The Dana Meadows Award was established in 2001 to honor the late Dana Meadows and encourage the next generation of students in the field of system dynamics. The award is given annually for the best paper by a student presented at the annual System Dynamics Conference. The winner receives a cash award, a conference registration and an allowance for travel
expenses. The Society awarded its 2012 Dana Meadows Award to David Keith at the Massachusetts Institute of Technology, and András K?vári at Delft University of Technology. David Keith received the award for the paper "Understanding Spatiotemporal Patterns of Hybrid-Electric Vehicle Adoption in the United States." András K?vári received the
award for the paper "Prostitution and Human Trafficking: A model-based exploration and policy analysis." The award was presented by R. Joel Rahn.
To help modelers increase the transparency of their models through enhanced documentation, scientists at Argonne National Laboratory (ANL), building on model documentation work by Oliva (2001), developed the System Dynamics Model Documentation and Assessment Tool (SDM-Doc) that enables modelers to create practical, efficient, HTML-based model documentation and provide customizable model assessments. The model documentation created by the SDM-Doc tool allows modelers to navigate through model equations and model views in an efficient and practical way creating documentation of the model sorted by variable name, type of variable, group, view, module, module/group/name, and variable of interest. Additionally, model tests are performed allowing modelers and reviewers of models to gain confidence in fundamental characteristics of model structure. The tool, its use, and the different model assessments included in it will be presented and explained. Participants are encouraged to bring their laptops to be able to use the tool during the workshop. A copy of the software will be distributed to participants at the workshop (the tool is accessible at http://tools.systemdynamics.org/sdm-doc/).
The purpose of this study is to build an experimental platform for scenario and policy analyses of social security institutions that deploy pay-as-you-go schemes as the financing method. To realize this aim, system dynamics methodology is utilized and a generic dynamic simulation model is constructed. Afterwards, the financial sustainability of the social security institution in Turkey, as a susceptible country for its aging population, is investigated via scenario and policy analyses. The results show that (i) irrespective of scenarios and policies, aging phenomenon is quite dominant and a serious threat to financial sustainability, (ii) informal sector plays a crucial role in the financial sustainability of social security systems, and (iii) a hybrid policy combining increase in retirement age, premiums and decrease in informal sector ratio seems to be the most promising one among the other policies. Future research involves modeling the fully funded scheme complementing this study to enable the public policy makers to compare and contrast the two financing methods comprehensively.
This paper presents a soft landing model and an experimental platform. The aim of the modeling effort is to transparently represent the process of landing a spacecraft on the surface of a celestial body. The process of landing is a challenging task because there are two main contradictory performance criteria to be met simultaneously; the landing duration should be as short as possible, but at the same time crashing the spacecraft to the surface should be avoided. If the only criterion was to prevent crashing the spacecraft, that would not be difficult to achieve by slowing down the landing process. However, long landing duration necessitates extensive use of fuel, which should also be avoided. As a summary, the main goal in the soft landing problem is to land the spacecraft as gently and as fast as possible. The model and the modeling process presented in this paper will serve as a modeling case to be used in teaching. Based on the soft landing model presented in this paper, we also developed a platform for simulation experiments. Our simulation-based discovery learning environment can be used to introduce dynamic complexity. It can also be used as an introductory control design tool for physics, engineering, and interested social sciences students.
The purpose of this study is to introduce system dynamics as a methodology to analyze intra-organizational innovation diffusion processes. Therefore, a purely algebraic model is replicated and analyzed in a system dynamics environment before it is extended by relaxing the restrictive assumption that intra-group diffusion and inter-group diffusion take place consecutively. The findings of this study suggest that the parallel occurrence of intra-group and inter-group diffusion can change the outcome of the diffusion process significantly. In addition, system dynamics is used to illustrate and analyze the complex dynamics of the diffusion process. The interplay between the self-reinforcing dynamics of intra-group diffusion and the balancing dynamics of inter-group diffusion is heavily influenced by the structure of the network between groups. The simulations suggest that adopter-dominated groups should be connected to each other, while non-adopter-dominated groups should be isolated in order to increase the probability and speed of successful innovation diffusions. Major limitations of the study are that only one network structure between groups was examined and that all groups are considered to be homogeneous.
Increasing concern regarding the cost, security, and environmental impact of fossil fuel energy use is driving research and investment towards developing the most strategic methods of converting biomass resources into energy. Analyses to date have examined theoretical limitations of biomass-to-energy through resource availability assessments, but have not thoroughly challenged competing tradeoffs of biomass conversion into liquid fuel versus electricity. Existing studies have focused on energy crops and cellulosic residues for biomass-to-energy inputs, however the conversion of these biomass resources is often less energetically efficient compared to fossil energy sources. Waste streams are beginning to be recognized as valuable biomass to energy resources. Municipal solid waste (MSW) is a low-cost waste biomass resource with a well-defined supply infrastructure and does not compete for land area or food supply, making it a potentially attractive renewable feedstock for energy conversion. The Waste Biomass to Energy Pathway model (WBEM) described here demonstrates a system dynamics approach to analyze the impact of converting MSW biomass to either bioelectricity or liquid fuel. The WBEM incorporates macro-scale feedback from supply chain costs, energy sector impacts, and greenhouse gas (GHG) production within the competing pathways of MSW to 1) landfill, 2) electricity, and 3) liquid fuel within California.
