This follow-up paper presents seven actual cases for testing and teaching System Dynamics developed and used between January 2010 and January 2011 for the Introductory System Dynamics courses at Delft University of Technology (250+ students per year). The cases presented in this paper range from short to long and can be used for teaching and testing introductory/intermediate System Dynamics courses at university level as well as for self study. Additionally, the use of traditional and new Multiple Choice questions for testing System Dynamics is presented and discussed.
Enormous future investments are needed to replace and expand energy systems, and prepare them for future needs. Moreover, smarter technologies/systems are needed. And in this ever more complex, interconnected, and uncertain world, smarter policymaking in the energy field is certainly needed too. After all, current energy policymaking still mainly ignores (dynamic) complexity and (deep) uncertainty.
Plausible dynamics of a major demographic shift --(societal) ageing-- is studied in this paper, both from a global perspective and from a national perspective.
This paper illustrates the use of Exploratory System Dynamics Modeling and Analysis -- a multi-method combining System Dynamics and Exploratory Modeling and Analysis to explore and analyze uncertain dynamic issues and test deep policy robustness, i.e. policy effectiveness over thousands of plausible futures.
Radicalization and deradicalization are deeply uncertain dynamic processes. Exploring and analyzing many plausible futures and assessing the robustness of policies to reinforce desirable evolutions seem more useful for such processes than trying to predict their precise development over time and optimize the associated policy response. This paper illustrates how the combination of System Dynamics Modeling and Exploratory Modeling and Analysis could be helpful in that respect for deeply uncertain dynamic issues as de/radicalization processes. The generic SD model about radical and non-radical activism used first is methodologically relevant because it generates clear bifurcations. This generic model could be seen as a plausible dynamic theory about how activism may become more/less radical. Specific instances of this generic model are subsequently used to shed light on particular de/radicalization processes - such as animal rights activism - and successful actions to fight radicalization. Finally, SD teaching and testing cases based on these models are provided in the appendix.
The objective of this research is to identify the key factors that impact the system of product commercialization in the Bogota´s market to allow a better comprehension of the growth behavior of the convenience stores in this city.
The use of DDT for Indoor Residual Spraying (IRS) in recent years has proven to be a cost effective way of combating malaria in sub Saharan Africa. A variety of alternatives to DDT for IRS exist. However, their costs and benefits are insufficiently understood. This is particularly true when it comes to evaluating vector control strategies in an integrated way, i.e., also in terms of their broader socio-economic development impacts. The Malaria Management Model project estimated the costs associated with the eradication of malaria for different combinations of vector control interventions and for different time horizons. For this purpose it developed a computer based simulation model that is based on an extensive database and calibrated for the aggregated sub Saharan African region. It studies long-term (1970-2050) trends of malaria diffusion and the implications for socio-economic development. Model simulations showed that for all policy-scenario combinations, the average yearly expenditures for malaria prevention were much lower than the possible average yearly gain in GDP from eradicating malaria. Model simulations also revealed that the additional costs of substituting DDT for IRS create a series of benefits as well as avoided risks that overall more than offset the costs.
In promotion, tenure or funding decisions, publication performances of researchers in scientific institutions are evaluated using some performance measures. However, there is a concern that measuring research performance, if not properly done, may damage science. Researchers tend to change their research practices when they are asked to be good at some particular measure. In this study, a dynamic model is developed for analyzing the changes in publication practices of researchers towards improving the performance measures used. Reputation, skill level, total time devoted to research activities, fraction of papers accepted by the journals, publication and citation pressures on researchers are the basic variables in the model. The model is constructed and calibrated using Bo?aziçi University Engineering Faculty data. Validation of the model is established by standard structure and behavior tests. Scenario and policy analysis are performed with the simulation model. Pushing researchers to publish in high numbers causes spurious publications with low citations. Allowing researchers to spend more time on research activities is found to be an effective policy. Encouraging mostly the high quality research results in more high-quality publications compared to low-quality ones, hence increased citations. The model provides a platform on which many other policies can be tested.
Flood is the most frequent natural disaster in Indonesia. However mitigation program is still not effective, especially the indirect impact related to human health. The limitation on clean water, sanitation facilities, cold temperature and the quality of health surveillance might trigger the outbreak of infectious disease and also ineffective the mitigation policy. Therefore in this paper we use System Dynamic that modeled the the two diseases that mostly emerge during rainy season, diarrhea and acute-respiratory-infections (ARI)to give insight and feasible policy to mitigate and control the potential outbreak of infectious diseases.
For complex dynamic systems there are a limited number of transition paths to shift from their normal system state into a catastrophic system state. In the present paper, the time development for five generic types of paths have been identified and analyzed. Here, concepts of systems science are linked to observations in human-environment-systems and ecosystems. These generic paths allow analyzing systems from a systemic perspective of how their critical threshold is reached.
Over the past several decades, demands on the United States emergency and trauma care system have grown dramatically, but the capacity of the system has not kept pace. The result is a widespread phenomenon of crowded emergency rooms, especially in urban hospitals, which has become a major barrier to receiving timely care and has been implicated in adverse medical outcomes. This paper develops a stylized system dynamics model to examine the dynamics of patient flow in emergency departments. Simulation results show that increased ED resilience can come from relaxing bed constraints or from more human capability to cope with increasing workloads. The vulnerability of this system is rooted in the critical interaction between physical constraints imposed by the environment and the human capability of the staff to work at high performance levels under conditions of worsening workload pressure.
