The method presented in this paper allows for an investigation of how the eigenvalues characterizing the model behavior is created from the underlying model structure and how this behavior feeds back to change instantaneously the relative significance of the model structure. The method also allows us to identify the relative significance of the various parameters that governs the gains of the links and loops of the model. The method has been implemented using Matlab software for the purpose of facilitating an eigenvalue analysis of system dynamic models. This work is based on control theory as well as the previous work on eigenvalue analysis in system dynamics. It summarizes the thesis work by Ahmed AbdelTawab AbdelGawad (2004) and Bahaa E. Aly Abdel-Aleem (2004), under the supervision of Mohamed Saleh and Pål I. Davidsen. The method outlined and Matlab code developed in preparation for this paper may be implemented as part of any simulation package.
The purpose of this research was to assess the Egyptian software industry using a Systems Dynamics approach based on the Software Export Success Factors Model developed by Heeks and Nicholson, 2002. A CLD was prepared as a step towards building a model to simulate the expected effect of key software-related infrastructure variables on the Egyptian software export revenue. Simulations of software export industry over a period of 10 years point to the following: (1) Injecting an additional 30% financial resources resulted in an increase of 8.4% in software export revenue and 2.1% in job opportunities with respect to the reference mode, (2) Improving IT staff productivity by 42%, and delivered software quality by 10%, with a decrease in resistance to change of 20% led to an increase of 68.7% in software export revenue and of 12.9% in job opportunities with respect to the reference mode, (3) Enhancing R&D by 50% and IT staff innovation contribution by 10% resulted in an increase of 14.4% in software export revenue and 3% in job opportunities with respect to the reference mode, and (4) Improving the software export promotion efficiency by 14% and quality of delivered software by 10% led to an increase of 38.7% in software export revenue and 8% in job opportunities with respect to the reference mode.
The paper addresses the question whether a modular organizational structure breeds mechanisms that promote proactive strategic flexibility. We examine this question from the perspective of the cognitive school of strategic management and with the aid of system dynamics modeling and simulation to explore long-term dynamic effects. Both our analysis and our experiments with the model suggest that modular organizations do not necessarily encourage the construction of managers mental models with a capability to generate more strategic options and, thus, do not promote strategic flexibility at a higher degree compared to more traditional organizational structures.
The glucose regulatory system in man is a complex system. It is a nonlinear, multiloop, self-regulatory feedback system which exhibits behavior which is often counter-intuitive and which is insensitive to many external interference. The challenge in this work is to employ a model that is simple, but not too simple for the students of first medical year with the purpose to help them understand the glucose regulatory system in the human being body by quasi-practical approach based on simulation tool and not my theoretical understanding. This model describes the carbohydrate metabolism, digestion, absorption and fate of intake carbohydrates. The model attempts to reflect the underlying (patho) physiology of insulin action and carbohydrate absorption in quantitative terms such as insulin sensitivity, volume of glucose and insulin distribution and maximal rate of gastric emptying. The model represents the integration of two existing models proposed earlier by Foster et al. (1970) and Lehmann et al. (1992).
Despite the fact that much of recent terror is ethnically based, little attention has been paid to systematically explaining ethnic violence. We build on the work done by the Minorities at Risk Project (MAR) to the issue of ethnic terror using systems dynamics. While there has been important work done using MAR to explore ethnic violence as a base using statistics and qualitative analysis (Gurr 2000) there has been little work exploring ethnic terrorism specifically and none that has exploited systems dynamics as an analytical tool. The application of a systems dynamics approach will help us go beyond some of the limitations of statistical analysis to explore how government policy and ethnonationalist terrorism feed of each other in a cycle of violence, discrimination and repression. This work has three broad goals. First, it is targeted at understanding the causes of ethnic terror and second examining the way the relation between the ethnic policies of governments and the behavior of ethnic groups - particularly their choice to use or not use terrorism relate systematically. Third, this work sees to apply for the first time the tools of systems dynamics to political violence.
Evaluating new bank loans has been considered as one of the main dilemmas that banks managers have to deal with in order to reduce the probability of default. The lending process is a series of activities involving two main parties whose association ranges from the loan application to the successful or unsuccessful repayment of the loan. This paper describes the construction of a flight simulator which uses the ideas of System Dynamics and the Viable Systems Methodology. The Decision Support Tool thus formed uses systemic approaches to measure a firms performance and can provide a risk assessment in the sense of evaluating performance under different (what- if) scenarios. The credit worthiness from this model can then be evaluated against the usual estimate based only on financial ratios.
Prices in the Property and Casualty Reinsurance market are known to undergo significant fluctuations. In order to understand the reasons for these fluctuations a simulation model was built that replicates relevant features of the reinsurance market: a limited number of market participants are competing, low product differentiation, volume constraints for each market participant and discrete volume decisions based on estimated rather than actual market prices. Despite a number of simplifications the model captures the current market dynamics. In a further development the model was made interactive allowing actual players to take the role of the reinsurance companies and make the individual volume decisions based on current financials and the market history.
The model was built using agent based instead of system dynamics modeling techniques particularly to simplify implementation of critical discrete events and to create a simple to understand structure.
We will discuss the model, the trade-offs between the Agent-based and System-dynamics approach as they applied to this model and share some experience in communicating the model structure with the business owners.
Demand Conditioning is one of the methods used to address imbalances between supply and demand in supply chains. This requires the manufacturer to adjust the demand plan to respond to supply issues. The supply chain has several sources of delays and uncertainties such as lead times at different stages, forecast error, supply yield variability etc. that could potentially trigger or influence the conditioning process. In this paper, we examine dynamical effects in the conditioning process to study potential instabilities. We developed a Systems Dynamics model of a PC manufacturing supply chain to examine instabilities in the supply chain. This model provides insight on supply chain risks and error propagation due to unsynchronized execution. We also use the model to study the effect of different countermeasures to stabilize the supply chain.
A key determinant of any groups performance in such contexts as varied as product development, consulting, and craft manufacturing is its transactive memory system (TMS): that is, its shared, tacit memory system for managing and communicating information relevant to the group. Using the methodology of system dynamics, we model the relationship between TMS and productivity by leveraging the theory of learning-by-doing at both the group and individual levels. We also incorporate into the model the concepts of group forgetting, in which employee turnover reduces group knowledge. We also include the effects of specialization, overspecialization, and knowledge obsolescence. We then simulate the impact of each of these refinements and perform sensitivity analyses on them. Finally, we discuss several implications of this model for future research. One implication is that representing group learning processes by a single, traditional, power-law learning curve may be in many cases inadequate. Another is that the very development of a TMS may create excessive individual specialization that is detrimental to future productivity levels.
This paper examines results on a series of Cournot markets with groups of five seller subjects. Step by step, we add complexity (and realism) to the simplest market and test the effects on behavior in an accompanying laboratory experiment. Consistent with previous experiments and the rational expectations hypothesis, price behavior was explained with Cournot Nash equilibrium with biases towards competitive prices. When complexity is increased, there rationality is degraded and lead to a salient cyclical tendency. Indications of cyclical behavior were induced by the application of spectral analysis and autocorrelation. We found that the more problematic effect of complexity in market behavior is the extra delay rather than accumulations. We proposed a heuristic based on the bounded rationality theory, but the tests were not satisfactory.
An Adaptive Expectations Approach to the Mechanisms of Transmission Model of the Central Bank of Colombia
Fernando Arenas Pontificia Universidad Javeriana
Franz Hamann Banco de la República
ABSTRACT
Looking for the potential applications of system dynamics in macroeconomic modeling at the Central Bank of Colombia, the Mechanisms of Transmission Model (MTM) was recast in a system dynamics model. The forward-looking function of the model that, in the case of the MTM is a rational expectations based function, was approached by means of the TREND function. This document describes the system dynamics model and shows comparative impulse-response results between the models, when PULSE and STEP shocks are applied to inflation target, monetary policy, food supply, nominal depreciation rate, and risk premium.