This study empirically demonstrates that software firms in a niche market with relatively short-life cycle may experience a similar growth pattern that firm grows after a period of performance deficit. A system dynamics model is built to capture the essential interactions across industry- and firm-levels. It is found that the growth trajectory of worse-before-better offers an explanation of the high exit rate in software industry in which small and medium enterprises are the majority. Furthermore, it is also found that though activities of market development and service and activities of product development and enhancement were important in pursuing survival and growth, software firms with different attitudes towards growth emphasized differently on the these activities by different human resource management and allocation policies. In this paper, we argue, and show, that entrepreneurs attitude towards growth and his or her adopted growth strategies determine how worse to experience and the extent to grow. This is significant to system dynamists because it shift our attention from traditional growth dynamics exploration to the observation and explanation of why firms experience growth or failure differently. The difference of growth among software firms and its implications is deliberately discussed.
Customer lifetime value (CLV) is the core content of customer relationship management. With the increasingly fierce market competition, more and more enterprises realize the importance of maintaining long-term strategic partnership with customers. In this paper, we established a system dynamics model of CLV and use SF Company as an example. The model simulation results showed that the intensity of competition, price levels and investment levels all affect CLV. Reducing the intensity of competition can increase the CLV. More investment will raise service quality and then promote CLV. Reducing the price level increases CLV in the short term. However, in the long run, less income leads to less profit and less investment which can decrease CLV.
Several experiments have shown that, when predicting the behaviour of stocks and flows, many subjects rely on the erroneous correlation heuristic. They seem to assume that the output of a system should look the same as the input. Based on similar experiments with kinematics graphs we hypothesize that spatial ability explains variance on tasks involving accumulation. We propose that spatial ability might also generate other important differences between people, such as their ability to infer behaviour from diagrams. We tested participants on two dimensions of spatial ability: visualization and spatial orientation. In an experiment we found that the visualization dimension has a positive effect on performance in various systems thinking inventory tasks and a negative effect on the likelihood that the participant selects a response typical for correlation heuristic reasoning. The positive relation to performance was also present for tasks in which stock behaviour had to be inferred from text and diagrams. Furthermore, we found that people are not persistent in their use of the correlation heuristic between different types of tasks. Males and females did not differ in their spatial ability, but, males did perform better on almost all stock and flow tasks.
This paper introduces the industrial transformation model applied to the carmaker industry. We analyze the interaction between supply and demand as well as policy regulations supporting the diffusion of advanced vehicle technologies. It allows to assess prospectively threats and opportunities of induced technology changes for industries. The simulation exercise provides evidence that smart governance approaches involving concerted entrepreneurial and political decision making can avert severe industrial crisis of adjustment during phases of socio-technical transitions. The overall cycle pattern seems to play out over a time period of 50 years. It is strongly influenced by the climate policy regime and the innovation investment behavior of firms. It results in a sectoral boom phase once the transition towards near zero emission vehicles has been mastered. The policy induced technology change pattern is comparable to the long wave theory in terms of its duration and the argument, that deep structural causes are innovation processes in whole technological systems. Moreover, we have identified the drivers of single short term cash cycles. Differences between cash inflow and outflow over time that are triggered by strategy and policy changes explain short term fluctuations.
Over the past few decades, many studies of corruption have been carried out. These studies have mainly focussed on specific characteristics such as: economic issues, legal issues, social propositions, impact on national development, and in relation to economic policy. The rationale of this research is to build initial system dynamics models of corruption, so that these models can extend our understanding of corruption and act as an input to future policy making on corruption. System dynamics modelling allows researchers to discover hidden dynamics. Moreover, system dynamics enables the analyst an increased level of flexibility, as system dynamics modelling uses both theoretical understanding, as well as empirical data collection. Indeed, as a result of this study, we can offer an explanation that uncovers the underlying factors that address the dynamics of corruption, social, economic, political, judicial and cultural factors in case of any developing country, which can be applied with some modifications for developed world. In this we try to determine problem of corruption in societies by incorporating very complex and different social, cultural and even religious aspects that were mostly untouched in system dynamics studies in past. Systems dynamics model of corruption developed in this study would be of use to policy makers and non-governmental organisations in understanding the complex nature of corruption.
Accounting Dynamics (AD) is a methodology of accounting as social science. We studied Accounting Dynamics from 1982 to 1994. We first proposed the concept of Accounting Dynamics on International System Dynamics Conference in 1987 . We interrupted the study for a long time, because there were some difficulties to develop the real Accounting Dynamics models. The concept is still reasonable and so attractive that we have reviewed Accounting Dynamics again. This is first step to restart the project and show you Accounting Dynamics in order to organize the SIG. This paper shows what is "Accounting Dynamics" clearly.