System Dynamics (SD) and Discrete-event simulation (DES) can be viewed as complementary approaches to modeling. Both are popular approaches and have been applied in a wide range of situations for various purposes. Reviewing the literature from the multimethodology field allows us to develop a modeling framework that considers the differing designs for the combination of SD and DES. The aim of the work described here is to test, reflect on and further develop this framework through an intervention, and to examine how the modeling approaches can be combined in practice.
In this interactive half-day workshop we develop and run system dynamics models and simulators to explore sustainability and limits to growth in industrial society. I first describe a small model of the fishing industry. I then use the same model as a metaphor to think about global growth and industrialisation and to interpret the closed-loop feedback structure and dynamics of Jay Forresters World Dynamics model. This famously concise (yet dynamically intricate) model represents an industrial society whose growth is eventually curtailed. We also consider how the conceptual framework from World Dynamics might be adapted to address the societal effects of global warming. In the spirit of SD conference workshops, participants not only listen but also join-in. There is an opportunity to build a tiny metaphorical model and to run a sustainability simulator. We then use these experiences to discuss the role of models in shaping public debate and political action on global warming and climate change.
The public health community is recognizing the importance of social network dynamics in analyzing chronic diseases correlated with behaviors including tobacco and alcohol use, substance abuse, and obesity. These behaviors are driven in part by opinions that individuals hold regarding products, behaviors, and lifestyles. The opinions and behaviors of individuals are influenced by their personal social networks, as well as exogenous components, such as advertisements.
The aim of social scientists is to capture the causal mechanisms that explain behavior of people and groups of people, such as communities, societies or firms. Such an endeavor becomes increasingly difficult as theorizing concerns patterns of behavior. A theory of behavior explains how the cause-effect structure of interaction among specific variables leads to emergent paths of behavior of these variables. Thus, building theories of behavior implies creating a narrative that connects a deep theoretical structure to a repertoire of plausible behaviors that encompass the observed critical events and behaviors. A problem challenging discursive theories of behavior is the quality and robustness of inferred connections between causal structure and emerging behaviors. Equally difficult is to understand how modifications of theoretical assumptions, crystallized into a model, lead to modifications of the phenomenon under study. To make the described endeavor even more challenging, observed patterns of behavior are often produced by path-dependent processes that amplify non-systematic and stochastic disturbances. In this essay, we suggest that the interaction between field research, computer simulation and System Dynamics allows to elicit causal models from the rich texture of everyday life.
The authors developed a Dynamic Whole System Model of Alcohol Harm Reduction for the England Department of Health, to support local commissioning of alcohol related services. The project used group model building, based on the best evidence available. It is intended to help local primary care commissioners reduce hospital admissions attributable to alcohol. The main high impact interventions incorporated are brief advice in Primary Care, the employment of Alcohol Health Workers in hospital, and Specialised Treatment. The key output measures are hospital admissions and costs. The model uses four consumption groups (Abstainers; Lower Risk; Increasing Risk; Higher Risk) including binge and dependent drinkers in more than one state. Each state has a differing propensity for hospital admissions. The model provides a dynamic cost analysis; as interventions move people between states hence changing their risk of admission to hospital. The model contains a set of policies parameterised by the Department of Health, but also allows for local settings. The work relates to the search for consistent and cohesive policies by which central government can guide local actions. The approach of using dynamic models goes beyond action lists for guidance and allows localities to learn what will work for them.
The unprecedented increase in recent years of cartel-related violence has presented growing challenges both to Mexicos socio-political stability and to the United States (US) National interests. Current efforts to address Mexican cartels treat these organizations as only drug-trafficking networks and focus on law enforcement measures to interdict their operations. In this paper, we approach the cartel problem from a systems thinking perspective and present a holistic assessment of these complex criminal networks operating in multiple domains. By highlighting the dynamic relationships and complex feedbacks between critical variables involved in different domains of cartel operations, we identify the inherently systemic causal factors contributing to the problem situation. We argue that the efforts that rely on law enforcement measures and technological assistance alone will fail to produce lasting change. Instead they need to be coupled with high leverage strategies that address the socio-economic root causes that foster weak public institutions perpetuating illicit activities in Mexico.
The escalation of violence in Mexico and along the border with the United States has triggered a number of social responses that attempt both to control and to live with current levels of uncertainty in both countries. Additionally, several other social problems have contributed to the messiness of the current situation making it difficult for individuals and governments to identify leverage points of intervention. This work explores dynamic drivers of the emergence of violence in Mexico and along the border with the United States as a specific manifestation of the social processes that turn illegality into instability. A system dynamics approach is used to explore these issues in an effort to identify high-leverage points of intervention.
Finding the difficulties and concerns of the client, understanding the variables involved in creating the difficulties, exploring the casualty amongst the identified variables and framing the dynamic hypothesis is the most critical and difficult phase of system dynamics modeling process. Although, there are many ideas in literature to carry out this phase, lack of a comprehensive qualitative method is noticeable. Hence, the authors of current paper, by reviewing the literature, introduce an inclusive and customized grounded theory method, specific to requirements of qualitative system dynamics modeling. Additionally, this paper argues that the methodology described in the paper could contribute to integrating of existing methodologies, facilitating the iterative process of modeling and set up a systematic framework in order to maintain and relate findings of qualitative phase to quantitative phase in system dynamics modeling process.
Capital asset replacement has a significant effect on company cash flow, since the investment on new asset is expensive. Overhaul policy can extend the optimal service life of an asset, and results in lower total life cycle cost of an asset. Technological change also affects the life cycle cost and optimal service life of an asset. In this paper we examine the replacement/renewal and overhaul/refurbish policies in a combination under technological change. We used System Dynamics model and simulate hypothetical data for 4 cases, and the output is in line with some previous studies using analytical models.