Modelling of technology adoption has tended to be based on individual product diffusion, although traditional models have been extended to incorporate replacement, competition, generations of substitution and other managerial variables such as pricing. A question is: how can these models be broadened to represent service industry applications and generalised or upscaled to model the phenomenon of General Purpose Technologies? GPTs have the properties of pervasiveness and complementary technologies. GPTs suffer from long development delays or start-up problems involving the co-ordination problems of complementary bandwagon behaviour. System dynamics modelling is proposed as an effective industry-level modelling approach to link standard expert judgement market forecasting used in industry and theoretical analysis used by economists in order to provide robust technology management policies. This paper represents an overview of the work-in-progress research themes and a modelling agenda.
The automotive industry is considered as one of the main drivers of todays global economy. The industry spans across the globe, with nearly each country trying to develop the industry and its supply chain within its boundaries. This paper presents a Business Dynamics model that maps the Egyptian Automotive industry, which started as a public industry and then transformed to a market driven private industry. The Egyptian automotive industry focuses on the local Egyptian market, with no current plan for exporting to the global market. Such focus provides the Egyptian automotive industries with challenges that impede its growth. The Business Dynamics model presented in the paper presents an explanation of the current status of the Egyptian Automotive industry. The model is then used to provide insights for the current status of the industry, as well as testing several policy options for stimulating the industrys growth.
In this poster, authors explain a System Dynamics model developed for measuring efficiency of the Small Aircraft Transportation System (SATS) that NASA has been developing to enhance intercity travelers' mobility in the country. The model is comprehensive in the sense that it includes multi-modes such as automobile, commercial airlines and rail. It also considers different types of decision makers such as travelers, airlines, Federal Aviation Administration (FAA) and Federal Rail Administration (FRA) that dynamically interact with each other based on its own interest. The model allows users to change several critical but uncertain parameters such as the price for SATS trip, airports for SATS operations, etc. This feature enables users to do "what-if" type of study. Technically, the model is developed as a stand-alone tool with a Graphical User Interface that encloses all computational procedures written in MALTALB. Socio-economic data and computational results are represented at a county level using the Geographical Information System (GIS).
The Military Roundtable is the arena for sharing ideas and experiences
on the application of System Dynamics to military problems. The list of
topics includes, for example: strategy development; force-on-force
analysis; war-gaming; military decision making; training of military
decision makers; including command-post exercises; preparedness studies;
human resource management; development and management of military
capability; management of materiel acquisition; military logistics
modelling; in-service management. We suggest the following main topic
for this year's meeting: "SDM as a tool to support training and
exercise". Opportunities exist for participants to provide update on
recent research and consulting activities, to discuss opportunities for
the future and challenges that confront those working in or having an
interest in system dynamics modelling (SDM) in military context. We will
continue the work on assembling a compendium of models and readings on
SDM in defence.
The Norwegian Armed Forces used to have a unitary personnel policy. All officers were recruited with prospects of life-long employment. The long time constants in such a system meant that a transformation into a younger corps was almost impossible to achieve. The model-supported intervention significantly reduced the probable risk of failure in policy design and implementation. A number of achievements must be attributed to the model intervention per se. First, the models base case projected a 100% surplus of senior officers. This was an eye-opener. Moreover, the lack of suitable options within the current policy regime became obvious. Finally, the suitability of the new policy was convincingly presented and its implementation success virtually secured. The success of the model intervention is discussed. Though the most aggregated model sufficed analytically, the existence of a more detailed model that reflected the production system, crucially enhanced the analysis face validity, especially as a cost analysis was called for. However, more critical than the models transparency was that the results fell within the comfort zone of most key stakeholders. The results challenged intuitions enough so that the model was considered invaluable, but not so much so as to question the approach.
Natural gas for automotive purposes is an appealing alternative: curbing local and global pollution and dependence on foreign oil are among the most remarkable advantages. The other side of the coin implies building and maintaining an on purpose network entailing financial requirements. The final aim of this work is to compare its advantages with economic rationale.
A system dynamics model is built and taken as reference for all quantitative assertions. It contains data referring to two scenarios: business as usual versus expansion. The model treats separately global and local emissions and infrastructure needs. Quantitative results are the basis for the final assessment, that is grounded on the externalities theory. By analyzing the scenarios gap numerous remarks follow.
Regarding global emissions, beneficial effects seem modest. Local emissions would either decrease or not vary depending on the pollutant. Avoided externalities estimates exceed infrastructure financial requirements. Natural gas is a suitable answer in tackling some issues related to the road transport industry.
System Dynamics (SD) is a special type of simulation modeling where
output validity refers to validating the patterns of dynamic behaviors, such
as oscillations, growth or decline. The developers and users of these
models (the decision makers and people affected by decisions based on
such models) are all rightly concerned with whether a model and its
results are valid. Structural model validity and validation have long been
recognized as one of the main issues in system dynamics. This concern
is addressed through pattern recognition and testing in this paper.
Another issue in dynamic simulation methodology is parameter
calibration; assuming that the structure of simulation model constructed
by the user is valid. Parameter calibration is the minimization of an error
function which is a measure of the correspondence between numerically
calculated output patterns and the respective real behavior patterns. We
offer a software that does automated parameter calibration with respect to
a given (desired) dynamic pattern. This particular feature can also be
used in policy improvement design.
Our objective is to conduct simulations with economic environmental model. We list the important and causal relationships among the levels and trace the feedback loop structures. In describing an economic and environmental model we focus on the relations among income, consumption, emission, and damage. This paper yields insight into maximization of welfare. Next, we present the simulation runs of the model, conducted with the help of existing system dynamics modeling tools.
The importance of management flight simulators for learning has been already tested and documented. Single player simulation games are usually utilised, but a multiplayer simulation game adds direct competition to the existing problems (delays, nonlinearities and feedbacks). An asymmetric game also introduces bounded rationality and the dynamics of the information flow within the team. A network team game finally allows for the analysis of cooperation dynamics (by letting the users play against each other: against an unpredictable competitor, with no pre-defined strategy). This paper presents an asymmetric multiplayer network game that is considered to be easy to play and understand. The main advantage of the ILE here introduced is the facilitation of the analysis of: learning and decision making processes, cooperation and competition dynamics.
Project-based professional service organisations supply their services as tailored or one-off projects for specific clients. The particular form of their organisation, the character of their relationships with their clients necessary to deliver highly customised projects and the non-routine, creative nature of the work come together in a way which makes the management of these service firms particularly demanding. A common challenge is fluctuation in the workload. While this is partly influenced by changes in demand, the external environment does not provide a comprehensive explanation and the interaction between business processes and project processes needs to be examined. In providing a generic explanation of the causes of workload fluctuation as well as an assessment of different bidding strategies based on a system dynamics model, this paper aims to help to advance the theoretical understanding of the project-based professional service organisation and ultimately to help to provide tools for its managers.
Recently, an invasive Asian beetle known as the Emerald Ash Borer (EAB) (Agrilus planipennis Coleoptera: Buprestidae) has emerged as a threat to Ash trees in the Midwestern United States and Canada (McCullough and Katovich 2004). Significant infestations in Michigan and nearby areas have all but doomed nearly one billion native ash trees. This paper presents an argument for the establishment of a widely accessible knowledgebase of information on the EABs spread capabilities. We argue that spatial dynamic modeling stands as a flexible and powerful decision support system platform. We present initial simulations of EAB spread scenarios constructed using tree information and land use data collected for DuPage County, IL, an uninfected suburban county in the Chicago metropolitan area. These simulations test policies focused on impeding the costly spread of the beetle. This analysis also presents a framework for further studies assessing the economic impacts on municipalities and counties due to tree removal costs and aesthetic damage. Our work points to human driven movement as the major vector for EAB spread throughout our study area. Here, the focus falls on the ability of state and county implemented firewood quarantines to act as effective policies for slowing EAB spread.
The negligent upkeep of many abandoned industrial sites (brownfields) throughout the twentieth century has had grave impacts on the urban landscape of American and European cities. In recent years, brownfield redevelopment has come to be viewed as a strategy for sustainable land use and urban revitalization. This study assesses the feasibility of the construction of a dynamic simulation model of urban brownfield redevelopment. Literature surrounding brownfield redevelopment is reviewed and used to construct a dynamic hypothesis of brownfield redevelopment as it relates to site liability, economic viability, and availability of redevelopment funding. Finally, an initial system dynamics model of the brownfield redevelopment process is constructed. This quantitative analysis is performed using the 2003 US Conference of Mayors brownfield survey, which serves as a dataset on brownfield distribution and average site size. We conclude with suggestions for the extension of the model to capture spatial feedback in order to assess redevelopment effects on the surrounding matrix of urban land-uses.