There are many studies exploring the reasons behind failures in solving generic system dynamics (SD) problems such as stock- flow (SF) failure. Although they reach some limited associations, they do not find any significant cognition related factor explaining the variation in failures except the positive impact of visual saliency of the problem displays. In present study we put forward the question Does cognitive problem solving capability improve progressively? So, we prepare a performance sheet including two parts. First part consists of simpler SF problems and second part contains more complex ones. Then we ask these questions to motivated undergraduate industrial engineering students. Sample of participants consists of two groups. First group is SD educated and second group is not SD educated. We see that while some individuals are performing well in solving more complex SD problems, others are performing well in simpler ones, and ability to solve more complex problems is not dependent on performance in solving simpler ones. But we find associations between capabilities of solving two different more complex SF problems each other. We also see that SD education increases the capability of solving more complex SF problems but does not affect the capability of solving simpler SF problems.
Inter-firm trust is an essential element in supplier relationship that shapes the collaboration and coordination between suppliers and buyers. In this paper, we use system dynamics as an approach and perspective to analyze the evolutionary process of supply chain collaboration. Use a valve manufacturing firm as an illustrative case, this paper illustrates how a buyer firm in a networked supply chain unexpectedly harmed the inter-firm trust between the buyer and its suppliers that further resulted in the collapse of the relationships among them. Based on the quantitative system dynamics model developed, this paper argues and shows that supply chain relationships may be more complex than the consideration of transaction costs. Path dependency of the make or buy decision may exist and drive a supply chain to evolve over time. Buyers and suppliers rational decisions to reduce their own risks and to optimize efficiency may not only interfere with the benefits of the other side but also entrap a long existed supply chain to collapse. From the economic perspective, how to balance the time required for capacity expansion and the time for suppliers to develop new customers is of the essence in such a vulnerable supply chain setting.
Presented here are strategic planning tools used at a State University, College of Business. Four distinct tools are presented: The Strategic Initiative Scoring Model, which communicates how the college strategic planning execution projects fit the strategic priorities of the Universitys mission statement & strategic plan; the college Strategic Risk Planning Matrix, which describes both risk assessments and risk management plans; the college Strategic Planning (SD) Model, which is used by administrators to assess impacts from proposed or mandated changes in budgets, admissions, Student-Faculty Ratio targets, and faculty hiring/attrition; and the Strategic Performance Indicator matrix, used to monitor performance and drive the creation of new projects to be assessed in the Strategic Initiative Scoring Model.
Human resource requirements planning for nursing capacity has traditionally focused on expected utilization or demand and largely ignored the complex workplace policies. The approach taken in this research emphasizes the interaction of policies affecting compensation, work intensity, task satisfaction and career progression on hiring and retention the flows that determine the stock of nurses. Based on research conducted with Singapore Ministry of Health, we describe how policy changes influence employment levels at care venues over a strategic time horizon. To answer three research questions posed by experienced planners and managers, we employ a System Dynamics model to test and explain the implications of alternative policy choices.
A water cycle analysis System Dynamics model for designing an optimal reclaimed water production scheduling is proposed. A water cycle has various types of water flow and storage, so System Dynamics is suitable for modeling and simulating it. In addition, by using System Dynamics modeling software, various types of models for water cycle analysis can be modeled comparatively easily and used to design an optimal scheduling. The model must be able to analyze water quality and energies for water distribution and treatment as well as water flow and storage in order to schedule optimal production. It therefore consists of three components: water flow, water quality, and energy models. We constructed a water flow model that can handle various types of water flow. The Energy model computes the energy consumption of the pumps and blowers used in water distribution and water treatment systems, and the water quality model computes the water quality of treated wastewater and reclaimed water. Our constructed model was used to schedule water reclamation production to reduce the energy consumed during the water reclamation process and to ensure high quality of the reclaimed water. Simulation results showed that the proposed model is effective for designing an optimal scheduling.
Methods of systems analysis were applied to the illness multiple sclerosis (MS). By mapping causality among the many causes affecting multiple sclerosis, we have been able to show that it is a systemic illness, with multiple interacting causes and mechanisms. By using causal-loop diagrams we synthesized a systemic picture of MS in which the role of allergies, pathogens, molecular mimicry, venous vascular dynamics, membrane stability, immune system, and oxidants-antioxidant dynamics were integrated. There are important components that make up MS:
The TETRA-model has been built to predict the modern occurrence of ancient Athenian tetradrachm silver coins in quantitative terms, based on their original minting volumes an antiquity and the processes of their loss and destruction, as well as the process of finding them in modern times. The conceptual model was developed as causal loop diagrams and flow charts, based on Athenian siver mining dynamics, the minting process, the circulation in trade and finance in ancient Athens, rates of wear and loss of coinage, corrosion of coins in the buried state, modern retrieval rates and dynamic turnover in the numismatic market, as well as deposits into collections and museums. A systems dynamics model was programmed in the STELLA modeling environment and implemented for 500 years of Athenian coin production (526 BC to 42 AD) and preservation and retrieval until the present (526 BC to 2010 AD). The TETRA model was tested against independent estimates of past and present coin volumes, treasure finds, museum stocks. The model seems to work well in tests against independent estimates. The approximate number of coins surviving until today for the different types such as archaic owls, classical owls, transitional owls, heterogeneous owls and new style owls were predicted well within the estimates derived through other means and museum inventories (r2=0.82).
