The unconscious application of sophisticated tools, and in particular the popular reverence to data as the source of knowledge, seems to be the rule in many scientific activities in which the application of tools replaces thinking and data analysis replaces understanding. In this respect, system dynamics has much to offer, though sometimes it is tricky to appreciate its full value and scope. One of its trademarks is known as operational thinking. This paper underlines that operational thinking drives a distinct epistemic posture. This posture, unlike traditional scientific practice that seeks to explain the world by means of data analysis, intends to understand the world in terms of its operations. In this paper I explore the significance of such a posture for the domain of human systems, I highlight its epistemic value in particular with respect to the prevalent observational approach to science, the Humean problem of induction and determinism. Operational thinking means to recognize that human systems do not obey laws to be discovered by observation and data analysis, instead, it acknowledges agency, that is, the fact that a social system is the result of the consequences of actions taken by free decision-makers
The paper introduces a system dynamics Taylor rule model for monetary policy feedback between the real interest rate, inflation and GDP growth for the 2004 to 2011 period in Brazil. The nonlinear Taylor rule for interest rate changes considers gaps and dynamics of GDP growth and inflation as well as monetary policy sluggishness. The results outline a high degree of endogenous feedback for monetary policy and inflation, while GDP growth remains strongly exposed to exogenous economic conditions. Furthermore, stocks of absolute monetary policy flows provide a new mean for assessing empirical monetary policy moves. The stocks show that Brazilian monetary policy has been more driven by growth than by inflation considerations in the period under investigation. Moreover, simulation exercises highlight the potential effects of the new BCB strategy initiated in August 2011 and also consider a recession avoidance Taylor rule. In total, the strong historical fit of the Taylor rule model calls for an application of the model to other economies.
This research is to provide a methodology for making policy scenarios based on the system dynamics. The authors deem this new methodology would be a useful tool for policymakers to make policy scenarios. As for the case study, this research deals with the policy scenarios for managing polioviruses in Japan as an example. This methodology includes both the simulation part of using System Dynamics and the conversation part related to Scenario Planning. Through using this methodology, we had structural understanding of the problem with the visible simulation results and conversation with member which was focusing on the parameters that would be a part of suggested scenarios. This methodology is expected to improve the public deliberations for making policy scenario based on data.
It is known that the presence of a supply line delay may lead to unwanted oscillatory stock behavior. It is also well known that fully considering the supply line in the ordering decisions, which means using the same adjustment time for stock adjustment and supply line adjustment terms, prevents unwanted oscillations. The effect of using the same or different adjustment times is relative. Therefore, in the literature, it is suggested that a weight coefficient should be used instead of explicitly using two separate adjustment times. This weight is simply equal to stock adjustment time divided by supply line adjustment time and it is named as weight of supply line. In this paper, we defined one more decision parameter that we call relative aggressiveness, which is equal to acquisition delay time divided by stock adjustment time. The existence or non-existence of stable or unstable oscillations is a function of the order of the supply line delay structure, weight of supply line, and relative aggressiveness. Usually, acquisition delay time and order of the supply line delay structure are not decision parameters; weight of supply line and stock adjustment time are. In this paper, we aim to give more insight to the readers about the selection of these two important parameters.
Understanding historical overshoots is vital for policy-making, not least when assessing potentials for future global overshoots. For this purpose a simple, unifying theory of overshoots is described and discussed for a variety of observed overshoots. For undesired and avoidable overshoots, misperception at some level must be a major cause. Laboratory experiments support this hypothesis and point to dynamics as the main complicating factor. The theory suggests that misperceptions may cause global overshoots both because of climate change and scarcity of cheap fossil energy. New generations of simulation models are needed to study overshoots, test policies for sustainable development, and to aid information dissemination.
The study presents a System Dynamic model of the Nigeria electric power system. The model was developed with a view to using it to evaluate the long-term performance of the system. Both primary and secondary sources were employed to collect the systems baseline information. Results from this formed input to develop a four-sector-model in Vensim software for the long-term evaluation of the NEPS. Leverage points in the model were identified from the validated model using data from 2005 to 2009 in the Base Run. The system behaviour, based on two other scenarios (Scenario 1 representing improved basic level of consumption and Scenario 2 representing industrialization target), was then evaluated on a timeframe of 50 years starting from 2009. The study concluded that Compounded Annual Growth Rate (CAGR) and Economic Growth Rate (EGR) were the most critical policy leverage intervention points for NEPS improvement within the next 50 years.
