paper describes an effort by Sandia National Laboratories to model the attitudes and behaviors of various political groups along with that populations primary influencers, such as government leaders. To accomplish this, Sandia National Laboratories is creating a hybrid system dynamics-cognitive model to simulate systems- and individual-level political dynamics in a hypothetical society. The model is based on well-established psychological theory, applied to both individuals and groups within the modeled society. Confidence management processes are being incorporated into the model design process to increase the utility of the tool and assess its performance. This project will enhance understanding of how political dynamics are determined in democratic society.
Adaptive Campaigning describes the Australian Land Force response to the challenges of future warfare. It discusses the need for Army to perform successfully over various lines of operation and to maintain an adaptive approach in order to achieve its objectives in an ever changing complex environment. However, the novel nature of this approach poses some conceptual and practical implementation difficulties. A visualisation technique known as Influence Diagrams is employed to develop an Adaptive Campaigning Influence Diagram to abate some of these difficulties. The benefits of employing the diagram are illustrated by recent real world experiences of US Forces in Baghdad.
This paper suggests a classification of the social roles simulation models can play. Two dimensions are distinguished according to the context and use of models: models can be boundary objects or representative objects and they can be epistemic or technical objects. These two dimensions allow a classification of four types of model roles. Models can be ascribed different roles over time and different roles by different stakeholders involved in their development and use potentially leading to misunderstanding and conflicts. The suggested classification framework can be applied to a variety of problems around the use models including the discussion of the differences between System Dynamics models and Discrete Event Simulation models and the comparative analysis of model use.
Under what conditions does employee ownership improve firm performance? Employee ownership structure is part of a larger corporate system. To answer this question, one needs to unpack the underlying causal mechanism of how ownership structure affects the corporate system and how the corporate system and market conditions in turn influence the design of ownership structure. We developed a model of a startup company with various compensation and ownership structures, how they influence employee behaviors that drive business processes, and how those business processes interact with market conditions which generate firm performance in a dynamic feedback system. We conducted simulation analysis to study how various combination of salary, stock options, stock grants and profit sharing schemes influence firm performance overtime. We hope to contribute to the field of Strategic Human Resource Management by providing a model of the causal mechanisms between HR practices and firm performance.
While qualitative-based system archetypes have helped popularize the application of systems thinking since the publication of "The Fifth Discipline", some argue using the archetype alone, without the knowledge derived from working directly with formal models, can be dangerous. This paper presents a formal simulation model of Shift the Burden, one of the most popular system archetypes. I seek to create a model as parsimonious and generic as possible while grounding the formulations based on behavioral decision processes. A set of leverage points are identified that prevents the system from tipping into a vicious circle where more symptomatic solution leads to erosion of fundamental solution that augments problem symptom.
This paper describes formative field research to develop and test the utility of a system dynamics modeling intervention intended to promote evidence-based tobacco treatment practices in community-based primary care settings. Brief counseling interventions by primary care providers have been shown to effectively promote tobacco cessation among patients who smoke, yet many physicians are inconsistent in the way they intervene with their patients. Too little time, poor training, lack of third-party reimbursement, competing clinical problems, and the belief that their patients are not able to change explain, in part, why some physicians do not adhere to evidence-based guidelines for treating tobacco use and dependence. Via a protocol for conducting on-site office visits to small primary care practices located in medically underserved urban communities, we tested the hypothesis that providers exposed to the simulation tool would demonstrate better understanding and progress towards full implementation of the US Public Health Service Guideline for Treating Tobacco Use and Dependence. Results indicate that simulated output that reflects the dynamics of providers unique practice environment is associated with stronger behavioral intent than other forms of feedback information, such as patient chart reviews.
In recent years, due to fast development of information technology and fierce competition, information technology investment strategies are significant factors to sustain business operation. Furthermore, rival investment strategies and allocation of complementary assets should be taken into account so as to achieve maximum efficacy of the strategies. This study adopts the intellectual capital structure and complementary asset theory, and investigates Taiwans information-intensive services. A research model is presented to discuss the impacts of information technology investment strategies on organizational performance based on intellectual capital framework. This study introduces a system dynamics method to analyze a case of two rival companies, and interprets the effects of different IT investment strategies on operation performance through simulation and scenario analysis. The simulation results can help companies making information technology strategies and evaluating their overall performance. The results indicate that different information technology investment strategies and matching degree of complementary resources have different impacts on the organizational performance. Moreover, this can help companies to make IT investment strategies. The studied results can provide important theory and practice implications for organizational IT management.
In recent years, new business models are becoming increasingly more important for manufacturers in the capital goods industry. However, manufacturers of plants still hesitate to offer these customer-oriented solutions, due to existing uncertainties resulting from economic risks. The offer of innovative business models requires a stronger integration of the supplier into the life cycle of a plant and hence into the production phase of the customer, leading to the consequence that manufacturers have to restructure their previous activities extensively. Due to the financial risk connected herewith, decision models are required, which identify and assess the impacts resulting from the implementation of these innovative business models. Aspects like time delay, due to the reorganisation of the service department or the set up of adequat human resources have to be considered. Therefore, the aim of this contribution is to develop a system dynamics model for the analysis of long-ranging consequences due to the implementation of an exemplary business model.
Bounded by limited cognitive capabilities, decision-makers use mental models (reduced versions of real world dynamics) for decision-making and interventions in complex tasks. As such mental models are constantly updated with new experience and knowledge acquired, facilitating a learning process. Through this learning process, mental models can be refined to better represent real world dynamics. Systems theory suggests that updates of mental models happen in continuous cycles involving conceptualisation, experimentation, and reflection (C-E-R), which represents a dynamic decision-making process (DDM).
Stocks and flows are basis of dynamics. Understanding of stock and flow is crucial in comprehending and managing problems such as global warming and national debt. Yet previous experimental studies have found that people perform poorly in simple stock-flow tasks. However, many do have a notion of accumulation in terms of calculating running total, adding or subtracting items to keep track of a running tally. Here a pre-test-treatment-post-test experiment was designed to test the hypothesis that peoples understanding of stock and flow behaviours will improve after being asked to reflect on a cognitive conflict, generated by utilizing their running total calculation. Comparisons with a conventional approach to teach stock and flow dynamics and without teaching were also done. Results show that improvements were not significant; the hypothesis lacks support. On the other hand, the conventional approach produced significant improvement. Possible explanations of the results and their implications for education on dynamics, communication of complex dynamic problems and policy insights are discussed.
The main goals of this paper are to explain and illustrate Exploratory System Dynamics and Exploratory System Dynamics Modelling and Analysis, which are both useful for exploration of, and decision-making in, dynamically complex issues that are deeply uncertain. First, the need for exploratory approaches is discussed. Second, different exploratory approaches are briefly introduced. Third, a typology of safety and security issues/crises in terms of degrees of complexity, uncertainty and urgency is proposed. Different types of inter/national safety and security issues for which exploratory analyses may be useful are listed too. And the application of these exploratory approaches is subsequently illustrated on some of these issues, more precisely on (i) an acute financial crisis (the concerted bank run on the DSB Bank), (ii) an imminent pandemic flu crisis, and (iii) plausible mineral/metal scarcity crises. The paper ends with some conclusions, lessons learned, and a discussion of future work.