Tourism is a dynamic and complex system, which involves numerous stakeholders, each with different understandings of the system and holding different management objectives. These different expectations result in unforeseen conflicts among stakeholders that could negatively affect the development of tourism. This paper describes a participatory systems approach to develop a shared understanding amongst stakeholders of the tourism system in the UNESCO designated Cat Ba Biosphere Reserve in Vietnam.
Article describes the complex of imitation models of social sphere. The model complex is intended for support of decision-making in social sphere, focusing on problems of reforming of housing, public health services and social security. The complex is realized on the basis of system dynamics methods and modern technologies of simulation modeling.
In the political violence scholarship, there is a gap in explaining how group-level dynamics cause mass political violence. There are several theories of why political groups become violent. Because of the qualitative nature of these theories and the feedback complexity of political violence, it is hard to test these theories against each other and against data. This paper describes an attempt to use a combination of system dynamics and agent-based modeling to create a simulation pitting rival theories of political violence against each other and against empirical data. The purpose of the research is theory testing: to see what theory or combination of theories best explains political violence. The paper provides an overview of the relevant theory and data. The paper then develops a dynamic hypothesis and a prototype hybrid Netlogo simulation of two theories, political opportunity and collective action.
Out of Stock (OOS) has long been a plaguing problem in the consumer packaged goods (CPG) industry for both manufacturers and retailers. It refers to a situation in which an item is unavailable for sale as intended at a store. One study estimated that OOS items on average cost retailers 4 percent of their annual sales, and manufacturers $23 million for every $1 billion in sales. OOS could be caused by many factors, such as manufacturer production shortage, distribution center delay, consumer demand surge, and sub-optimal store operations, etc. There have been many previous attempts to model and fix OOS. To the authors knowledge, this is the first study to address the full production-distribution system using system dynamics (SD) and help all players understand the structure of the CPG distribution system that contributes to the system behavior that causes OOS, and interventions or improvements that can be made to the system to improve its performance related to OOS events. This paper will describe the OOS model we developed, the insights we gained, and the process we used to translate the initial SD model into a business application that can be employed on a wide range of product and retailer scenarios.
Rework in construction development projects can significantly degrade project cost and schedule performance. In a typical construction development project which involves design and construction, rework in the construction phase could increase construction cost by 10%-15% of the contract price (Burati. 1992, Josephson & Hammerlund 1999, Love & Li 2000). The proportion of money and time spent on rework in the design phase is usually higher (Smith & Eppinger 1997). In large, complex projects, undiscovered rework in the design phase can induce rework in the construction phase. The time when rework is discovered during the project development process affects the impact of rework on overall project performance. However, available knowledge is not always successful in improving project managers understanding of the feedback mechanisms which drive undiscovered rework impacts on project performance, specifically the interaction between different phases during the developing process. The current work uses a system dynamics model of a two phase project development cycle to identify high leverage points for minimizing the impacts of rework on development project performance. Model analysis suggests that failing to discover rework near its creation in the project development process can magnify the impact of rework on project performance.
Large, complex construction projects subject to unique types of risks. One such unique risk is the combination of rework and increased project scope that can push a project from a behaviour mode of progress toward completion, past a tipping point, and into a behaviour mode of falling farther and farther behind. Previous research has demonstrated the potential of rework-induced tipping point dynamics to cause poor cost and schedule performance on large, complex construction projects and the effectiveness of project design strategies in mitigating tipping point risk. Previous research has also examined three project labor control policies (overtime, workforce, and work intensity) and their impact on project performance. However, the impacts of project labor controls on tipping point dynamics have not been fully investigated. The current work uses a simulation model of a construction project to investigate the ability of project labor control actions to respond to tipping point dynamics. The model demonstrates that some well intended and reasonable project labor control actions, such as the extended use of overtime, can push a project over the tipping point to failure.
This paper examines the relationship between sovereign debt dynamics and the stability of financial institutions using a system dynamics framework. The model, which builds upon the seminal work of Saeed and Parayno (1993), incorporates three heterogeneous banks, a central government and a rating agency. Further, the banks and the central government are assumed to be boundedly rational and backward looking interacting via both the local and international capital markets. The model is calibrated to conform to time-series data of Jamaicas debt-deficit dynamics and banking system performance between FY 1997/8 and FY 2003/4 and then used to perform a set of counterfactual exercises based on the impact of exogenous hypothetical shocks to the Jamaican economy four years prior to the onset of recent the global financial crisis. Accordingly, the paper proposes an early warning system for the vulnerability of banking institutions to a default on public debt. Scenario analyses, conducted using the framework, suggests that significant shocks to net international reserves and exports in 2004 would catalyze a significant fall-out of the banking sector in the near to medium term, with the country being more vulnerable to shocks to net international reserves. We close with some implications for prudential regulation.
Industrial companies increasingly rely on services to stand out from the crowd. Alongside direct strategic and economic advantages, these industrial services can also provide impulses for the further development of the producer´s good. Likewise, modifications of the material product may lead to new or advanced service offers. Hence, product modifications may lead to service adaptations, which again lead to product enhancements. Consequently, product and service innovations seem to interact, driving a dynamic loop and accelerating the innovation activities of a company. This article analyzes the causes by means of a literature review. Afterwards a system dynamics model is constructed to describe the assumed interaction system of product and service innovations in industrial companies and show first consequences resulting from this dynamic loop. Finally, the impacts of some drivers are tested, to give some insights into the behavior of this system.