By using an integrated dynamic model we are able to reconstruct the supply and gold price of the past (1920-2010) and this is used to predict the future supply of gold to the market and to make a forecast of the gold price 2010-2100. The model was validated against field data for the period 1920-2010 and it performs well. The simulation results show that the market is fundamentally driven by supply and demand, but that derivates trade and speculations have affected the market significantly to create large short term variations in price. In the long term, the model predicts a shift from high-grade ores to low-grade deposits as the main supply source in the next 50 years, but that recycling will become the most important source of gold to the market. The authors predict a significant tightening of the gold market, with rising prices and a decreased derivates trade as compared to trade in the physical commodity. The model shows clearly that foreward and derivates trade create less stability and increase price fluctuations, but that they cannot prevent the long term trend from basic fundamental factors to set the long term levels.
Adaptation of SD mainly focuses on management and environment aspects, and successes to get enormous reputations from results. However, adaptation of SD is not limited on these areas, but disseminating to psychology and military science recently. Author believes such adaptation should be wider to other fields too. Continuous of such adaptation, this paper tries to build SD model for study literature with quantitative explanation and understanding. William Shakespeares Tragedy of Romeo and Juliet is one of best works in his early age. Similar story also looked in other literatures in other countries including works of Chikamatsu Monzaemon in Japan and opera Tristan and Isère. Added more, Romeo and Juliet was adapted to other forms of arts and literatures including Broadway musical West Side Story.
The main aim of this paper is to study the impact on birth rate of specific public policies: subsidies to chilbearing and public consumption. The analysis is framed in an developed economy in which fertility choices and economic decisions are interconnected. In particular, the study relies on overlapping generations, habit formation in consumption and endogenous fertility rate. This last factor is directly explained by the preference for children, the economic capacity of young people and the stylized fact of unemployment. The outcome is a versatile system dynamics model that is adapted for the Portuguese economy from 2000 to 2011. Two counterfactual exercises differentiated from the employment distribution but with identical alternatives of public spending are implemented in the simulation model. The results show two divergent aspects: the births do not vary if the public consumption increases but, the births increase when the costs of childrearing are subsidized even if the public consumption is high. These results also indicate that the subsidies are not sufficient to curb the decreasing trend of births. In addition to them, it is required a sustainable economic growth.
In the last decades in several mature democracies the problem of debt emerged as a violation of intergenerational equal treatment due to high expenditures concentration and dilution of costs by mean of debt creation. So far this issue has been analyzed from a statistical and a socio-economic perspective, which identified the high political interference as the main dysfunction of country debt management. There are no studies which frame the issue by focusing on State institutions as performance-oriented organizations, according to this perspective such organizations have to respect dynamically trade-off between development and the debt reduction through a mix of levers such as: funds acquisition/reduction, interest rate and financial leverage. System dynamics can be successfully used as an instrument to support Government in keeping control over the key variables affecting debt changes and implementing a sustainable policy. In the paper three kinds of policies are recommended: the reduction of expenses and increase of receipts in the short term to drastically reduce the debt amount; the opportunity to exploit the financial leverage in the long term. Such approach implies a change of perspective, looking at Italy as a performance-oriented organization in which a proper financial management serves economic development and not vice versa.
World Class Manufacturing (WCM) has attracted the attention of many manufacturing industries and operation strategists. Lack of clarification of relationships among widely spreading elements of manufacturing process and poor attention to non-linearity and time delays, all are the main reasons that some companies may be far away from developing a comprehensive and advantageous model in a WCM system. The purpose of this paper is designing and analysis a dynamic Model of WCM system to develop a proper strategy which changing the current situation into a WCM situation would be possible in the future By the Dynamic Balanced scorecard (DBSC) methodology as well as clarifying deficiencies of classical balanced scorecard, a systematic model of WCM has been presented through causal loop and stock & flow diagrams. This research has been carried out as a case study in the Iran Khodro Co.(IKCO), We've used Vensim software for designing and analyzing our model after entering related data, parameters, and equations. Some strategies have been presented through analyzing the scenario and running the simulation model.
The formation of the EU is the one of the biggest politicaleconomic events of the last 50 years. EU development process is still incomplete, with still evolving EU economic foundations and financial system. The aim of study is to develop EU economy functioning SD model, taking into account main economic indicator changes of EU countries since EU enlargement. Study result author divides countries into several groups, based on their economic specifics. For these groups in the paper the first attempt to develop EU economy system dynamic model is undertaken. General scheme of EU economy SD model is shown, new EU member economic integration model is developed. Model is tested only for one EU country, Latvia. Results of paper show failure of mechanism of EU operations. The available mechanism contradicts EU principles; it doesn't promote the cohesion in EU, but quite opposite- leads to solving problems of well-developed EU countries at the expense of developing countries. In the given conditions the example of Latvia shows that there is no possibility to overcome the system crisis. These circumstances specify necessity of changes in EU internal migratory policy, in principles of developing countries support, in distribution of means, taking into account internal migration.