The paper explores the relevance and use of games for speeding up the energy transition in the Dutch built environment. Since the transition of the Dutch energy system with the current policies is much slower than required given the urgency of the foreseeable problems and the substantive system delays. There seems to be a need for experimentation with innovative policy instruments, governance mechanisms, and systemic conditions. This paper includes applied emphases upon two topics as well as illustrations of the usefulness of games as tools for getting a grip on the energy transition. In this context, a conceptual model has been developed to illustrate the possible causes of the aforementioned slow transition in the built environment. Furthermore, we discuss the potential roles of games for managing the transition in the built environment and illustrate with an interactive experimental game developed for hypothesis testing and learning purposes. Finally, based on the results of the game we explore the possibilities for future research.
We discussed a management of Airline-Airport coexistence for a sustainable air transport system. Governments provide various financial supports for unprofitable regional airways when the airways are essential for local life and economy but providing inefficient subsidies are often criticized worldwide. This paper aims to examine the validity of Load Factor Guarantee (LFG) scheme in which an airline and an airport mutually agree with the load factor of a flight and the airport would compensate for the discrepancy between the actual and the agreed load factor. We analyzed the LFG management using the data of Noto Airport and All Nippon Airways (ANA) from 2005 to 2011. Examining several scenarios with System Dynamics, we found that LFG would be effective to maintain regional airways when combined with appropriate level of subsidy. The results illustrated that only having annual negotiation on a target load factor cannot balance the benefits between an airline and an airport and thus does not sustain the mutualism. Integral management of LFG and monthly demand adjustment is the key to success for the airline-airport coexistence. The SD model can be applicable to airways worldwide and contribute to better design and management of a regional air transport system.
An introduction of the participatory element into the existing policy making scheme challenges the whole policy making practice, since unmanageable stakes have a risk to mask the proper distribution of interests and hide needs wider of the society . The particular interest of this research is to describe participatory modeling procedures and construct the model by means of system dynamics that capacitate an input of policy stakeholders via a rational balance of interest expression in policy making and policy administration streams. The primary intention is to use these modeling techniques for the description of participatory procedures and apply them to governance of wider public policy issues. The model primarily is targeted to introduce such mechanisms to the policy making process that enable control of the completeness of the stake representation and to balance the stake representation. Equally the model has to protect policy makers from narrow interest advocacy against the public interest.
We present a system dynamics model called GT-Mod for assessing the development and management of geothermal energy production. The model simulates the entire geothermal energy cycle by representing the major components as a set of connected sub-systems that include the power plant, the injection well, the geologic reservoir, the production well, the surface feeder and distribution pipes, the pumps, and the economics. GT-Mod uses a Latin Hypercube Monte-Carlo approach to propagate uncertainties in various input parameters to calculate the systems thermal and power performance over the lifetime of the project and to assemble a probability distribution of the levelized cost of electricity (LCOE) that is used to estimate the integrated risk as a function of input uncertainty. Integrated risk is the summation of the product of consequence and probability over all probabilities and represents a comprehensive metric for benefit analysis that includes the full range of uncertainties in a particular problem. GT-Mod is also used to bound viable solution spaces and to identify areas of uncertainty that have the greatest influence on risk. An example based on a hypothetical but realistic geothermal site is presented that demonstrates the models application and highlights the suitability of the system dynamics approach.
In this paper we explore behavioral issues, coupled with temporary capacity imbalances that could influence the characteristics that a service supply chain may assume in the long run. We look at a service chain in which processing times by human agents are endogenously determined by what constitutes an acceptable and credible backlog, but implicit incentives, particularly within a formal hierarchy, may also impinge upon throughput rates at certain stages of the supply chain when agents are trying not to overwhelm downstream stations with excess work. We explore these issues in the context of a managerial intervention in a judicial service supply chain. Using data from a detailed case study we develop a preliminary model and discuss some results.