We will introduce a new system dynamic modelling and simulation environment based on open source components. The development was initiated by a group of active system dynamics modellers who had needs and ideas for an open toolset. The new needs for features like hierarchical modules, module libraries, collaborative model development and efficient model communication in system dynamics together with the development of open source modelling framework Simantics and simulation environment OpenModelica have driven us to start developing an open source modelling and simulation software for system dynamics. In this paper we discuss how current open source components can be used to build a comprehensive tool for system dynamics modelling and what impact open source could have on system dynamics modelling. Even though the development is still on its early stages, the open source components have enabled us to rapidly develop a tool capable of hierarchical modelling, simulation and some basic result and model analysis. When using open source, the modelling software becomes more affordable and distribution of models becomes easier, modelling software can be adapted to individual needs and models can be used and validated by all stakeholders.
In Korea, presidential pardons for traffic violations have been carried out almost every three years, starting from 1995. Whenever Presidents announced pardons for traffic violators, they repeatedly emphasized justifiable reasons that drivers under administrative ruling should be given another chance to make a living by driving. Nonetheless, whenever Presidents issued pardons towards violators of traffic offenses, they were not free from a series of criticism or blame. In fact, the pardons were controversial from the outset.
This paper provides the CSI (cloud computing, smart devices, and the Internet of things) system dynamics model to simulate the future trend in the fields of education, health care, and smart work system. The simulations focus on the policy strategies for success in each field. In addition, this study has a unique meaning in terms of system dynamics modeling approach. A new attempt to build an archetype model for applying to different policy fields was adopted as a new trial.
The objective of the study is to conduct an exploratory study of the causes that constitute to skilled labor shortage in Norway. Subsequently, we formulate policy to increase skilled labor supply. We apply system dynamics methodology to model the causal relationship between individuals motivation to tertiary education participation, from wages and job opportunity perspective. From the simulation, we find that if tertiary education participation persists as it is, skilled labor shortage will increase from 40,000 in 1994 to 190,000 skilled laborers in 2050, which accounts for 11% of the total skilled labor force. With the introduction of voluntary-based internship program into current tertiary curriculum, promotion of online tertiary education, and encouragement of more foreign tertiary students to study in the country, total university students in 2050 will be 1.30% higher, domestic skilled labor force will be lifted 2.5%, and skilled labor shortage will be reduced by 35%.
The Health Systems Design Laboratory applied progressively more complex concept models to help elicit expert knowledge from medical professionals leadership at a population health agency (PHA) as part of a study of medical professional capacity planning over a 20-year horizon. In this paper we document the knowledge elicitation process employed with PHA managers and medical professionals in two half-day sessions in which we introduced first principles of System Dynamics methodology and applied those in progressively more complex concept models. We observe that our working group, made up of persons with widely divergent levels of experience with complicated models and systems thinking consultations, quickly learned iconography and terminology of system dynamics and contributed to the development of dynamic hypotheses.
Prior exploration is an instructional strategy which has improved performance and knowledge acquisition in system-dynamics based learning environments, but only to a limited degree. This study investigates whether model transparency, showing users the internal structure of models, can extend the prior exploration strategy and improve learning even more. In an experimental study, participants in a web-based simulation learned about and managed a small developing nation. All participants were provided the prior exploration strategy but only half received prior exploration embedded in a structure-behavior diagram intended to make the underlying models structure more transparent. Participants provided with the more transparent strategy demonstrated better knowledge acquisition of the underlying model on an objective measure (multiple-choice posttest) but no difference on a subjective measure (open-ended verbal protocols based on short essay questions). Furthermore, their performance (managing the nation) was the equivalent to those in the less transparent condition. Combined with our previous studies, the results suggest that while prior exploration is a beneficial strategy for both performance and knowledge acquisition, making the model structure transparent in this way (with structure-behavior diagrams) is more limited in its effect and may depend on the participants level of expertise.
When evaluating the effectiveness of interactive learning environments it is important to include measures of knowledge acquisition that complement measures of performance. In this paper we report on participants knowledge acquisition in a dynamic decision making task where participants learned about and managed a small developing nation. In the course of the experiment participants not only had to make decisions but also answer multiple-choice questions and short essay questions. The results suggest that participants had a fairly good understanding of the reinforcing nature of national development processes and of processes that are in close causal proximity to their decisions. On the other hand, participants largely failed to recognize nonlinearities, the existence of the outflows to stocks and the proper treatment of delays with different durations. Knowledge acquisition was facilitated by the intensity of participants exploration activities during a simulation-based, guided exploration phase between reading textual instructions and making actual, simulation-based decisions.
Over the past two decades, Calgary a midwestern Canadian City of approximately 1 million inhabitants has experienced periods of rapid resource-driven economic growth and attendant municipal growing pains interspersed with periods of relative stasis. Effective municipal financial planning in this environment imposes profound challenges, particularly due to the presence of feedbacks, delays, non-linearities. To facilitate improved municipal financial planning, the City of Calgary has constructed the detailed multi-sectoral Calgary Impact Assessment Model (CIAM). CIAM whose structure draws inspiration from previous peer reviewed models includes an articulated representation of population demographics, migration, the labor market, the domestic and commercial property market and taxes thereon, infrastructure, finances, and the budget, recreational land, service levels, and quality of life. CIAM was parameterized using data from City databases and reports. Model construction incorporated a variety of best practices, and underwent a through a rigorous peer review. CIAM was subsequently calibrated to dozens of time series, leading to further model structural refinement and parameter estimation; the resulting model reproduces quite well a wide variety of historical municipal dynamics. CIAM has been used to investigate several scenarios important for municipal financial planning, and offers the potential to serve as an important decision-making tool for future city financial planning.