The complexity and characteristics of the pharmaceutical firm present an intriguing context for underlying information management issues during clinical trials for new drug development. This paper reports on the evaluation and performance of MIS for information management in clinical trials in new drug development. The main objective of the study is to examine the economic and business impacts of automating that process, to enhance our understanding of informational stakes involved, using a system dynamics (SD) model. The SD method is enriched in this paper with other conceptual frameworks such as Alters (2001) Work Centered Analysis (WCA) and the Balanced Scorecard (BSC) (Kaplan and Norton, 2001). Results of the simulations for alternative sensitivity analyses on errors rates in data transmissions, that is, on alternative error-rate specifications, do not necessarily influence project delay, but rather work intensity. A discussion details the usefulness of enriching the SD modeling process with alternative conceptual frameworks in the problem definition in such complex settings.
The phenomenon of dwarf or stunted small and micro firms (in Italian nanismo aziendale) is recognised in the small business literature. These are firms that have survived through many years, maybe many generations, providing their owners with acceptable returns and lifestyles, but have remained very small. They might therefore represent potential lost opportunities for owners and, given the importance of the SME sector, local employment and economies. A system dynamics model replicating the basic no-growth, cyclical behaviour attributed to stunted SMEs is firstly analysed. Alternative policies arising from different entrepreneurial views and aimed at changing behaviour to one of stability or steady growth, are then tested and analysed. In this relatively simple form, the model does link behaviours to system structure and could support individual entrepreneurs in understanding the reasons for dwarfism in their firm and the potential for unleashing growth. It could also form the basis for a more detailed model to support the identification and evaluation of strategic alternatives in individual firms.
Modelling knowledge in SD organisational interventions may become a puzzling task because of difficulties in achieving a common shared view among business key-actors about the impact of Intellectual Capital (IC) investments on future company performance.
Such difficulties are not only related to the intangible nature of IC, but also to the indirect role of knowledge in affecting performance drivers and outcomes. This phenomenon is particularly relevant in service businesses, where intangibles account for a high percentage of total assets.
In order to overcome such problems, a conceptual framework has been developed by the authors to build a generic SD model aimed to support business decision makers in IC planning, with particular regard to service firms.
Such model has provided the basis for developing two ILEs focused on a telecom mobile service provider and an insurance company. The first application was related to an education project, while the second one was linked to a consulting assignment.
The use of a conceptual framework as a basis to build an ILE has proved to be a successful strategy in order to better communicate business key-actors the potential of SD in modelling and assessing IC policies.
Main key-issues underlying model development and the ILEs application are discussed in the paper, and most significant outcomes from simulations are commented.
The evolution of fleet maintenance and management policies highlights the growing importance of maintenance issues in both private and public companies. The need to improve maintenance performance requires an accurate evaluation of the trade-off between costs and benefits related to alternative fleet maintenance and management policies. However, the complexity of maintenance system makes this evaluation a very difficult task.
More often a fleet manager deals with the following key issues:
is it more profitable to repair or to renew the company fleet?
Is it more convenient to reduce the average age of the different assets (e.g., by increasing investments in new bus) or to expand the maintenance activities (e.g., by rising repairing costs)?
In fact, fleet managers cannot ignore the impact of their decisions on both company service and financial performance over time.
Aim of this paper is to show how the System Dynamics approach can effectively support fleet managers in designing and evaluating their strategies. The simulation model here presented is based on the result of a project with two Italian city bus companies. Through such tool decision makers can test different fleet strategies and assess their effects on company performance.
In todays economy all manufacturers need to pay attention on how to build strong and long-term relationships with their dealers chain. In fact, it has been demonstrated that short term policies aimed to provide dealers immediate benefits (e.g., price discounts) may prevent the development of long term and fruitful relationships. Also supporting dealers in promoting manufacturers products has been proved as a sustainable strategy in long run.
Another implication of manufacturers bounded policies refers to their inclination to reinvest significant amounts of their sales revenues in advertising and product portfolio improvement, without taking into account the need to invest in dealers human resources, to make their strategies sustainable.
Based of the above remarks, this paper aims to demonstrate the usefulness of a system dynamics approach in involving both manufacturers and dealers in strategic reasoning.
Empirical evidence arising from a research project conducted by the authors with a manufacture operating in a high-tech industry, shows that using system dynamics as a methodology to support communication and learning may act as a significant lever to design successfully long term oriented policies. Such policies ought to increase dealers skills and motivation, and improve potential customers awareness of product benefits, at the same time.
Electric power systems are traditionally designed and developed with the assumption that demand is exogenous to the system. Connecting the feedbacks from the system to consumers will provide incentives for consumers to reduce demand during periods of high system prices. A system dynamics model is used to analyze the dynamics and long term implications of adoption of technology to enable demand response. The model includes the decision by consumers to adopt demand response technology along with decisions by investors to build generation capacity. The adoption process reduces overall system prices for peak demand periods, creating feedbacks with generation investment. The effects of technology improvement via learning, long term demand elasticity, and policies to promote adoption are considered. The results of the simulations show that diminishing returns to adopters and significant externalities in terms of free rider effects limit the attraction of individual adoption. A subsidy to alleviate the costs to individuals can be justified by the significant system level savings from widespread adoption. Several pernicious effects can emerge from large scale demand response, however, including increased price volatility due to a reduction in generation capacity reserve margin, an increase in long term demand, and increased emissions from the substitution of coal plants for natural gas and renewable generation capacity.
PANEL: Andrei Borshchev, Xjtek,Russia; Nate Osgood MIT,USA; Mark Paich, Decisio Consulting, USA; Hazhir Rahmandad, Sloan School of Management, MIT, USA; Mark Heffernan, International System Dynamics, Australia; Sara Metcalf, University of Illinois, USA; Chris Johnson General Electric, USA;Geoff McDonnell UNSW Australia; Other users from industry.
There is increasing interest in combining agent based (AB) and system dynamics (SD) modeling methods. This workshop will demonstrate the differences between the AB and SD approaches using some popular examples from the Dynamics of Contagion and the Diffusion of Innovation, using the AnyLogic multi-method software. It will also walk through some practical examples of the use of combined methods in health, marketing and other industries. The workshop will conclude with a "warts and all" panel discussion involving experienced SD practitioners and researchers in SD, geography and computer science, all of whom are adding AB methods to their work.
This paper presents a dynamic hypothesis explaining the system dynamics underlying the identity theft epidemic. The causal loop structure synthesizes current understanding of the problem and suggests that any strategy to address the identity theft epidemic by primarily focusing on prosecuting thieves without effectively mitigating the underlying forces is doomed to failure. The causal loop diagram elucidates the dominant feedback structure ...a collection of rapid-feedback, self-reinforcing dynamics that generate ample opportunities for would-be thieves. Preliminary results from the analysis provide a foundation for exploring policy options through a full working model, yet to be developed.
Environmental strategies such as Zero-to-Landfill are gaining increasing attention throughout the world. Product take back is a significant means of ensuring that products that have reached the end of their useful lives are reclaimed for reuse, remanufacturing, or recycling. Such a strategy is expected to minimize environmental impacts, reduce overall resource consumption, and provide economic value to manufacturers and consumers. The reverse logistics, however, can be quite complicated as product collection, product disassembly, processing, component returns, and component reclamation must be considered. Further, the costs and magnitude of the requisite system must be projected to support appropriate planning and execution. In this paper, we present a model of a reverse logistics system for a consumer product. The impacts of closed-loop logistics on product adoption rate, product costs, and component reliabilities are balanced against the cost of new infrastructure, shipping and tracking, and processing and inventorying of expended components. We illustrate how a reverse logistics approach may develop as a function of product adoption, the total value of returned components, product reliability, and product lifetime. A Zero-to-Landfill strategy has a significant potential to improve the triple bottom line people, planet, and profit of companies that adopt it.