Mismanagement of societal aging is an important threat to health care systems, social security systems, and the economy of many nations. A System Dynamics simulation model related to societal aging in the Netherlands and its implications for the Dutch welfare system is used here as a scenario generator for Exploratory System Dynamics Modeling and Analysis - a System Dynamics-based approach for exploring and analysing deeply uncertain dynamically complex issues and testing policy robustness many plausible futures. Key concerns derived from this exploratory research are (i) the existence of plausible futures with severe labour scarcity, especially in health care, (ii) unsustainable evolutions of health care costs, and (iii) insufficient labour productivity, especially in health care. Our analysis shows that labour productivity may be cause of and cure for many of the undesirable evolutions. We conclude that (i) sufficient increases in labour productivity in health care as well as labour productivity in general without pinching the necessary workers in care are needed, and (ii) sufficiently raising the retirement age only helps if both the willingness to work longer and the willingness to keep older employees increase. These conclusions are derived from systematic data analysis which is fully documented in the appendix.
Supply chain collaboration is the key to success in business. A major challenge in such collaborations is the dilemma between locally optimized quick solutions and the more systemic, long-term but slow-acting approaches. Such dilemma in business collaborations has been contemplated in supply chain management research, illustrating their respective benefits and disadvantages. In light of the findings from literature, this study investigates the dynamics of this dilemma using an integrated perspective, utilizing both theories and case studies in supply chain relationships and collaborations. The archetypical dynamics and behavior of relationships over time are modeled, proposing an ever-evolving framework of supply chain collaborations. Along with the model, a prototype of a supply chain collaboration simulation model is also presented, as a customizable environment for policy testing and demonstration of different supply chain collaboration approaches. This model may also be used for training purposes as Microworlds.
The productivity of services has recently become the subject of intensive research. While most contributions here have focused on developing measurement concepts, so far little is known about the dynamics of productivity in service companies. Because productivity tends to increase if the service delivery process is enhanced and improved, there seems to be a link between incremental service innovations and the productivity of services. Therefore, this article analyzes the interaction of innovations and productivity over time in knowledge-intensive business services (kibs). A simple system dynamics model was constructed to examine these dynamics and interactions over the life cycle of an exemplary knowledge-intensive business service offer. First the system structure is developed using literature analysis. Second, several simulation runs and experiments are conducted, to obtain a deeper understanding of the interactions of service innovations and productivity. The paper closes with findings and conclusions.
We report the results of a collaborative decision making exercise using a simulated stability operations task. The exercise allowed Canadian Forces personnel to experience first-hand the benefits and challenges of taking an integrative decision making approach (i.e., with information and resource sharing) compared to a stovepipe approach (no communication and partial view of the whole system). While teams generally achieved greater mission success in the integrated condition, they could only partially cope with the complexity of such an endeavor. A training session on systems thinking and collaborative design generally improved integrated planning effectiveness. We designed a decision support tool capable of suggesting an effective integrated course of action based on qualitative information about system structure and effects. The tool essentially relies on an innovative 'action-oriented' cross-impact matrix and decision matrix that jointly allow deriving a viable resource allocation given a range of intervention options. The prototype tool aims to be simple and generic for use in real-life applications. The system's inputs are based on simple user judgements (i.e., mental models). We show that the tool provides solutions superior to most human teams. Future research will test the generalization of the approach and assess human ability to refine the tools' solutions.
Coastal communities dependent upon groundwater resources for drinking water and irrigation are vulnerable to salinization of the groundwater reserve. The increasing uncertainty associated with changing climatic conditions, population and economic development, and technological advances poses significant challenges for freshwater management. The research reported in this paper offers an approach for investigating and addressing the challenges to freshwater management using innovative exploratory modeling techniques. We present a generic system dynamics model of a low lying coastal region that depends on its groundwater resources. This systems model covers population, agriculture, industry, and the groundwater reserve. The system model in turn is coupled to a powerful scenario generator, which is capable of producing a comprehensive range of plausible future scenarios. Each scenario describes a unique future pathway of the evolution of population, the economy, agricultural and water purification technologies. We explore the behavior of the systems model across a wide range of scenarios and analyze the implications of these scenarios for freshwater management in the coastal region. In particular, the results are summarized in a decision tree that provides insights into the expected outcomes given the various uncertainties, thus supporting the development of effective policies for managing the coastal aquifer.