Almost everything we use today is manufactured by a virtual enterprise composed of hundreds of companies. These large distributed systems have led to numerous problems and challenges across multiple industries. The need is great for an analytical technique to examine the performance of a large-scale virtual enterprise. System Dynamics has been successfully used to model these large enterprises and assess the impacts on system behavior of changes in demand and various parameters. These large-scale enterprise models, however, are complex and time consuming to build and are difficult to restructure. For enterprise management, the ability to reconfigure the network of companies in response to external forces is critical, and models of the enterprise must have similar flexibility and rapid re-configurability. Using System Dynamics agent models of factories, distribution centers and customers, scmBLOX uses drag and drop features that enable fast construction of enterprise models and rapid assessments of alternative enterprise structures. Replacement of a make-to-stock factory for a make-to-order factory or the addition or elimination of distribution centers can be quickly evaluated. On-going research is focusing on the interplay between enterprise structure and performance, the development of additional agent models and new features for current agent models, and the assessment of optimization strategies such as push-pull boundaries within the global virtual enterprise.
A number of papers have been published describing various pedagogic techniques for the dissemination of the System Dynamics (SD) approach at various Education institutions and academic levels ranging from schools (K-12 in the US) to higher education. This paper builds on previous papers by this author that provided a catalogue and classification of this work in order to highlight potential areas of research in this field of study and to identify system archetypes at different hierarchical levels and discover new ones. The findings from these investigations are briefly described.
A number of papers have been published describing various System Dynamics (SD) models of various Education institutions and issues, on topics including the role of SD in Corporate Governance, Planning, Resourcing & Budgeting, Teaching Quality, Teaching Practice, Microworlds and Enrolment Demand. This paper builds on previous papers by this author that provided a catalogue and classification of this work in order to highlight potential areas of research in this field of study and to identify system archetypes at different hierarchical levels and discover new ones. The findings from these investigations are briefly described.
Complex adaptive systems-of-systems are inherently multi-scale across several dimensions, including temporal, geographical, and organizational. We present a multi-model paradigm integrating a localized community-scale individual-based model (IBM) with a population scale system dynamics (SD) model to analyze long term results of potential policy interventions for obesity prevention. The IBM uses virtual agents embedded in a social network to simulate the spread of opinions relating to nutrition and physical activity (N&PA) behaviors such as dieting and exercise, and the effects of these opinions on individual behaviors. The network structure uses a mixture of scale-free and uniformly random connections to represent a social network of relationships and interactions within a local community. The N&PA related health behaviors of individuals change dynamically relative to endogenous influences within their social network and exogenous influences from industry-based advertising and public health-related educational policies. The outputs of the IBM, seen as changes in obesogenic (N&PA unhealthy) behavior prevalences, can be used as inputs to a SD model to calculate the resulting changes in mortality and morbidity over the ensuing decades. We analyze and compare effects of possible policy interventions, and illustrate a policy cocktail that addresses multiple aspects of the obesity problem, resulting in amplification of desirable results and a strong uncertainty reduction.
In order to cope with the vast range of ambiguous, multi-causal and multi-faceted potential causes for firm success, managers tend to look for critical success factors as a reduced number of essential factors that determine future business success. Although scholars have been serving this need for more than four decades, the insights derived from empirical research on critical success factors have low impact on strategy in practice. We take this phenomenon to discuss potential causes and propose to complement empirical methods with the dynamic feedback perspective of System Dynamics modeling.
A dynamic model of maintenance services is presented in this paper. The focus is on the service (i.e. value co-creation) perspective and the main purpose of the model is to facilitate the understanding of the added value of services. Determining the monetary value of services is important since the pricing of services is based on the value rather than on the cost. The modeled services vary by their complexity and their effects on the system. The model was built to be a communication tool for customer and the service provider to enable shared understanding of the system and the effects of different collaborative services.
In the aftermath of the expansive fiscal policy stimuli dealing with the consequences of the world financial crisis of 2007/2008 the public indebtedness around the world has increased dramatically. As a consequence the world-wide interest in policy measures to limit and reduce public debt has increased drastically. In Germany the parliament has altered the constitution which encompasses now a new article regarding a seemingly tight debt rule. In many member states of the EU and around a political discussion has started whether the German debt rule could serve as a guideline. This article explains the German rule and analyses its effects by employing system dynamics methods. The mainly qualitative analysis demonstrates that the German debt rule has important shortcomings and that there are severe side effects which have to be addressed by public policy.
The overall objective of this work is to improve the holistic value of energy development strategies by integrating management criteria for water availability, water quality, and ecosystem health into the energy system planning process. The Snake River Basin (SRB) in southern Idaho is used as a case study to show options for improving full economic utilization of aquatic resources given multiple scenarios such as changing climate, additional regulations, and increasing population. Through the incorporation of multiple management criteria, potential crosscutting solutions to energy and water issues in the SRB can be developed. The final result of this work will be a multi-criteria decision support tool usable by policy makers and researchers alike that will give insight into the behavior of the management criteria over time and will allow the user to experiment with a range of potential solutions. Because several basins in the arid west are dealing with similar water, energy, and ecosystem issues, the tool and conclusions will be transferrable to a wide range of locations and applications. This is a very large project to be completed in phases. This paper deals with interactions between the hydrologic system and water use at a basin level. Future work will include the interdependency between energy use and water use in these systems.