GEPSUS, decision support system for handling hazardous air pollutant releases was developed based on a Gaussian simulation model of air pollution dispersion using MATLAB. For the Gaussian model the following assumptions apply: a) the smokestack emission is constant and continuous, b) flat homogeneous terrain, and c) the wind speed is constant. It is assumed that in the main wind direction, x, advection dominates over diffusion and dispersion. A detailed outline of the system integration is provided, which includes aspects of hydro-meteorological data, eco-toxicological data, Geographical Information Systems (GIS), user input, and system output including a description of threat zones and evacuation plans using a geo-browser. The Gaussian air-pollution dispersion simulation model is linked to the GIS by generating the output in KML file format. Several simulation scenarios were considered using meteorological data sets of wind speed, wind direction and ambient temperature. The developed simulation model and decision support system is intended to facilitate rapid emergency response for both deliberate and accidental air pollution releases. System dynamics model is developed to address the crisis mitigation issues.
In this paper we model the impacts of competition between cities when considering demand management strategies on both the optimal tolls and business and residential location choices. The work builds on earlier work which studied competition in a small network using a static equilibrium approach. That work showed that while both cities have an incentive to charge alone, once they begin, they are likely to fall into a Nash trap or prisoners dilemma where both cities are worse off. Our research extends this by setting up a system dynamics model which includes all modes and longer term location responses. The model is used first to study an isolated city and a simplified welfare function is used to determine the optimal toll around the central area and its impacts on location decisions and other transport indicators. A twin city is then added. Traffic from the neighbouring city may be charged and the revenue retained - a form of tax exporting behaviour which should increase the welfare of the city. We study the impact on the optimal tolls set by the cities and how the game develops between cities of equal size and amenity. The impact on location decisions and other transport indicators are presented along-side the implications for regulation and the development of cities within regional partnerships.
This paper presents a dynamic simulation model for the study of the residential heat market in Germany with regard to the European energy targets for the year 2020. It describes the model properties and specifies the dynamic structures of the demand side based on housing units and of the supply side which is formed by heating systems. An initial model validation indicates the appropriateness of the model assumptions. Five policy scenarios are introduced which take into account different measures for the promotion of renewable and innovative heat generation technologies and obligations for energy-efficient renovation of buildings. The discussion of the scenarios shows that with the given set of policies, the EU targets for heat demand reduction and CO2 emission mitigation in the residential sector would not be met, while the envisaged share of renewable and innovative technologies seems to be achievable.
Successful corporate action requires a comprehensive recognition of the relevant cause-effect relationships. In combination with the mental models of decision-makers, and as a complement to static instruments for business management, system dynamics simulation models provide valuable support. However, due to the usually experienced big effort and the demand of specific modelling knowledge the use of such models is not yet widespread within management. In order to give medium-sized companies in particular access to such simulation models, a practice-oriented concept was developed, enabling the design and implementation of system dynamics models as to support decision-making within strategic management. Within the framework of an empirical case-study, simulation models were developed for and implemented in four production companies. In order to make the modelling process as simple, efficient, effective and relevant as possible, a practical procedure was derived out of the case studies. This procedure describes the entire modelling process encompassing the initial process of structuring the mental models, the development of quantitative simulation models, as well as the analysis of various scenarios. The concept is based on generic model components, assembled to form a fundamental model structure (backbone) in order to facilitate and to accelerate the modelling process.
One of the excellence enablers is KM . In order to evaluate the KM processes, a comprehensive model is required, which should be able to capture all aspects of KM. One of such models is KMAT . This research exploits system dynamics in order to measure the effects of KM on business excellence with a combination of KMAT and EFQM .Relationships between KM and EFQM are analyzed and demonstrated by means of the literature reviews, expert interviews and system dynamics .The results of this study could be useful for knowledge management planners and managers in organizations.
The Brazilian program for sugarcane ethanol has been greatly successful since its inception about 40 years ago. But the road has been bumpy and today there are still major problems with price, supply and demand stability. This paper describes a research with the objective to propose policies by the government to stabilise and foster the Ethanol market in Brazil. The policies are tested by simulation. For that purpose a system dynamics model was built and calibrated to mimic the industry. Once the model is considered robust, it is used to test several proposed policies under different macroeconomic scenario forecasts. Historical evidence and the simulations suggest that the dynamics in the system are highly important in defining prices and other important variables. As one example, periods of high growth tend to negatively influence productivity after five to six years via a decreased investment in crops renovation which may create long term cycles. The effects of long term dynamics are mixed with several short and long term cycles typical of commodities markets and the combination increases complexity exponentially. Simulation can be a crucial tool for understanding causality and planning sound policies for the medium to long terms.
This paper is about the shortage of water resources in the central part of Iran -Isfahan while the region faces rapidly growth of the population. The study utilizes the system dynamics approach. The model consists of the following three main parts: water consumption, water resources and population. We will account for the current policies and the current population growth rate in hope of preventing a catastrophic failure in less than two decades from now. So, emigration, birth control policies and major changes in the consumption style are evaluated.