Organizations may fail to adopt sustainable solutions as a result of incomplete and/or inaccurate feedback into the decision making process. Events that cause harm - environmental, health, or social - are commonly the delayed effect of a prior course of action, itself the result of decisions that emerge from endogenous policy. By accelerating the cost of future harm into current period decisions, producers and purchasers have greater access to the quantity and quality of information that influence decisions to produce and consume. The creation of a financial policy structure that makes future, long-term costs of production, promotion, and consumption explicit in the decision process will correct a current deficiency in the analysis of costs and benefits made by producers and purchasers. Such a feedback loop would correct a structural market failure and could reduce the need for governmental regulation.
Laboratory studies have shown that people cannot handle the time con-stants in dynamic tasks. Yet they obviously cope with such tasks with some success outside the laboratory. This study is one in a series of studies that examine the hypothesis that people cope by relying on heuristics that allow them to simplify the task. The heuristic studied here was that of relying on frequency differences, i.e., what Reason (1990) calls frequency gambling. It examines the effects of varying the relative frequency of scenarios that require different responding, and where relying on frequency rather than learning the actual time con-stants will lead to some success. The results show that the participants did not learn the time constants, that frequency had a strong effect on their decisions, but that their responding also seemed to be influenced by another heuristic identified in earlier studies, viz., that of rapid and massive responding. Implications of these findings for system dynamics modellers are discussed.
This paper introduces the notion of increasing returns to economic activity agglomeration and develops a formal system-dynamic model where this notion is used to explain the self-organizing nature of the spatial structure of industrial clusters. In this model, both pecuniary and external economies based on knowledge spillovers are considered.
The objective of the paper is to show that the one of the main source of macroeconomic investment instability is similar to that which makes difficult managing supply line in famous Beer Game developed by the system dynamics group of MIT Sloan School of Management. It will be pointed out that ignoring production time delays causes instability not because economic agents simply ignore supply line delays, but because they adjust their expectations more rapidly than the delays involved in supply lines, whatever those delays could be. The paper is structured in three sections. In the first we present the classic Phillips argument about unintentional destabilizing effects of stabilization policy in modern dynamic system language, in order to show how to build a simplified macroeconomic supply line model for investment dynamics; in the second section, the macroeconomic model is developed and simulated. Third section concludes the paper suggesting that the inclusion of production time delays in macroeconomic models reopens the space to the control theory in stabilization policy debate
Capturing Project Dynamics with a New Project Management Tool: Project Management Simulation Model (PMSM)
Ali Afsin Bulbul
Portland State University
Systems Science Ph.D. Program
Harder House
1604 SW 10th Ave.
Portland, OR 97201
Phone: (503) 221-4576
Fax: (503) 725-8489
afsin@pdx.edu
In this research, traditional project management concepts, methods, and their deficiencies relative to increasing complexity of projects is discussed. System Dynamics (SD) modeling is proposed as a complementary project management tool to be used at the higher level to augment operational level project management methods. The potential usage of SD models to promote the learning from projects, both in individual and organizational dimensions, is discussed. Working as a project management laboratory, SD project models can be successfully used to improve understanding of the project process. They can be used to design the project in the project-planning phase, to monitor and control the project in the project-execution phase, and to learn from the project in the post-mortem phase working as a learning infrastructure. A generic SD project management simulation model (PMSM) is built to serve for this purpose. The model structure and the graphical user interface are explained briefly. Tests performed to validate the model revealed that the model is appropriately designed, works properly, and it is robust relative to the purpose of the model.
The Department of Homeland Security (DHS) is funding the development of a Critical Infrastructure Protection Decision Support System (CIP DSS) that is intended to be used by DHS decision makers to assess the impacts of deliberate attacks or disruptions on the United States infrastructures and how they might be mitigated by investments in protective or recovery technologies. One of the 17 critical infrastructures is the Defense Industrial Base. The basic mechanisms of such a model are the flows, especially surge response flows, of war materiel from private sector defense industries to the Department of Defense (DoD). In order to capture surge flows, additional models of military logistics, especially deployment, and military missions are needed to drive the behavior of interest. Basic system dynamics models are being considered to provide this feedback to the basic mechanisms. With this consideration of military mission effectiveness, the models main output decision metric is an estimation of casualties, which presents its own system dynamics modeling challenges.
In this paper, we present a novel project management model that incorporates several features yet to be actively addressed in the literature and focuses on earned value management. The model utilizes the basic structures employed in building project dynamics models. The effects of time-varying project team size, of training and communication overload, and of change management are incorporated into our model. With the help of our model and a hypothetical software technology project, we demonstrate how our system dynamics model can contribute beyond basic project tools like MS Project, in generating the earned value management indicators required by project managers under different scenarios and starting assumptions. Results are consistent with well-known behavior of projects in that the later the changes arrive, the longer is the delay in completing the projects. These phenomena are propagated through the earned value measures to see the actual effects upon schedule and cost performance indices. The study also focuses on the use of earned value measures as well as critical chain concepts to understand how these separately impact project duration and cost.
This paper takes a system dynamics perspective of the contemporary trend of Offshoring Knowledge Worker jobs from USA to gain a better and deeper understanding of the results and implications of the trend, its impact on the jobs and workforce dynamics. The results not only support the viewpoint of economists that offshoring is beneficial to the economy, but also highlight another impending phenomena just round the corner, namely the slow rate of growth of workforce. Net U.S. workforce growth is slowing because seventy-one million baby boomers are beginning to retire. In this context, model outputs suggest that offshoring is postponing the undesirable state of U.S. jobs outstripping the U.S. workforce by nearly five years. Thereby, policy-makers have longer to find effective solutions to tackle the impending shortage of workforce in decades to follow. The model suggests that offshoring could not have come at a better time for the US economy.
Faced with new challenges in managing the cyclical and volatile business environment, management at a Commodity Plastic (COM-P) Company agreed to apply System Dynamics (SD) to support strategy development. A SD model of COM-P industry was built by adapting the Pulp and Paper Model. The structure of COM-P Index Price creation was mapped and added to the generic model. The following were investigated: a) The effect of current delays in adjusting prices on phantom demand, on capacity utilization and shipment rates; b) The phenomenon of Phantom demand or pre-buying when customers perceive that prices may be about to go up was modeled; c) By applying the model, the amount of margin lost or gained by the industry due to the price protection terms in the contracts was estimated; d) The risk in the top ten long term contracts under different supply and demand conditions and oil prices in order to support the sales organization with their negotiations; e) The model was applied to get guidance on capital investment timing and to assess the effect of different oil prices and supply & demand scenarios on the profitability of new investments. In many cases the results were counter-intuitive.
Society membership has grown by over 40% from 1999, but the representation of women has remained flat at 12%. Thus, in July 2004 the Policy Council unanimously approved the formation of a committee to work on tracking and improving the diversity of the System Dynamics Society. Last October, a pilot diversity survey was included in the annual membership renewals. In the course of developing the survey, members raised important questions about how diversity should be defined for the System Dynamics Society. More importantly, the initial results suggested potential solutions. Both issues raised questions that need to be discussed. How should diversity be defined with respect to the System Dynamics Society? How does diversity affect participation at conferences and in the society? What are some possible solutions? Please join us in this roundtable discussion on diversity in the System Dynamics Society.
Kaplan and Norton propose a double-loop process that integrates the concepts of Balanced Scorecard and Strategy Map to support managers to define and implement the firm strategy more effectively. The BSC is a performance management system based on a set of few and critical indicators. These key performance indicators are linked together in a causal diagram that represents the hypotheses about the strategy. This approach supports what Argyris calls double-loop learning which facilitates the strategic learning of managers and leads to better performance. This type of learning produces changes in manager assumptions about cause-and-effect relationships and leads to a better understanding of the context, what means a process by which managers can explicit and improve their mental models about the business system. This article describes a simulation-based research for testing a system of hypotheses about the influence of the BSC approach on strategic learning and performance, which uses a System Dynamics-based micro world.