In this paper we demonstrate how the Major League Baseball (MLB) free agent compensation system (FA-CS), intended to achieve parity across MLB teams, has the unintended and adverse consequence of increasing inequality. The FA-CS compensates teams that release a Type A Free Agent by giving them a compensation pick the highest draft pick from the team that signs the free agent. The cost of each lost pick decreases as teams sign multiple Free Agents. This characteristic lowers the cost per Free Agents, when multiple Free Agents are signed. However, such benefits are solely accessible to teams that are relatively resource unconstrained, giving rise to an inequality-increasing positive feedback. To explore the importance of the FA-CS positive feedback, we develop a dynamic model of the flow of Type A Free Agents through their MLB career, including their maturation from draft picks, to minor league, to major league, to free agency, and finally to retirement. Additionally, we model teams free agent hiring process to understand free agent dispersion within the league. Isolating the FA-CS feedback from other scale effects and calibrating the model to MLB data we estimate the strength of this adverse inequality-increasing effect.
Throughout history some societies, including the Maya, Anazi and Easter Island, have collapsed, while others facing similar challenges, such as New Guinea and Japan, have succeeded. The Maya and New Guinea cases were taken from Jared Diamond's study, "Collapse," to create a system dynamics model capable of producing both the collapse and success behavior. The endogenous pressures described by Diamond were used to develop the feedback story. Policy interventions undertaken in by the society in the model were controlling family size, increasing farming intensity, reducing resource usage and composting. In the initial attempt the society enacted these interventions in response the cues of food shortages, perceived environmental degradation and falling crop yields (an indicator of soil quality). However, this version of the model was incapable of creating the success behavior mode, ruling out these cues as ones successful societies could have used. In version two, the society used a target land fraction occupied as its main cue and the gap between needed food production per acre and actual food production per acre as the drive to increase composting. This version was able to produce success behavior, which establishes these cues as possible cues a successful society could have used.
Global climate change is affecting the rain-runoff process around the world since pre-climate change normal rain patterns are giving way to short periods of strong precipitation, followed by long periods without rain. In addition, temperature and evaporation are expected to increase about 20% over the next 20 years. The State of Guanajuato in Central Mexico utilizes 87% of all available water for agricultural production and is extremely concerned about the impacts of climate change on water supply and demand for its various uses in the short and medium term. To explore the future impacts of climate change in Guanajuato a two-component approach was developed: (1) an atmospheric interface that generates synthetic precipitation, temperature and evaporation time series; and simulates the characteristics of these three meteorological variables and (2) a system dynamics model that beginning with the rain-runoff process generates time related behavior for natural and man-made process for each of 13 watershed that make up the States geography. Base Line and Climate Change scenarios have been generated from the present through 2030 to examine the impacts that this phenomenon is having on each watershed; recommendations have been drawn to assist these areas in adapting to new climate conditions.
In this paper we present our concept and prototype of a web platform which supports participatory modelling. This platform facilitates web-based collaborative and cumulative modelling when face-to-face participatory modelling sessions cannot be organized as often as desired. Successive iteration steps of the model development can thus be displayed interactively in a standard web browser together with comments and explanations made by the modeller. The platform strengthens the support of formal model construction and documentation on the one hand and reduces the effort of model re-publishing on the other hand. This platform shall be used to support participatory modelling and decision-making processes in the field of sustainable development and in many other fields.
Shared capitalism is a set of compensation practices (e.g., employee ownership, stock options, and profit sharing) through which worker pay, or wealth, depends on the performance of the firm or work group. Empirical studies on whether employee ownership improves firm performance, while predominately positive, offer mixed results. This paper addresses the question: under what conditions do shared capitalism policies improve firm performance? A system dynamics model of high performance work systems estimated using the NBER Shared Capitalism dataset and calibrated to a clean technology startup company is presented. The model posits explicit causal mechanisms to explain how various shared capitalism policies and human resource practices influence employee behaviors that drive business processes, and how those business processes interact with market conditions to generate firm performance. Simulation analyses demonstrate that employee ownership and profit sharing create and mediate the strength of multiple reinforcing feedbacks linking firm performance and employee behavior. The more wealth is shared through broad-based employee ownership, the more wealth is created, given the appropriate conditions. Policy analysis suggests how mutual gains for owners and employees can be attained through a balance of salary, stock grants and other shared capitalism policies.
This poster summarizes a project designed to explore the complex social system that influences households decision to use banks and other financial institutions. The dynamic hypothesis was that the number of unbanked and under banked African-Americans in the region was due to a complex interaction of individual behaviors, banking policies and practices, and those of the payday lending industry. The project was designed to develop a grounded theory describing households experiences related to financial institutions and how financial decisions based on previous experiences impacted their household economic security. Group model building methods were used to gather insights from banks, alternative financial institutions, and community residents.
The HealthBound game (available online at http://www.cdc.gov/HealthBound) was developed in 2008-09 under the auspices of the US Centers for Disease Control and Prevention, and was described in a plenary talk at ISDC 2009 in Albuquerque. The underlying SD model is the most integrative tool available anywhere for national health policy analysis, and presents the challenge of balancing different types of policies in order to effectively improve population health, lower costs, and achieve greater equity. This workshop starts with introduction to the model and the game, followed by an extended opportunity for small teams to experiment and play the game at their laptops, and concluding with discussion of results and their implications.