The Veterans Administration faces growing dissatisfaction with the delivery of one of its key services, Compensation and Pension (C&P). This paper focuses on the system surrounding the administration of C&P exams, which determine the extent of a veterans service-related disability. Many VHA facilities nation-wide are experiencing increasing service delays, along with reductions in exam quality and patient satisfaction. A system dynamics model was developed to determine the relationships between operational policies, management decisions, and process outcomes, and calibrated with data from one New England-area VA hospital. Simulation of system performance under various demand scenarios reveal the extent of the implicit the trade-off between resource flexibility, clinic utilization rates and patient wait-times. These scenarios are used to develop strategic policies to improve resource allocation and increase timeliness under highly variable demand conditions. Furthermore, alternate staffing models were tested against historic demand patterns, providing quantitative evidence for system redesign.
Shareholder Value (SHV) and value-based management (VBM) are blamed for causing short-termism of investors and managerial myopia. Empirical evidence states decreased holding periods of stocks by investors, increased discount rates and widespread adoption of earnings management. While this supports the existence of short-termism and myopia, it does not clarify its causes. What is missing is: do shareholder value and value-based management cause short-termism in the behavior of investors and managers? The paper uses System Dynamics to model both concepts and to try to explain short-termism and myopia as endogenous outcome of these concepts. The main result is, that, given uncertainty of outcomes of managerial action managers will have incentives to engage in short-termism. Since SHV raises target hurdles which increases pressure on managers, short-termism is a direct consequence of SHV itself. The contribution to the debate on short-termism is to better understand the role of SHV and VBM in explaining short-termism and to direct future empirical research as well as advancing modeling of SHV and VBM.
The sophistication of schools texts has been declining for more than 100 years in the U.S. Coincidentally, student capabilities and measured verbal achievement have been declining, certainly since the 1950s and probably since 1900. This investigation built a tiny model representing the famous sliding goals archetype tracing back to Forrester's Market Growth paper, and fit the model beautifully to the data. The fit is very dramatic and persuades everyone who sees it that the sophistication of texts and student SAT verbal scores are linked in a sadly sliding long-term pattern. But the fit, derived by robust and correct procedures, is fundamentally flawed, and the lovely fit to data is grossly misleading. This presentation will reveal the entire sad story, with implications for wise practice in the field.
Tourism is an important industry in many developing countries. In the past few decades, the issue of how to minimize the negative effects of tourism on natural and cultural environments and maximize its positive effects on economic development has been a major topic for tourism researchers and practitioners. Successful tourism-related policies not only can deliver economic benefits to communities, regions, and countries, but also can facilitate their sustainable economic, environmental, and cultural development. Within this context, it is important for policy-makers to incorporate sustainable initiatives into tourism-related policy making. The question of how policy-makers can incorporate sustainable initiatives into tourism-related policy making in a way that will allow them to develop implementable policies and achieve sustainable tourism is, however, not a simple question to answer. Since tourism practices are depicted as processes that reflect different competing interests and values, in order to incorporate sustainable initiatives into tourism-related policy making and achieve sustainable tourism, the first step should be understanding different competing interests and values and their possible contributions to sustainable tourism. This study is aimed at contributing to this area by investigating tourism stakeholder groups interests and values and their influences on tourism development through a system dynamics approach.
Climate change (CC) mitigation and adaptation are preeminent goals of the European Union (EU) because there is a need to produce and consume in harmony with the global ecosystem that sustains us. To achieve those goals, the EU has set a target of ten percent green house gas emissions reduction in the agricultural sector relative to 2005 levels by 2020. The development of optimal strategies to meet that goal is the responsibility of each individual country, which suggests that country-specific research on the topic is needed for policy makers. Spain presents a unique setting for the study of optimal CC strategies because its agricultural sector is diverse and highly threatened by CC. This paper develops a continuous dynamic model in order to elucidate the current and emergent relationships and behaviors between the agricultural sector and its direct natural resources, human capital and social capital. The final aim is to identify efficient CC mitigation and adaptation strategies for the short and long run that consider the relationships between economic, natural and social systems. The model structure is based on the Spanish AgroSAM (social accounting matrix), extended with natural resource, human capital and social capital satellite accounts, and converted into a general disequilibrium model.
Detailed individual level simulation models are needed for better policy analysis to combat the costly obesity trends. Current models largely focus on adulthood and do not capture variations across individuals. In this paper I develop a simple simulation model spanning the full life cycle of an individual that captures both weight changes and growth in height. The model is tested for consistency with growth charts, robustness under different energy intake scenarios, and consistency with other empirical sources including a previous model from the literature and the experience of a lost ocean traveler. The results suggest the model structure is capable of capturing the key trends in growth and weight dynamics, however better data sources are needed to estimate a few of the model parameters empirically.
Reproducibility of research is critical for the healthy growth and accumulation of reliable knowledge, and simulation-based research is no exception. However, studies show many simulation-based studies in the social sciences are not reproducible. Better standards for documenting simulation models and reporting results are needed to enhance the reproducibility of simulation-based research in the social sciences. We provide an initial set of Reporting Guidelines for Simulation-based Research (RGSR) in the social sciences, with a focus on common scenarios in system dynamics research. We discuss these guidelines separately for reporting models, reporting simulation experiments, and reporting optimization results. The guidelines are further divided into minimum and preferred requirements, distinguishing between factors that are indispensable for reproduction of research and those that enhance transparency. We also provide a few guidelines for improved visualization of research to reduce the costs of reproduction. Suggestions for enhancing the adoption of these guidelines are discussed at the end.