A method of overall analysis for a compared evaluation of various nuclear fission and fourth generation units is here described. In this paper a series of questions related to the near-term deployment of new nuclear technologies in the US and Worldwide are answered and validated by reproducing the mechanisms that drove the nuclear market to the actual configuration. It is then presented a simplified model of the form often used to project market competition ad hoc configured for the case of the energy production by nuclear power. The reproduced mechanisms of interest as well as the out coming model had been designed following the SD approach since it was considered a most suitable and necessary tool for the research and evaluation of the typical feedback effects, which are characteristic of the destination market.
The most outstanding mechanism in terms of importance, uniqueness and significance was undoubtedly the lock-in effect, also referred to as long-term market domination. According to the lock-in phenomenon, even though a nuclear power plant is less attractive from a technical point of view it can take control of the market by being the first to be installed or by moving faster along its learning curve.
This paper revisits the macro-economic modelling and medium term scenarios undertaken at the New Zealand Planning Council (now disbanded) in the mid 1980's. The following major reports were published: "A Macro-Economic Model and Scenarios to 1995" (by Eric Haywood & Bob Cavana) and "Towards 1995: Patterns of National and Sectoral Development" (by Dennis Rose, Adolf Stroombergen, et al). These reports discussed the development and use of a macro-economic system dynamics model (SDMACRO), used to generate trends for the main macro-economic variables, and a general equilibrium price sensitive sectoral model (JULIANNE), which generated compatible sectoral and national forecasts of a range of variables for each of 22 sectors for nominated years. The (JULIANNE) model used outputs from (SDMACRO) as constraints and inputs. A brief overview of the SDMACRO model and its use at the NZ Planning Council will be presented. Also, the reforms of the New Zealand economy that have taken place since the mid 1980s will be summarised and a comparison of the SDMACRO scenarios will be provided against what actually happened over the period between 1985 to 1995. Finally, the paper indicates the development that has taken place with the macro-economic model and how it is currently being used.
The integration of information systems and business process will affect competitive advantages of firms. In order to develop information system, modeling of business process is a fundamental work of system analysis and design. System dynamics is useful to solve non-linear, complex, time delay and feedback problems of business processes. However it still belongs to a special field of modeling language because it cant be integrated well with information systems in organizations. The purpose of this paper is to integrate system dynamics with UML and thus they can be developed synchronously during information systems implementation in enterprise. For this reason, integrated development process and system architecture with system dynamics and UML have also been proposed in this paper.
In this paper, I try to grasp the inner significance of abnormally sustaining house price growth, or so-called house market bubble in Shanghai real estate industry by the tool of system dynamics which especially focuses on the systems with highly dynamic characteristics, and complicated feedback relationships involved, which is consistent with the real estate market system. The most fundamental purpose of this project is to see whether it is the speculators intervention that causes the problem of unsuitable high price in Shanghai house market or not and to see what kind of impacts both on the aspects of society and economic fields will be after the trend of speculation is quenched. This paper mainly divides the system into 6 parts, population and economy sector, family house demand sector, speculators demand sector, speculators profitability sector, house price sector, and house construction and sale sector to analyze how these subsystem can directly or indirectly work on the whole real estate industry in Shanghai.
The system thinking is a kind of new thinking mode that fostering the creative ability. It already has some successful applied experience abroad, particularly in education. In the chemistry teaching especially the calculation of chemical equation of high schools,students are always puzzled by the numerous and complicated superficies of chemical equation and hardly grasp its mathematics essence,which result in bad teaching effect.
This dissertation makes some beneficial quests. Aiming at the relevant problem of the calculation of chemical equation, we put up some teaching practice in 5 classes by using the system thinking method and its related software STELLA, such as the teacher's brief introduction to the software, the basic calculation model establishment way and students activity etc. In this process, students can hold the calculation regulation more effectively. At the same time, the study moving ability between teachers and students also improves dramatically, which leads to the exciting development in other realms.
As a high school student who really enjoy the world of architecture, I use the Stella software to have a try on explaining the former of the curved roof of Chinese ancient architecture by system dynamics view: the factors we call structure, practical, aesthetic judgment, economy affect each other. The trend of the using of the curved roof was increased a lot at first, and then reached a balance eventually; the explanation itself has caused and satisfied my interest of a kind of research. But something more important is that I have cemented an opinion here: in our world, physical and mental (we call it a system), so many social phenomena exist under the control of different basic factors. Its more complicated than we expect most of the time. Luckily the system dynamics view makes us face the complicating world in a deeper, wider sight, and retrace the procedure of its former and change. Then we can make sense of world better. So this kind of try has encouraged me a lot.
This article examines the conceptual framework for the social amplification of a risk issue with an analytic lens of System Dynamics. It will explore the dynamic interaction of general public, mass media, government agencies, and non-profit organizations; or what is called social stations, with regard to the national project of constructing the high-speed railway in Korea which was stopped by a Buddhist nuns 100-day hunger strike for protecting salamander and natural environment. Existing studies show that risk amplification occurs when media sensationalism causes risk perception and public concern to be magnified far beyond levels proportional to the risks estimated in risk assessment science. The case study underlines that social amplification is much accelerated within a highly networked society, or internet environment. Such process can create political over-activism or disruption, social conflict, or policy failure more costly than what the issue is.
The possible diffusion of plant-derived vaccine (PDV) biotechnology in developing countries offers an interesting potential substitute to existing more expensive vaccine technology currently available on the market. This paper is concerned with the potential impact that the introduction of such a technology could have on the cost of immunization, and also, more broadly on the incidence of hepatitis B cases on Indias population overtime. The objective of the paper is to look at the hypothetical issues of a PDV diffusion using a system dynamics (SD) model. Some illustrative results are presented to show the interaction between infection rates, mortality rates, and immunization costs. In spite of promising features, such as much lower production costs, institutional hurdles to a widespread diffusion of the technology still need to be overcome.
This paper addresses the question of whether there is a conceptual model that can explain operational risk in a wide range of organizations. It utilizes case studies and other research literature to build on the foundation laid by previous modeling research into system failures. The validity of the model is tested by how well it fits the parameters of operational risk failures and successes in case studies representing a diverse range of situations in manufacturing, mining, financial services and government.
The aerospace, IT, and construction industries have seen a significant shift over the past few years from "cost-plus" contracts (where "every change is good", and means more revenue), toward "fixed-price" or "ceiling value" contracts (where the cost of every change must be negotiated with the customer or traded off against other work). The disruptive effects of these changes are substantial, but are universally poorly (and under-) estimated. The result has been unexpected cost overruns, lost profits, and disputes. This workshop will combine lecture and group exercise to teach valuable lessons about project disruption dynamics. In the session you will learn how change impacts spread to disrupt a project's performance and learn some mitigations to reduce or avoid the disruptive impacts of changes. For further information please contact Tom Kelly at
tom.kelly@paconsulting.com.
In this paper we discuss the way in which dynamic modeling can be used to deal with front-end, back-end and integration issues in current high-tech virtual supply chains (SC).
In a first part of the paper we review and propose dynamic modeling options to connect customer value to business targets. This is done by explaining how to characterize target market by formalizing what are often informal but deeply held beliefs about what drives their customers' purchase decisions. We explain how dynamic models may help to connect planned investments to expected improvements in the customer's perception of the product critical attributes and thus increase sales, revenue, and market share.
In a second part of the paper we review and discuss the operational and financial effectiveness of existing virtual tools used in supply chain integration. We discuss how dynamic modeling may help to obtain a comprehensive model of supply chain integration. A modeling effort that can be used for the analysis of the effectiveness of various levels of integration.
In a third part of the paper we discuss and explain experiences in modeling different types of supplier contracts to accomplish varying degrees of security and flexibility.
Previous research has shown that individuals fail to understand the basic building blocks of complex systems such as stocks and flows, feedbacks, and time delays. This paper presents three empirical studies intended to understand why individuals misperceive the relationships between stocks and flows. We used problems that were quite familiar to the participants, interventions to motivate participants to think harder in the problem, simplifications of graphs and direction of attention to specific aspects of the graphs. The results seem to disclose some of the mechanisms that individuals use to make their inferences about the graphs. That is, individuals attend to the most salient features of the graphical representation to make their inferences about the stock in the task. Does this really imply a misunderstanding of stocks and flows? We believe the further research needs to address this problem in realistic presentations rather than graphical representations.