Dental caries in primary teeth of children 5 years of age or younger is one of the major health problems in the United States, especially for low-income children. This paper presents a framework for assessing the impact of various programs designed to reduce the prevalence and consequences of Early Childhood Caries. The paper describes a System Dynamics simulation model of the population of children 0-5 years old in Colorado. Results of simulations with a number of individual interventions and combined strategies are presented and program costs and savings in treatment costs are compared.
The economy is studied at all scales, from micro to macro. With global trends toward rapid urbanization, one abstracted scale of the economy will become increasingly important to understand, that of a city economy. Working in close cooperation with the urban planning staff of a US city, the authors developed a system dynamics model of a city as a complex, adaptive, system of system. The economy sector of the model is distinguished by its incorporation of the citys highly porous boundaries and unification of multiple definitional approaches to the key measure of City Gross Domestic Product. The result is a system thinking tool for policy makers to explore the relationships between citywide, policy-initiated changes and the structurally determined performance of the city economy.
The purpose of the paper is to test whether people make different decisions when a task requires either a fixed delay or a continuous delay conceptualisation. With the help of a structurally simple dynamic decision making task, we test two conditions in a controlled experiment: hiring when personnel stays in an organisation for exactly ten years (fixed delay condition) or when personnel stays on average for ten years (continuous delay condition). In this preliminary study, 71 participants were tested. Findings so far show no differences in performance between the groups, indicating that they most likely use the same cognitive representation of the task. Since participants answers are substantially closer to the fixed delay condition, we assume that people have the tendency to conceptualise lags in the form of discrete delays, at least in the context of personnel hiring. Research implications comprise the repetition of the experiment to achieve a higher number of participants and to allow for a more extreme differentiation between the two conditions. Practical implications regard the formulation of decision making tasks within organisations, for instance in human resource management. The value of this paper lies in its rigorous usage of a structurally simple dynamic task to shed light on a fundamental trait of human decision making.
To better understand the performance of hospital operations in response to IT-enabled improvement, we report the results of a system dynamics model designed to improve core medical processes. Utilizing system dynamics modeling and emerging Health Information Systems (HIS) data, we demonstrate how current behavior within the hospital leads to a stove-pipe effect, in which each functional group employs policies that are rational at the group level, but that lead to inefficiencies at the hospital level. We recommend management improvements in both materials and staff utilization to address the stove-pipe effect, estimate the resultant cost-saving, and report the results of a new experiment conducted in the hospital to validate our approach. We believe that the major gains in health information systems use will accompany new information gathering capabilities, as these capabilities result in collections of data that can be used to greatly improve patient safety, hospital operations, and medical decision support.
After announcing the fuel rationing policy in 2008, government decided to eliminate subsidies in order to manage consumption of natural resources. Thus, a cashing subsidy policy has been applied since end of 2010. In first stage, different kinds of energy and resources like water were considered. Government's plan was to pay subsidies directly to consumers.
We began to develop an agent-based epidemiological model of animal disease propagation within the beef and dairy industries. Model development was done in context of a consortium of interested parties including the New Mexico State University (NMSU) Extension Service, the New Mexico Livestock Board (NMLB), ranchers representing the beef industry, and farmers representing the dairy industry. The model required a thorough understanding of the life cycles for commodity livestock, especially the transportation and mixing that occurs as part-and-parcel of how production and commerce is practiced. Once this detailed network of animal movement and interaction is articulated within the model, we can simulate the introduction of disease at any given location and track its propagation. The model will serve to understand how inter-operation transfer of livestock can impact the likelihood and magnitude of infectious disease outbreaks. With this understanding, the cost-effectiveness of current and proposed prevention and monitoring strategies, as well as mitigation strategies, can be assessed. Our first focus for model application may be the propagation of bovine tuberculosis (TB) in beef cattle. In subsequent work, we would like to expand the computational model to include dairy cattle, and to consider the propagation of other diseases such as foot-and-mouth disease (FMD) and Rift Valley fever.
Physicians are far from optimal decision makers: they overuse defensive medical practices such as medical tests (bias), and they disagree on their diagnoses and treatments (practice variation). Besides the regional factors (such as culture), at the individual level, the most common explanations for these phenomena are linked to physicians personality traits (e.g., risk aversion) or their financial incentives. We develop a theory that offers a new explanation. With the help of a simulation model, we show that practice variation and bias does not have to be caused by personality traits and financial incentives, but can endogenously emerge through daily practices and outcome learning even for physicians with similar trainings working in the same region. Specifically, a physicians exposure to outcome feedback and her accumulated experience and skill contribute to variation and bias. A preliminary validation is achieved by comparing simulation results with the data from c-section surgery in the states of New York and Florida.
Nearly 3 billion people around the world use solid biomass, such as fuelwood and crop waste, for cooking and heating. The implementation of biogas, liquid petroleum gas, solar and other alternative energy cookstoves presents an opportunity to alleviate the burden of fuelwood collection and the health implications associated with inefficient biomass combustion while mitigating the negative ecological and climate effects of deforestation. Many governments and international development agencies have initiated programs to distribute alternative energy cookstoves, but the new technologies rarely achieve sustained use with consumers. While funds have been widely distributed to research the technical design of cookstove technologies, very little systematic research has been done to understand and improve implementation and use of the technologies in the complex markets they target.
