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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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).
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 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 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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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 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.
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 aim of this paper is to illustrate the biofuel model BioPOL and its new developments, to describe a set of scenarios, in which BioPOL was applied and to discuss the results of the scenarios.
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.
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.
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.
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.
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.
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.
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.
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.