We still know very little about the long-term learning patterns of organizations. Analysis tends to favor the more immediate factors over more distant ones. We focus on synchronic portrayals of the organization while ignoring diachronic representations.
The model presented here analyzes changes in the state of the organization over time. It describes and investigates the totality of forces and actions that generate the organization's dynamic. It offers a speeded-up aging of the organization intended to bring out, over time, the counter-intuitive effects of decisions. Moreover, it endeavors to identify the cost drivers that contribute to increasing or shrinking the firm's profits.
We have used the meta-model that we developed to derive an application model whose purpose is to reproduce the long-term life of an organization. Our simulation speeds up the aging of the organization, enabling us 1) to show the counter-intuitive effects of decisions over the long term versus the short term, and 2) to highlight the cost drivers that generate hidden costs. Through its decisions, the firm gives rise to its own factors of development and decline: its own actions eventually change both the organization's health and its properties.
Distribution must make a decision regarding its role in the specialty contracting supply chain. It can continue its historical role as wholesale/retail combination and hope for profitability, or it can choose to manage the channel by providing low cost products and services.
Profitability can only come through system productivity. System productivity depends on recognition and elimination of waste in the current operations and can be further improved by operational process innovation.
The cost drivers (CDs) of distributors can be impacted by identifying and addressing internal inefficiencies, effects of customer interactions, and the impact of suppliers on price and delivery. By managing the following elements, distributors can improve their bottom line by better than 30%:
1. First-time pass yield of order taking and delivery
2. Identification and reduction of waste
3. Customer point of entry
This paper suggests a methodology for improving the system productivity through management of these elements.
Accounts of the real-world use of system dynamics as a policy evaluation tool in macro-economic management are relatively rare. This paper offers an overview of current research being undertaken for the government of the State of Sarawak in E. Malaysia where an SD model is being formulated to inform the States future economic and social planning to 2020. Although still a work-in-progress, enough has been achieved to enable an interim account of the research to be written. Positive engagement with State government officials at the highest level has put system dynamics on the map in this corner of SE Asia.
Our paper presents a model of economic impacts arising from disruptions to critical infrastructures. This model is a component of the Critical Infrastructure Protection Decision Support System (CIP/DSS) which simulates the dynamics of a set of interconnected individual infrastructures. We use factors of production (such as energy, telecommunications, and labor) from the CIP/DSS model to estimate the effects of interruptions to these infrastructures. The system dynamics approach we use is compared to equilibrium-based approaches such as input-output modeling. This method allows an understanding of the economic benefits of various protective measures. We incorporate non-equilibrium dynamics that arise from these disruptions to provide values for various economic impacts such as lost revenues and lost sales. The results from a disruption due to an infectious disease outbreak are presented. We show that the effects of quarantine dominate the overall economic impacts in a number of cases.
Extreme Events are low probability, high consequence events, often resulting in billions of dollars of damage each year in the United States. Natural hazard issues connect experts in the natural science and social science, which complicates the problem for policymakers who may have balance multiple objectives as well as short term and long term goals. The recent devolution revolution trend in government has made its way to natural hazard policy domains. There is more pressure on local communities to create and implement mitigation plans that will promote long term sustainable development at the local level. The conceptual model for this research project explores the primary mitigation policy alternatives and depicts the "false sense of security" trap, with endogenous explanations, in a stock and flow feedback structure.
If junior doctors are to work significantly fewer hours in the future, how can they still receive full training and continue to provide necessary levels of medical service to patients? Historically, excessive hours have been a way of the life for junior doctors worldwide, but New Deal regulations, a revised junior doctor contract, and the EU Working Time Directive are changing this. A project at Derriford Hospital in Plymouth is researching the nature of quality and effective training, and constructing SD models to yield insights and eventually support operational decision-making. This has already yielded significant insights for those at Derriford wrestling with this seemingly impossible task, including, the circularity between junior doctor training, consultants service and their training-supervision role, and the quality of training provided, and the likely importance of recruiting outside the progression process in addressing service imbalances. It also highlights some of the special challenges in projects where there are many stakeholders, political agendas, and a continuously changing environment.
Most dynamic decision making tasks include assumptions which have a huge uncertainty attached to them. Organizations are inherently complex. The combination of uncertainty and complexity results often in a sub-optimal decision. This paper emphasises on the usage of probabilistic system dynamics (SD). The focus of probabilistic SD is to represent the behaviour of uncertain variables in a realistic manner. The information generated by probabilistic SD could produce complete information thereby improving the mental models of decision makers. Many SD models use deterministic values of variables. However, determinism is untrue for real business settings. In order to test the effectiveness of probabilistic SD on managerial decision making, this study aims at conducting a series of rigorous and controlled experiments. Specifically it tests the usefulness of (1) system dynamics itself, (2) model validation techniques and (3) probabilistic system dynamics on decision-making. Furthermore, these experiments are conducted in two settings (1) using a simple model and (2) using a complex model. It is hoped that probabilistic SD would be instrumental in producing relevant information that would help in improving managers mental models, especially in complex scenarios. This in turn will result in better decisions under uncertainty in complex business environments.
This paper discusses the benefits of having an interchange standard for system dynamics models, why XML is a good candidate on which to build such as standard, and how the development process may take place through community-wide participation. The paper also presents XMILE, a prototype model interchange standard, as a proof of the concept.
We analyze experimental data from the Beer Game in which the customer orders are constant (4 cases/week) and all the subjects are informed about this fact before the game starts. Even though the experimental settings disfavor oscillation and amplification, we still observe them. To analyze the decisions made by the subjects, we first estimate the decision rule used by Sterman (1989). This analysis suggests that typically subjects do not understand the time delays and the stock and flow structure of the Beer Game. Next, we relax some assumptions of this decision rule and use more sophisticated alternatives. These alternative decision rules do not yield overall improvement in terms of fit to the real data. However, for some subjects, these decision rules lead to significant improvement. Our analysis reveals strong evidence that these subjects were caught up in a reinforcing phantom ordering loop even though the experimental conditions strongly disfavor such behavior.
Sustainable use of a natural resource ensures that the ecosystem associated with that use will also provide long term environmental services to society. Such services might include the provision of clean water, removal of excess CO2 from the atmosphere, flood protection, pleasant vistas, or enhanced biodiversity. These benefits are becoming less abundant as inappropriate resource uses hasten environmental degradation.
In theory, if beneficiaries pay for the environmental services received, and these payments are given to the resource users/owners to reward, or encourage, sustainable resource use, then such sustainable use will be assured. Schemes to implement such arrangements might be able to support conservation programs, and also supplement income of poor farmers and forest dwellers. Such payments are also seen as a means of encouraging better management of carbon dioxide in our atmosphere, by paying for forest practices which can store CO2.
How do such systems actually work? Can payments for environmental services encourage better resource management? Might they also create disincentives for management based on ethics, altruism, and stewardship? A generic system dynamics model was used to examine these questions.
Multiple objective optimisation (MOO) is an optimisation approach that has been widely used to solve optimisation problems with more than one objective function. The benefit of this approach is that it generates a set of non-dominated solutions which a policy maker can explore and evaluate before making a final optimal selection. This paper demonstrates that MOO can be used to assist policy makers explore a richer set of alternatives when deciding on a range of values for key parameters in their system dynamics model. In order to demonstrate the approach, a well-known case study The Domestic Manufacturing Company is used, and a stock and flow model and a multiple objective optimiser are designed and coded. The results show that valid solutions are generated, and that each of these solutions can be examined independently and hence give greater insight into the problem at hand - before a decision is made as to the most appropriate solution.
Multiple Objective Optimisation (MOO) is a proven technique that can be employed by systems dynamicists as they seek to optimise parameters in simulation models. MOO employs genetic algorithms and Pareto-based ranking to find non-dominating sets of optimal solutions to problems that have more than one objective. The aim of this workshop is to: (1) Explain the multiple objective optimisation approach; (2) Show, though an interactive simulation model, how it can be applied to a popular system dynamics model (a two actor version of the beer game); (3) To explore with participants answers to a number of questions, including: (a) What kind of benefits can MOO bring over traditional optimisation approaches? (b) How do modellers decide on the appropriate payoff function? (c) How do decision makers approach the dilemmas of trading off two objectives? All participants will have access to a special purpose simulation application (Windows based) that will allow them to run simulations and optimisations on the two-agent beer game.