Extending the line of research on stock-flow performance we examined the impact of personality characteristics on task performance. It was assumed that the need for cognition, the need for closure and the preference for intuition and deliberation would relate to individual variations in task performance differentiated into the dimensions heuristic reasoning, task effectiveness (number of correct answers) and task efficiency (time needed to perform the task). It was found that the need for closure did not relate to any of the task performance dimensions, while the preference for deliberation related positively with task effectiveness, and the need for cognition positively with task effectiveness and negatively with heuristic reasoning. Although all three constructs possess a rather explicit temporal dimension, the examined needs and preferences appeared not te be correlated with the time needed to perform the stock-flow task. Further research is needed to substantiate the findings of the current study and to elaborate on the precise relation between needs and preferences and stock-flow information processing as well as to refine the concept of task effectiveness.
This paper presents a system dynamics based macroeconomic model of the Pakistan. The model comprises of population, human development, production, international trade and system of national accounts, and public finance modules. Conscious efforts have been made to achieve the best possible blend of standard long-run theories and country-specific features to model underlying system structure of human centered development in Pakistan by focusing on long-term dynamics. The tracking performance of the model is evaluated. Empirical investigation of a number of topical macroeconomic issues utilizing model simulations have shown the model to be useful which would be extended to address spatial dimension of socioeconomic planning issues of Pakistan. The model helps to better conceptualize the underlying system structure to bring in a broad-based improvement in the human condition without forgoing economic growth. It highlights the need to mobilize cost effective resource generation and suggests that priority be given to allocation of public finance to human development and not the economic services and infrastructure confirming that human development and economic growth are interdependent and intertwined in feedback processes which are mutually reinforcing and that human development is not only an end in itself but is a means to achieve higher productivity as well. This challenges the very basis of continued disregard of human development by public finance managers of Pakistan.
This paper presents a bright future for quantitative System Dynamics Modeling. This future relates to all major issues and grand challenges which all happen to be dynamically complex and deeply uncertain. Combining System Dynamics Modeling and Exploratory Modeling and Analysis allows one to generate, explore and deeply analyze tens of thousands of plausible scenarios related to such deeply uncertain dynamically complex issues, and to design and test adaptive policies over all plausible scenarios. By doing so, the art of System Dynamics becomes the computational science of System Dynamics. This innovative approach is explained in this paper starting from the core of System Dynamics modeling, and is illustrated with three real world applications (pandemic shocks, resource scarcity, and energy transitions). However, more is needed than the brightest analysts and the best analyses for decision makers to decide and take action when facing uncertain complex issues: that is what experiential System Dynamics gaming is needed for. Only when heart and mind are aligned will knowledge and understanding become effective. The use of experiential System Dynamics gaming for conquering the heart of decision makers is illustrated with real world examples too.
In an ever more complex and uncertain world, integrated risk-capability analysis methodologies that allow dealing with increasing degrees of complexity and deep uncertainty are needed more than ever before. Today, some governments and organizations use scenario approaches, risk assessment methods, and capability-based planning, but few have truly integrated risk-capability approaches, and almost none use integrated risk-capability approaches appropriate for deeply uncertain complex risks. However, many important risks are particularly dynamically complex and deeply uncertain. This paper presents and illustrates a novel integrated risk-capability analysis approach for deeply uncertain dynamically complex risks, and discusses near future developments. As such, it illustrates a multi-method consisting of Exploratory Modeling and Analysis, Exploratory System Dynamics Modeling, Scenario Discovery and Selection, and MCDA, and discusses the use of Robustness Optimization for simultaneous all-hazard capability-based planning.
Lyme disease poses an uncertain dynamic threat to many people and public health systems. However, rather different perspectives related to the societal impact of Lyme Disease exist. Thousands of plausible evolutions of lyme disease are generated using different System Dynamics models of Lyme Disease and are studied in this exploratory study with new data analysis techniques in order to assess the risk posed by Lyme disease, in this case to the Dutch population and the Dutch health care system. The risk is scored in the Dutch National Risk Assessment framework adapted to deeply uncertain dynamically complex risks, and mapped in a new type of risk diagram developed for uncertain complex risks in order to compare the risk posed by Lyme disease to many other plausible risks. Scenario discovery techniques are used to identify a small set of representative scenarios that could be used for subsequent capability analysis.