Modeling Dynamics Systems: Lessons for a First Course (third edition) provides a set of materials that enable educators at the secondary and college levels to teach a one-semester or one-year course in System Dynamics modeling. These lessons are also useful for trainers in a business environment. Developed for beginning modelers, the lessons contained in this book can be used for a core curriculum or for independent study. The lessons include some of the classic System Dynamics problems (population change, resource sustainability, drug pharmacokinetics, spread of an epidemic, urban growth, supply and demand, and more). Feedback analysis is integral to the lessons. Guidelines for an independent project and an outline for a technical paper explaining the creation process and structure of the final model, together with scoring guides for both the model and the paper, are included. Participants in the workshop will have a chance to build some simple models (participants should bring laptops) and gain a sense of the progression leading to a more sophisticated model. Student work will be demonstrated and can also be viewed at www.ccmodelingsystems.com. New materials in the third edition (oscillations, transfer of loop dominance, mapping systems in the news, ) of this book will be presented.
This paper describes work in progress on Houdini: a system dynamics model of the Dutch housing market focused on explaining institutional structures leading to high price increases and obstructing new supply and on
This paper presents an application of system dynamics to understand the behavior of the AH-64 Advanced Aircraft Course at the U.S. Army Aviation Center of Excellence. This course trains Army lieutenants and warrant officers as combat aviators. In the last several years, a large bubble of students awaiting the different phases of training has developed because of organizational and process problems within the course. This paper presents a system dynamics model of the course and recommends policy changes to eliminate the backlog of students awaiting training. The model incorporates both the organizational aspects of the course, including personnel and equipment; as well as the processes within the course. Base on output from the system dynamics model, the best course of action for the U.S. Army Aviation Center of Excellence is to add additional days to the course to account for weather and increase the number of hours available for training on a daily basis. This policy enables the center to eliminate the bubble of students and stabilize the process of training combat aviators.
From June through October 2008 the National Guard Bureau (NGB)J8 conducted a capability based assessment (CBA) to determine National Guard (NG) capability gaps for Defense Support to Civil Authorities (DSCA). A major DCSA mission that the NGB Capability Assessment and Development Process (CADP) focused on was Chemical, Biological, Radiological, Nuclear, and high-Explosive Consequence Management (CBRNE CM) response. As expected, the most difficult portion of the CBA was defining and quantifying the gap in NG specialized CBRNE CM capabilities (CERFPs). Initially, NGB developed a simple allocation model that captured the total number of CERFPs employed based on subject matter expertise. However, NGB-J8 developed a more objectively quantifiable model that would systemically document and consistently apply assumptions. Repeatability was essential to defining and quantifying NGB CBRNE CM capability gaps. NGB-J8 determined a System Dynamics Model would be the best approach for developing this model.
Automated sensitivity analysis approaches in system dynamics focus primarily on model parameters. Although table functions are often subjectively approximated, they do not form the focus of most sensitivity analyses. Recently, a promising approach that allows automation of sensitivity analysis on functions was proposed by Hearne (2010), but the applicability of this method to system dynamics table functions has not been studied, yet. In this study, the new method is applied to a simple system dynamics model. In the light of the observations a number of shortcomings are identified and a set of extensions to address these are proposed and then tested. The results of experiments with the original and the extended method demonstrate that the method can be used easily and efficiently for table functions. The extensions are shown to be valuable in creating a more comprehensive method, but they also raise the research issue of the trade-off between their added value and the cost of dealing with increased complication. Apart from our experimental results, the article also puts forth a set of directions along which the approach can be improved further. Despite the issues requiring further research, the method holds promise for routine implementation.
How can simulation be sold to policy decision makers? How can simulation be sold to other social scientists that do not accept simulation as a complement to accepted techniques (Repenning, 2003)?
Simulation provides a means to gain insight into the past behaviour and future trajectories of complex social systems. The simulation process is one of discovery: individual mental models are communicated, formalised, and simulated under a range of scenarios. There are two main approaches to social simulation: system dynamics, centred on the feedback perspective, and agent based computational modelling, which uses the individual and their interactions as the basic building block. This short paper describes a new simulation tool that can accommodate both perspectives, and where all model building is achieved using an equation-based approach. The system design is summarised and an example based on the SIR model is described.
Social-ecological resilience is an increasingly central paradigm for understanding sustainable resource management. While previous works on resilience have observed that sudden shocks or gradual stressors may force a system over a critical threshold, natural variations may have similar results. This paper aims to better understand the effect of environmental variability on the resilience of fishery systems, and the important role that social institutions play. To explore these issues, we build a System Dynamics Model of the mollusc fishery of the indigenous Seri people in the Gulf of California, Mexico. This model includes the dynamics of the two dominant species of penn shell in the fishery (Atrina tuberculosa and Pinna rugosa), several institutional rules that the Seri use, and a number of key stochastic variables derived from empirical data. We find that modeling with multiple species, rather than the standard one-species model, uncovers more resilience in the system. However, while we expected stochasticity to be detrimental to resilience, we find that endogenous environmental variability can also increase resilience. We examine possible reasons for this finding, and discuss additional insights our study revealed about managing multiple-species artisanal fisheries.
Maize is widely grown in Africa including in drier areas where alternate crops will often perform better. Although maize will fail in drought years, it produces substantially higher yields than alternates, like sorghum and millet, in wet years. Although people tend to select which crops to grow based on recent experience with crop harvests and market prices, there is a widespread preference for maize even in areas where planting it is risky. This can lead to crop failures when rainfall varies from year to year. Introduction of higher yielding maize varieties might, under some conditions, cause increases in food shortages by further incentivizing the planting of maize in inappropriate situations. A preliminary model helps to investigate this and related issues.