Rockström et al. (2009) introduced the concept of a safe operating space for humanity that will not push the planet out of the Holocene state. Establishing the limits of this operating space is ongoing for various earth bound systems. Estimates of these limits are plagued by uncertainty. In case of the limits to the world water system, these uncertainties arise out of conflicting models, regional variations, limitation of expansion of water use through financial and institutional capacity, uncertainty about the realization and efficiency of trans-boundary water transfers, and interdependency between the water system and other earth systems. This paper aims at investigating the limits to global freshwater use. To this end, the behavior of a System Dynamic model of the world water balance is explored across a wide variety of uncertainties. Active non-linear testing is used to identify the best case and worst case for water stress and world population. We find counter intuitive results related to the occurrence of maximum water stress, conclude that global limits can be investigated with a spatially aggregated model and are strengthened in our hypotheses that exploratory modeling adds to the understanding of complex and uncertain issues in a way that predictive approaches cannot.
Urban mobility is a prevalent problem in many cities around the world. Cycling offers a fast and cheap transportation option for short-distance trips, with smaller carbon and physical footprint than driving a car. Cycling can also encourage a modal shift from private car to public transport by providing efficient last mile connections. This has led to a renewed interest to promote cycling in cities, manifesting in a growing number of bike-sharing projects with larger bicycle fleets. However, the economic sustainability of these bike-sharing systems has not been demonstrated. Moreover, city governments may invest resources in bike-sharing projects at the expense of developing policies or infrastructure to improve cycling safety and convenience. We take a systems perspective to study how bike-sharing and other policies can influence cycling as a transport mode in the urban mobility problem. We observe that while bike-sharing projects may increase cycling level and generate public demand for better cycling infrastructure in the short run, loss-making bike-sharing projects can discourage the infrastructure investments over the long-run, thereby hampering cycle adoption. Public funds should not be invested in bike-sharing programs at the cost of cycling infrastructure. Instead, governments should facilitate economically viable bike-sharing systems by the private sector through adoption of appropriate policies. Investments in cycling infrastructure should come first.
In the passenger car sector purchasing decisions are driven by economic factors and acceptance. Based on cost analysis, the factors which can be dedicated to different technologies are fuel costs and purchase price. The decision to buy a new car is always accompanied by a cost comparison of each alternative. This leads to a compilation of costs for each technology in terms of negative utility. The decision process is solved by a Logit-Model. The realization within a system dynamics model allows the modeling of feedback loops.
Assessing impacts of policies and strategies to reduce CO2 emissions from road transport requires an integrated modeling approach. System Dynamics suits perfectly as methodology to simulate the dynamics determined by feedbacks between transport, energy, economic and environmental systems. The ASTRA model incorporates these capabilities. The paper at hand describes the structure and the dynamics of the ASTRA model and zooms into the vehicle fleet model. The dynamics considered in the technological diffusion model is explained in detail. Finally, the paper presents a set of different scenarios which should create a common understanding on the complexity of the transport and energy system and the potential contribution of policies and technologies to reduce the carbon footprint of car transport.
This paper deals with prostitution-related human trafficking. After a brief introduction into the problem of prostitution-related human trafficking, this study focuses on the Dutch policy debate. A first dynamic simulation model is presented based on the problem situation in the Netherlands intended to explore the field and give more understanding about the effects of proposed policies. Using this simulation model a short policy analysis is carried out uncovering the dynamics of the system leading to some preliminary conclusions. Finally it is argued that deep uncertainties exist in this problem field and this is just the first model from various plausible models that are currently developed. An in-depth exploration of the uncertainties related to many of the parameters, functions and structural assumptions will be performed using Exploratory System Dynamics Modeling and Analysis.
One of the main goals of system dynamics models is to improve decision making in dynamic systems. This paper addresses the question of how we can measure what people understand about dynamic systems and what benefit people get from exposure to system dynamics models. For this purpose, we use existing literature about assessing understanding and learning in system dynamics to reflect on outstanding research questions in this area. Learning about dynamic systems requires restructuring of existing knowledge into new knowledge as well as re-use of such new knowledge over time and in different contexts. Existing approaches in system dynamics use elements of dynamic systems to represent knowledge.