System Dynamics simulation models of organizational business system of management of material (raw-materials, orders, money, labor, personnel, population, capital equipment: tools, units and factories e.t.c.) and informational flows in productive company will be presented in this paper. Organizational business-production system is simulated by effective scientific discipline System Dynamic and realized by Dynamo (PD4) and PowerSim program packages, also.
Due to complexity and extensiveness of business management of organizational business process or production-distribution system global simulation models of companies are presented on the modular way, i.e. with seven relevant sub systems:
1. Production-inventory sub system;
2. Credits sub system;
3. Debits sub system;
4. Sub system of productive capacities;
5. Sub system of Cash-Flow;
6. Gross income-net income sub system;
7. Sub system of demand for organization products,
which are common structural characteristic in every productive business organization. These sub system are modelled according to its specific quality.
The paper is conceived as follows: sub systems of business production organization, entire model of productive organization system and its simulation, conclusion and used references.
Access to energy, particularly through clean and modern technology, can make substantial contributions to promote rural development in the poor areas of developing countries. However, the relationship between energy, poverty alleviation and sustainable development is still unclear. Additionally, while improving access to energy is required for development, the way that this has been supplied has not always warranted a sustained livelihood in rural areas.
With the purpose of gaining a better understanding of the relation between energy and development, the current research Renewable Energy for Sustainable Livelihoods-RESURL, aims to assess and measure the factors that contribute or hinder the development of efficient, viable and appropriate access to energy provision in remote rural areas by using a multidisciplinary and participative perspective.
A System Dynamics model is constructed to evaluate the contribution of energy to rural livelihoods. SD modeling facilitates understanding feedback and control processes, as well as delays in decision making. Simulations show how isolated communities in conditions of poverty could attain a satisfactory level of human, social, physical and financial development by making sustainable use of their natural resources through energy technologies. The study draws on the sustainable livelihoods approach as a framework for assessing community assets and capacities.
The rapid spread of HIV/AIDS is a global crisis one that is particularly devastating to the economies of nations where the disease is most prevalent. Booz Allen Hamilton, in conjunction with the Global Business Coalition on HIV/AIDS (GBC) and the Confederation of Indian Industry (CII), developed an innovative approach for The AIDS Epidemic in India: A Strategic Simulation. Their approach captures the complex interdependencies that drive the HIV/AIDS epidemic and its economic consequences. At the core of this strategic simulation is an analytic framework that leverages epidemiological and economic System Dynamics modeling, partnerships with leading academic centers, and simulation-driven gaming.
Health care is a complex dynamic setting suitable for system dynamics analyses. The method has the potential to be an important quality improvement tool in the near future. However, it will be necessary to develop the models beyond the pure production model focus on the clinical care process from a patent perspective and in doing so it is inevitable that variables such as health, communication and care planning are involved. Consequently, useful and valid models for modern health care must involve variables that are unfairly designated as intangible. The present paper describes an exploratory system dynamics model of the care planning process. It draws on a range of studies and theories about the process. The paper discusses how it could be possible to incorporate and validate variables alongside the more traditional way.
This paper presents insights from an interactive seminar game using system dynamics to help the U.S. Latin American policy community explore issues associated with the process of paramilitary demobilization in Colombia. The game used system dynamics to represent the strategic interactions of the key actors in the Colombian paramilitary peace process, including their pursuit of both competing and complimentary goals. The process leveraged the gaming mode and rapid causal tracing capabilities of the Vensim system dynamics software to generate an interactive event in which players generated a rich set of strategic interactions in a hands-on learning environment. The success of the event suggests a promising new approach for leveraging the power of systems thinking and system dynamics software in policymaking and learning environments.
A panel of business and industry practitioners will describe how they have and hope to use system dynamics in their organizations. They will discuss which issues they have addressed with system dynamics and also share their perspective on what have been their biggest challenges and most significant successes.
This paper offers insights into the dynamics of carbon emissions in metropolitan regions. These
emerge from a system dynamics model of urban land-atmospheric interactions. The paper provides
contextual background, outlines modeling methodology, inventories insights and documents policy
implications. Section One considers climate change, worldwide urbanization, urban CO2 emissions and
urban land-use/transportation dynamics. Section Two identifies the study area, the modeling tool, its
dynamic organizing principle, its structure and the scenarios used to explore system behavior. Section
Three considers urban CO2 emissions and the mitigating effects of land-use and transportation
policies. It compares these to practicable improvements in fossil fuel combustion efficiencies and finds
that modifying urban form compare favorably to improving combustion efficiencies. Section Four
asserts that, given todays global-scale inter-metropolitan economic competition, todays urban
challenge will be largely met by cooperation at the metro-regional scale to tame the dynamics of
carbon-based metropoli.
Water supply is a hydrologic phenomenon, whereas water demand is largely driven by human wants and needs. The combination of these two systems, hydrology and economics, is necessary for accurate modeling of our water resources. Moreover, in times of drought or water scarcity it is the human behavioral component that will determine whether a regions water supply can be sustained. The stakeholders of the San Juan Basin are many and varied, from Indian tribes, agriculture interests, and municipalities, to recreational fisherman, power generators and conservationists. Stakeholders must make policy decisions regarding shortage sharing in times of drought to ensure their water supplies are sustainable. We develop a system dynamics simulation model for the San Juan Basin watershed (located in the states of New Mexico and Colorado). The model can be used to quantify shortage-sharing amounts needed for sustainability of water supplies. Hydrology drives the water supply while economics drives the water demand.
In the UK, drug misuse gives rise to between £10 billion and £18 billion a year in social and economic costs, 99% of which are accounted for by problematic drug users. There are strong links between problematic drug use and crime. The Drug Interventions Programme (DIP) is a critical part of the Governments strategy for tackling drugs. The implementation of the UK Drug Intervention Programme poses a number of challenges. This includes providing a through-life approach to drug user treatment management. This must take place within a multi-agency system some of which have been newly formed. This paper discusses a study working with one such coordinating body Lancashire Drug Action Team (DAT) in its Drug Intervention Programme (DIP) strategy. Initial work has focused on Aftercare Services in the Burnley area. A systems modelling approach using System Dynamics has been adopted.
"Modeling Dynamics Systems: Lessons for a First Course" provides a set of tools that enable educators at the secondary and college levels to teach a one-semester or one-year course in System Dynamics. 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. A set of student lessons, a teachers guide with all the answers to the student lessons (and additional comments to the instructor), as well as a CD containing all of the models, is provided with the book. Participants in the workshop will have a chance to build some simple models and gain a sense of the progression leading to a more sophisticated model. Student work will be demonstrated and a CD containing samples of student work and their technical papers will be provided to all participants.
Abstract: This paper examines the nature and effects of collaboration using a System Dynamics Model. The goal of the model was to place collaboration into a System Dynamics operational construct using stocks and flows in order to examine its workings. Using simple representations of two analysts attempting to learn from a dynamic document set, questions regarding collaboration, skill, learning and the effects of rapidity of change within the document set are examined.
Findings indicate a knowledge-based rationale for collaboration during periods of increased operational tempo. However, there also appear to be knowledge-based reasons not to collaborate under certain conditions. The knowledge-based rationale is mirrored by the behavior of real social systems.
By 2011 Switzerland aims to liberalise the milk market which will result in market changes in the basic conditions for agriculture. The impacts of the liberalisation are investigated with a composite model obtained by combining an optimisation model for the agricultural sector and a dynamic simulation model for the milk and meat market. The calculations with the composite model indicate that milk price depends strongly on the phasing out of market support, while the abolition of milk quotas in 2009 is less decisive. An introduction of a dairy cow premium leads to a higher milk production, especially with abolished milk quotas. In this case the European milk price level represents the lower limit for the milk price in Switzerland. Compared to the milk market, with falling quantities meat prices are likely to exhibit a stable development.