This follow-up paper presents cases and multiple choice questions for teaching and testing System Dynamics modeling. These cases and multiple choice questions were developed and used between January 2012 and April 2012 a large System Dynamics course (250+ BSc and 40+ MSc students per year) at Delft University of Technology in the Netherlands. The cases presented in this paper could be useful for teaching and testing introductory/intermediate System Dynamics courses at universities as well as for self study. For these cases, students need to develop simulation models, answer multiple choice questions related to their models, as well as open questions related to their modeling and model use. Second, the use of multiple choice questions and quizzes for teaching and testing System Dynamics understanding and modeling skills is discussed and illustrated. Finally, changes to the System Dynamics curriculum enabled by further development of the teaching/testing approach of the Introductory System
The scope of this work is to develop an instrument for the economic evaluation of agricultural research in the productive chain of wheat and its impact in the profitability of agricultural cooperatives. A conceptual model was developed using the balanced scorecard and system dynamics methodologies. In the development of the model all processes involved in the productive chain of wheat agricultural research were initially mapped. Furthermore, a BSC strategic map was developed, explaining the objectives and indicators of the cooperative. Finally, using the system thinking approach, a modeling was driven seeking enlargement of the problem systemic vision. The resulting model developed in this work allowed a better understanding of the complex relationships between research and agricultural production, making it easier to analyze the process and the decision of new investments in research on the part of managers and analysts of agricultural cooperatives.
This article discusses about the design of a qualitative model of strategic implementation and control in agro-industrial cooperatives. Based on the concepts of Balanced Scorecard - BSC and System Dynamics - SD, and considering the corporate features of cooperatives as people societies and not capital societies, the article proposes a strategic map, which presents up variables that represent the critic processes in strategic management for these organizations, as well as identifying causal relations hypothesis between the variables. From the concepts of BSC, the map is built with the four traditional perspectives: financial; customers; internal process; growth and learning; and adding two other important perspectives: the social perspective and the member relationship perspective. From the concepts of SD, the map is qualitatively built, predicting the complexity of strategic control, in accordance to the need of conciliation and balance of economic goals between the organization and its members. From the proposed strategic map, the goal is to proceed with the research, defining new indicators of each variable in the map, as well as its adaptation and application towards cooperatives, through the action-research method. The qualitative model can also serves as a conceptual basis for future parameterization and simulation of a quantitative model.
The health care sector is facing a multitude of problems at the same time: rising costs, increase in patients with lifelong diseases, and unsatisfying quality. There is a prominent role for conditions that require a combination of simple (care) and complex (cure) activities. These conditions require different provider expertise; one offering care expertise or more general, preventive monitoring, and the other offering cure expertise, or more specialized, medical monitoring/intervention. In organization design theory the focused factory concept is presented as a way of organizing such processes. However, the application of this concept does not always work well. For decennia, Dutch perinatal care is organized according to the focused factory concept, but recently there has been considerable debate with regard to its performance. Research has shown that the design of the Dutch perinatal care system might not be the right one (Pieters, Van Oirschot, & Akkermans, 2010). In response to its problems, the sector is seeking alternative organization designs. In this paper simulation modeling is used to evaluate these different organization design experiments. From these simulations, we seek to build organization design theory for this type of conditions (Davis, Eisenhardt, & Bingham, 2007; Schwaninger & Grösser, 2008).
Construction projects are complex as they include many activities which influence and interact with each other at different stages. The impact of design phase undiscovered rework on construction phase quality has been hypothesized as influential in project dynamics by many. However few empirical studies have measured this impact. In this paper we develop a simple system dynamics model, estimate it using data from 18 construction projects, and validate the model on a validation set of 15 projects. The model provides good fit for the calibration set and strong predictive power on the validation set. It also allows us to estimate the impact of undiscovered design changes on construction phase quality, which appears to be notable.
In this study, using different versions of a growth management game involving two different complexity factors, we compare performances of heuristic rules with experimental results. We present a method for obtaining a statistical distribution of scores resulting from a given simulated decision heuristic, which can be used to compare against and assess experimental gaming results. The method is based on the idea of generating vast number of scores by stochastically simulating a given decision rule and obtaining the resulting score distribution. We use this method to compare scores from different game versions whose scores are essentially not comparable, and to see how the score distributions change from one game version to another. In simulations, we first use a simple random "decision rule" and then develop a more intelligent hill-climbing heuristic. The results show that when the games involve delay, human subjects do not perform better than the random heuristic a primitive rule composed of a sequence of random decisions. On the other hand, in nonlinear games, subjects outperform the random heuristic and their scores fit better the score distribution of the hill-climbing heuristic. We also demonstrate how the score distribution from random heuristic can be used as a reference performance measure.
The aim of this study is to test statistically the effects of delay, nonlinearity and feedback factors on the complexity of a stock management task. The task requires the player to bring the inventory to a target level and keep it there. Each of the individual complexity factors brings different challenges to the game. Using a slightly modified Latin square experimental design, we test the factors at different strength levels. We use two measures of game complexity: game scores and players subjective difficulty ratings. The results show that, with respect to the simple base game, delay and nonlinearity create worsening in game performances. Also, with increased delay duration, delay order and nonlinearity, subjects' performances deteriorate. However, feedback does not deteriorate the game performance. Furthermore, increased feedback strength even improves scores, due to a technical side effect on the performance measure. All subject groups exhibit learning by repeated trials. Nevertheless, there is also evidence that delay prevents transfer of learning to other game versions. The subjective complexity ratings of the players yield parallel results, the overall correlation of game scores with the subjective difficulty ratings being +0.59.