The impacts on energy generation and use on sustainability, increasing energy demand, and declining natural resources have made energy improvements a top priority for many organizations. But adequate financing for sustainability improvement projects for built infrastructures is not available. The Paid-From-Savings approach can leverage savings to pay for energy improvements. Although well established and adopted by many organizations, an incomplete understanding of the dynamics of these revolving fund programs hinders their effective and efficient use. In the current work the Harvard Green Campus Initiative and a Texas A&M University sustainability improvement programs were used to develop a dynamic model of a revolving sustainability fund. The validated model is used to test the effectiveness of three project planning strategies and two finance alternatives. Results indicate that with adequate funding it was most advantageous to proceed with all projects as quickly as possible and that with insufficient initial funding the best strategy depended upon the program objectives (e.g. earliest completion, largest fund, minimum negative fund balance). Contributions to sustainability and system dynamics modeling and future research opportunities are discussed.
Meeting 21st centurys challenges of climate change and scarcity of crude oil requires the transition to alternatively powered vehicles, such as electric vehicles. As a consequence, car manufacturers have to integrate these vehicles into their product portfolios. Decisions have to be made about, for instance, the power-train to be offered in specific vehicle models and their times of introduction. This is a complex decision making task, especially due to high uncertainties about the future development of the market demand for alternatively powered vehicles.
Introducing System Dynamics(SD) to solve a complex problem is difficult in two ways: 1) modeling the problem behavior, and 2) selling this approach as a desirable alternative to past troubleshooting methods. Adding the new concept of SD to the problem-solving mix often results in resistance. The perception is that other solutions worked in the past and there isn't time to learn new methods. This classic Limited Growth Archetype is best managed by addressing the balancing loop factors that limit adoption of change. In other words, the change agent needs to identify opponents and change their minds. In this paper I suggest that there is another way: provide the concepts and lessons without recipients being aware.
The financial crisis shifted the focus of monetary policy. Whereas before the crisis the main goal of using monetary policy instruments was to keep the inflation rate low after the crisis policy makers put much emphasis on stabilizing the financial system. The economic literature has started to elaborate on the issue of macroprudential regulation only recently. Financial turbulences, by their very nature, constitute a complex dynamic phenomenon. Hence, an analysis employing tools of system dynamics should help to improve our understanding of the underlying feed-backs. In order to link economic reasoning and the systems approach a model of financial behavior developed by Stein is introduced and used to create building blocks for a basic dynamic simulation model.
Alcohol use is prevalent among college students in the US and is the leading cause of many alcohol-related consequences such as injury, driving under influence, and sexual assault. The problem of college drinking involves complex individual, social, and cultural factors. By viewing college drinking as a complex system problem, this paper describes two components necessary for the full development of a simulation-based dynamic agent model for alcohol use in college. The first component is a basic agent-based model that explores the dynamic of college drinking. The second component discusses the use of system dynamic modeling to explore the causal relationship between various personal/environmental factors and alcohol consumption. The paper also discusses important leverage points for intervention strategies, especially in the context of targeting both high-risk and low- to medium-risk drinkers in college.
The problem of empty houses in Taiwan continues to concern the public. The Government currently conducts housing survey to detect the number of empty houses every year. But, no systematic analysis of the monitoring and early warning programme has been undertaken to improve the situation. This study formulated dynamics and genetic artificial Neural Network models for the monitoring and early warning system stimulating. Several strategy scenarios were conducted. The research findings showed that economic strategy has a more positive and profound impact than financial one; combined strategy often has a better policy assessment compared to a single strategy. The method developed in this study is a comprehensive and systematic approach to achieve the sound housing market in Taiwan.
Health system reform is a national priority in the U.S., but it is increasingly being pursued through a mosaic of local initiatives. More and more concerned leaders in cities, towns, and regions across the country are working within their local health systems to achieve better health, better care, lower cost, and greater equity. Such ambitious and widely dispersed ventures, however, are hard to plan, unwieldy to manage, and slow to spread. Further progress could occur if diverse stakeholders were better able to play out intervention scenarios, weigh trade-offs, set aside schemes that are unlikely to succeed, and enact strategies that promise the most robust results. Through the Rippel Foundations ReThink Health initiative, veteran leaders and creative methodologists are learning what it takes to spark and sustain system-wide improvements in different settings. Interactive simulation modeling and game-based learning support innovators by bringing greater structure, evidence, and creativity to the action planning process. In this paper we provide an overview of the ReThink Health Dynamics simulation model by providing a summary of its structure, intervention options, data sources, user interface, experiences in pilot sites, initial insights, evaluation plan, and possibilities for further development and diffusion.
Organ transplantation is a lifesaving procedure for many people. However, the lack of organs from deceased donors makes it unavailable for many additional people who need it. A commissioned study was undertaken to estimate deceased donor potential in the US. Organ procurement and transplantation take place in the context of a complex system of organizations and policies. This system can both constrain and enhance the realization of deceased donor potential. A system dynamics model is being developed to help identify how that systems behavior affects the availability of deceased donor organs and how particular strategic policy options might increase the number available for transplantation. The structure and data sources for the model are described along with illustrative tests of those strategic options.
Fast growing electricity demand in Indonesia has threatened countrys economic development pace. However, government owned Electricity Company cannot cope with this growing demand. As a result they rely on Independent Power Producer (IPP) which harm government budget. In the mean time, government realizes this growing issue and tries to do something by building more power plants. On the other hand, their plan on building new coal and oil based power plant is meeting a lot of resistance from NGO and parliament. On top of it, government cannot afford continue funding electricity from IPP. The situation is increasingly become worse if government does nothing about the issue. Therefore, understanding and smooth communication is needed to provide solution for the issue. A system dynamics based game is built to foster communication between stakeholders, in order to help them visualize dynamics and feedback loop inside Indonesias electricity system. In the first development phase the game tested on group of students and showed good result on improving their understanding on current electricity issues.
Quantifying the strength of causal loops on a stock can help bring insights into the relationship between model structure and behavior. This paper uses mathematics to derive loop strengths in a number of generic small models using the relationship between the second and first derivative from the Pathway Participation Metric method. The loop strengths are plotted in a System Dynamics (SD) simulator together with the stocks to help explain behavior in the Limits to Growth, Predator-Prey, Diffusion and SIR models among others. Issues such as loop dominance, flow dominance and the change of polarity of higher order loops are used to explain behavior. In particular the identity of the causal loops in the Diffusion and SIR models are discussed and compared with previous work. Finally a numerical method for computing loop strengths and identifying dominant loops within an SD simulator is presented and applied to the Yeast Model. It is hoped that the paper will inspire others to use loop strengths in their analysis and understanding of SD models
Recent trends in demographic changes in Germany mainly because of rapid population ageing represented as increasing ratio of older population over total population, have become a major problem for the German government. They are worry if recent trends continues it would cause massive disturbance in Germany socio-economic system, starting from vast amount of pension fund government have to pay to immerse fall of countries GDP. Therefore, by using System Dynamics approach this paper offers systemic point of view on how population structure changed in Germany; it explain why fertility rate in Germany stays low and how economic indicators would trigger changes in population structure. Moreover, it also illustrates feedback effect from population age structure to economic indicators. The result shows that current trends will continue and will not dampen if there is no adequate policy intervention from government. Hence, this paper offers set of policy measures to stabilize increasing ratio of older population. By opening more immigration opportunity for productive age workers, increasing child incentives, increasing pension age, and promoting gender equality as a set of policy measures might exhibit a better result to stabilize the population age structure. This policy measures effect shows desirable result toward expected behavior.
Firms have long used strategic foresight to adjust to fast changing business environments and increasing uncertainties. While strategic foresight on a corporate level is rather common, approaches addressing the network perspective are still rare. Documented attempts within the last few years to combine different foresight methods indicate a need for integrated approaches. Methods to communicate and discuss future thoughts between strategists and decision makers engaged in foresight processes gain importance. The goal of this paper is threefold. First, to present a strategic foresight approach that evaluates key drivers of future changes. This evaluation is conducted based on a firm's business model by considering the network perspective. Second, the application of the approach is shown with focus on the development of a system dynamics model during a group model building process. Third, a generic system dynamics model for performing strategic foresight in production networks is introduced.
The purpose of this paper is to investigate whether stock/flow failures persist in naturalistic decision making environments. A tangible stock/flow experiment is used in this study, which asks participants to pour a certain amount of water into a glass through a funnel in an as short time as possible. Findings are that people on average do not perform better in a tangible stock/flow task than in a computerized or paper-based test of a comparable task. In addition, individual performance in the tangible task cannot be related to performance in a similar paper-pencil stock/flow task. An implication of this study is that naturalistic stock/flow tasks are as difficult for humans to control as more abstract tasks. Further research should address individual differences between the two modes of task (tangible vs. paper-based). A limitation of this study is the usage of one tangible stock/flow task only. The value of this paper lies in the combination of a standard test with a tangible experiment addressing the same cognitive capabilities.
Different approaches to model feedbacks in financial systems are assessed based on requirements for the conceptualization of the feedback dynamics. Given the non-linear, behavior driven, and interconnected characteristics of systemic financial feedbacks (SFFs), modeling concepts from System Dynamics (SD) theory provide appropriate and attractive features. Surprisingly, few SD models exist to explain systemic financial feedbacks. The scarcity of SD modeling for SFFs may be attributed to the lack of required economically-sound foundations for theoretical modeling. This paper considers a conceptual framework for SFFs that emerges from the synthesis of formal principles of economics and SD. In doing so, this study links existing SFF models to concepts of SD and provides suggestions for further modeling.
This paper describes the role of systems modeling in the National Parks. The parks have been described as Americas Best Idea, and they are celebrating their 100th year anniversary. Systems thinking and systems dynamics can help the parks plan for the second century.
This paper presents a review of the criticisms of system dynamics and assesses the validity of these against recent findings in the field. The authors survey the literature critical of system dynamics and review their criticisms using the current understandings in the system dynamics field. This work suggests that there are some pertinent criticisms that have been aimed at system dynamics. These include the apparent disagreements regarding the role of historical data in model confidence building, system dynamics' reductionist perspective and how system dynamics addresses plurality and hierarchy. Overcoming these criticisms require the ever present need for education, communication and theoretical work. It is hoped this paper will strengthen the mandate of system dynamics in the eyes of its critics, assist and improve the field and its general acceptance as a tool of analysis.
System dynamics unmistakably has perfect innate capabilities for helping responsible decision making in an increasingly complex world. But as Forrester (2007) sighed, the system dynamics community is not yet making the change for policy making it should aim at. One possible cause is that many system dynamicists are specialists in the SD method and generalists as regards to the themes involved. As a result, there are few position papers collecting the system dynamics insights of all relevant studies in one particular area of application. The purpose of this paper is providing such an overview of system dynamics works on recent dynamics in global real estate markets.
The article sets out to describe the first stages of conceptualization process initiated within the scope of an action research project in the field of waste and residual resource management in a large urban center in a low-income country. For the project it is important to test that the technological concepts developed by the project have the potential of improving waste management in future megacities. This involves evaluating if when implemented, these technological solutions can contribute to the alleviation of the current problematic situation. Additionally, it is important for the project to find out to what extent could the performance (financial, socioeconomic, environmental, etc.) of the waste management system improve as a result from the implementation of the waste management strategies it proposed. For this purpose a set of simulation models is being conceptualized and developed using a modeling methodology (namely System Dynamics), which will allow evaluating how the waste management situation would evolve if a set of strategy options would be introduced. This would be done by comparing the future development of the system in the absence of the strategies (business as usual) with the development of the system in the presence of the strategies. The article presents the first results of model conceptualization and gives an outlook of the activities that will follow.
This paper examines the effectiveness of different delivery methods for teaching System Dynamics to undergraduate engineering students. The paper presents the findings from a survey of the learning styles of the student population and compares that to the current breakdown of the course content by learning style. It presents the findings of several classroom assessment techniques that were conducted over the course of a semester to evaluate the effectiveness of the delivery methods utilized in the course. The classroom assessment techniques focused on an evaluation of the effectiveness of readings, lectures, labs, and case studies in teaching the material. Additionally, students participated in two self-confidence surveys mid-semester and at the end of the semester, which evaluated their confidence in their ability to accomplish the course objectives and the content delivery methods. Based on this evaluation, the paper presents recommendations for improving the content delivery methods of the course to take advantage of the student populations learning styles.
Ongoing counterinsurgency operations in Iraq present a complex, dynamic environment in which traditional analytical methods struggle to explain the behavior over time. System Dynamics is extremely well suited to analyze this environment as the methodology focuses on understanding the structure of the system and the behavior it creates. This paper proposes a system dynamics model of reconstruction projects for essential services to examine one aspect of this operating environment. One of the many challenges that exist in this environment is determining the proper balance between the use of the Commanders Emergency Response Program (CERP) for small scale and major reconstruction projects. This paper attempts to mitigate this challenge by analyzing the structure of the system, modeling the behavior of the system over time, and proposing policy recommendations to improve the system behavior. Although the model is not calibrated to historical data, it produces behavior consistent with behavior described in Army doctrine. The causal relationships provide valuable insights into the dynamic behavior of reconstruction efforts and their impact on essential services. With further calibration of the model, leaders can develop and evaluate policy alternatives for capacity development to mitigate the impact of the insurgency.
Although both India and New Zealand recognise trade between the two countries as important for their respective economies, the current and past trade in information technology between the two nations has been very low. This research seeks to study this problem situation systemically by analysing the complex interactions of factors responsible for this situation. While most of the literature on IT offshore outsourcing is based on client perspectives, this study takes a service provider perspective. A causal loop model is developed to explain the underlying structure related to this problem situation. Finally, strategies to improve the problem situation are discussed using an analysis of the feedback loops captured in the model.
Unconventional gas has raised debates all over the world following its considerable contribution to the natural gas production of some countries such as the US. The Netherlands, which is a prominent gas producer in the Western Europe, also considers unconventional resources as an alternative to conventional production, which is estimated to significantly decline in the next 25 years. However, the development of unconventional gas in the Netherlands is surrounded by several uncertainties. In addition to parameter uncertainties, uncertainties in the boundaries and structures of the models used in the analysis of this future development play an important role. This study aims to investigate the effects of such uncertainties on the production rate of unconventional gas, by combining the Exploratory Modeling and Analysis method with four different SD models. The results show a wide range of production rate possibilities, where the variety is mostly caused by the model uncertainties. This study can be extended with more model alternatives, and the results of this study can be used in further analysis for robust policy making.
Aggregate continuous time formulations used in System Dynamics models result in the implicit mixing of individual constituents of levels. Normally, this is acceptable as the heterogeneous nature of model variables implies that some individuals counted in a levels value will pass others and exit earlier. In models with a focus on chronological aging and age-related characteristics this phenomenon, which we call cohort blending, can result in large distortions. Though these distortions can be reduced by using aging chains, they persist in a significant way even when using one-year grouping in the aging chains. As an alternative, we introduce an approach we call continuous cohorting in which populations are tracked with cohorts sized the same as the computational interval of the model. This approach eliminates the blending problem with minimal notational and moderate computational burden. The resulting models display quantitative, though limited qualitative, differences from their traditional counterparts and are more easily defensible with demographers and others who study population.
There are increasing environmental concerns in México, as in many other countries, regarding the CO2 emissions tendency, due mainly, to the intensive use of fossil fuel based electric generation. Recently, several laws and amendments have been passed in Mexico with the objective of promoting non-fossil generation technologies, aiming to increase their relative participation in the energy portfolio mix. Although several mid and long term objectives in this regard have been established in Mexico, these would be hard to achieve if the investment capabilities should continue to be directed mainly to fossil fuel thermal technologies, like natural gas on combined cycle plants, and proportionally less, to investment in non-fossil technologies. This article presents and evaluates three scenarios based on a System Dynamics Model, to assess the non-fossil generation capacity investment and timing requirements, in order to achieve both ecological and safety strategic objectives, and at the same time satisfying the electric energy Mexican demand expectations.
Supply chain management supported by digital services is one of the most promising areas of research that have emerged in the last years since it has a tremendous potential to improve both operational and economic performance. In particular, distribution of freight is a field that lends itself to the application of the latest information and communication technologies to enable quick and safe ordering and delivering activities. However, in order to make new smart distribution services desirable for users and profitable for providers, careful feasibility studies are necessary to evaluate possible strategies to make the diffusion time as short as possible and secure adequate profits.
Strategic decision on the execution of national security improvement project is greatly important for the present and future national security. Though, the importance of strategic decision, decision making process has been executed under one-way thinking framework. This research provides a decision-making tool with make-or-buy approach for the national security improvement policy execution methods: foreign purchase and military R&D project, and, via simulation, confirms dynamic change of military capability index respect to change in ratio of foreign purchase and military R&D. Results of research are as follows. If the ratio of military R&D investment is under 38%, military capability index from military R&D investment cant overtake increasing effect from foreign purchases in the whole life cycle, so easy to be restricted by another country. Applying the model from this research provides an appropriate ratio for short term and long term defense strategy and policy goal, and consequent result of increase in national security capability. Thus, this research model can be effectively utilized for national security improvement project.