The Climate Stewardship Act, a global warming mitigation policy calling for a cap-and-trade program, was reintroduced in the United States Senate this year. The Energy Information Administration analyzed the implications of the bill and found that under such a policy renewable energy will increase, with the strongest response coming from biomass energy. Dedicated energy crops are one source of biomass that is expected to contribute significantly to the future biomass energy supply. This paper describes a system dynamics model of the carbon impacts from a dedicated energy crop. The work relies on another carbon accounting model, GORCAM, which uses spreadsheet modeling to investigate various land management regimes. We were able to reproduce the GORCAM results for a 20-year harvest rotation; we then simulated several different harvesting intervals to gain insight into the carbon impacts of these rotations. Our results show that a shorter harvest rotation will remove more carbon from the atmosphere if the biomass is used to replace a fossil-fuel burning power plant compared with no-harvest or longer harvest scenarios. These results agree with previous work that found long-term benefits were greater for scenarios where trees were planted for energy generation rather than specifically for carbon sequestration.
There is a critical need to develop land planning processes that can build the
capacities of local communities to address stewardship and sustainability at both the individual and collective/landscape scales. Social learning has been advocated as a process by which to build the capacity of local communities to address these issues. This paper outlines a social learning process currently being conducted to collectively develop a common mental model (or schema) of local landscape change among private forest landowners of Morgan County, Tennessee. By seeking a shared schema of landscape change landowners will elucidate and engage hidden assumptions that guide their land use decisions. This learning process is expected to increase community capacity by giving landowners a common understanding from which to make and/or support more sustainable land use decisions. The effectiveness of the social learning process is evaluated using individual cognitive mapping in a pre/post test quasi-experimental research design.
Previous system dynamics work models the tipping of a series of product development projects into fire-fighting mode in which rework overwhelms progress. Similar dynamics also threaten the performance of individual development projects. The current work extends previous tipping point dynamics research to single projects and demonstrates how a simple, common feed back structure can cause complex tipping point dynamics, trap projects in deteriorating modes of behavior, and cause projects to fail. Basic tipping point dynamics in single projects are described, analyzed, and demonstrated with the model. Researchers recommend dynamic resource allocation policies to improve project performance threatened by tipping point dynamics. This existing work and the potential robustness of adaptive policies suggest that dynamic resource allocation policies can protect projects tipping point-based failure. But this hypothesis has not been tested for specific policies. We test several strategies for managing projects near tipping points, including dynamic resource allocation. The effectiveness of dynamic resource allocation as protection against project failure are modeled and described. Implications for project management practice and future research opportunities are discussed.
Climate change researchers are often asked to evaluate potential economic effects of climate stabilization policies. This paper examines what impact modelers' assumptions have on a model's results. Specifically, MIT's Emissions Prediction and Policy Analysis (EPPA) model is examined to understand how uncertainty in input parameters affect economic predictions of long-term climate stabilization policies. Eleven difference categories of parameters were varied in a Monte Carlo simulation to understand their effect on two different climate stabilization policies. The Monte Carlo simulation results show that the structure of stabilization policy regulations has regional welfare effects. Carbon permits allocated by a tax-based emissions path favored energy importers with developed economies (e.g., the US and the EU). Countries with energy-intensive economies (e.g., China) will likely have negative welfare changes because of strict carbon policy constraints. Oil exporters (e.g., the Middle East) will also be negatively impacted because of terms of trade fluxes. These insights have implications for stabilization policy design. The uncertainty surrounding economic projections exposes some countries to larger economic risks. Policies could be designed to share risks by implementing different permit allocation methods. Direct payments are another means to compensate countries disproportionately disadvantaged by a stabilization policy.
Insurance Companies sell information to clients, written in contracts called policies. Clients buy those contracts by paying a premium. Those contracts are promises to pay for possible future casualties. Thus, it is essential to manage information flows to improve profits and stability. Loss Ratio LR, claims cost to premiums ratio, is a key profitability factor, used for management and underwriting decisions with the help of different actuarial models. However, the fragmented visions provided by those actuarial models, mislead decisions and deteriorate performance. This paper integrates basic insurance statistics into a comprehensive SD model, to price insurance coverage. The emphasis is stressed on modeling rather than on policy design, so experience can be used elsewhere; however, tampering and major deteriorating loops are analyzed. Policy design complement policy underwriting.
ERP projects are often undertaken by project managers in an effort to solve a problem, increase efficiency, and/or provide a higher level of customer service. Although ERP systems can provide all of these benefits and more, they can also cause havoc in an organization if not managed correctly. There are far too many horror stories about organizations failed ERP initiatives. In fact, the success rate of ERP implementations is only around 33% and approximately 90% of ERP implementations are late or over budget. ERP implementation articles consistently report that implementation failure or success is people-related. It's often easier to blame the technology then to explore these deeper issues but in the end they are the controlling factors. It is important for managers to understand the complexities of the people-related issues, relationships and office politics before embarking on a new ERP project. This research is intended to provide insight regarding ERP implementation dynamics through modeling; to build and explore theories regarding what causes ERP success/failure and ultimately aid project managers in avoiding common pitfalls.
Technologically oriented firms must allocate resources between exploration (research) and exploitation (development) activities. March (1991) proposes that the ecology of competition will directly influence the degree of emphasis on exploration and exploitation activities by organizations; the greater the competition, the greater the need to emphasize exploration activities. Exploratory case studies and real market data indicate that this is seldom true. This study examines this issue by adopting a two-pronged approach. First, a game-theoretic model is used to gain insights regarding the optimal strategies for firms. Second, the intuition from game theoretic analysis is enhanced and validated using complex adaptive systems approach. An agent based model is used to simulate the complex market place where competitors R&D strategies directly affect the focal firms R&D strategy outcomes. The authors find that organizational adaptation to dynamic environments significantly impacts the firms performance over time.
Previous studies have used the mental models construct as an ex-post explanation for poor performance on complex tasks, but the effects have remained untested. This experimental study measured and tested the role of mental models in a complex decision environment. Participants worked on a product lifecycle simulation under one of two levels of complexity for three blocks of 40 trials before measures of mental models were assessed. Immediately following the measures, participants completed another three blocks of 40 trials. Ten weeks later, participants completed another three blocks of 40 trials each. The results indicate that ability and task complexity are significant predictors of mental model accuracy, and that mental model accuracy and complexity are significant predictors of performance. Mental model accuracy is also related to the decision heuristics employed on the task, and the decision heuristics are related to performance. The results suggest there is potential to increase performance in complex decision environments by up to 50% through improving decision making. Validating these measures of mental model accuracy will enable researchers to incorporate this variable into their study designs in future research, and begin to identify levers for improving causal inferences, mental model accuracy, decision heuristics and performance.
There are two parts.The first,Systematic dynamics and students innovational activities.The second ,Systems dynamics selective breeding physics theory study. Student's achievement indicated that, with the system pondered instructs student's innovation, may sharpen student's innovation ability, causes the student to experience the innovation pleasure, raises students' innovation spirit.
An exploratory system dynamics (SD) model presents disruptive innovation diffusion as a
replicable process that can spawn business growth for d, Inc., a company that offers an
over the air digital subscription TV service. Building on diffusion processes in
epidemiology, marketing and sociology, the eight-sector SD model shows customer
switching in the high-and low-end and non-consumption markets that disruptive
innovators exploit. As extreme-condition scenarios test its robustness, the model shows
performance results for the multiple market penetration and defense tactics that disrupter
and incumbent firms execute through time. In a relentless hunt for superior performance
and a sea of external-change triggers and internal-change levers, d, Inc. takes on cable
operators who overlook low-end markets and devote their attention to and invest in
higher-end tiers, their service tailored to more demanding customers. But low-end
markets cannot absorb sustaining innovations that exceed what non-consumers need or
know how to exploit. The results show that despite the high environmental turbulence,
market risk and uncertainty facing d, Inc., being in a market that blends its commercial
and technological competence with discontinuity and instability transients suggests
ample opportunity for sustainable disruptive growth, even if markets contract.
Even if arbitrage opportunities are found in a statistical sense, they might not be exploitable due to unexpected widening of spreads. This paper models such a case in the framework of a hedge fund. Specifically, Long Term Capital Management is presented as a case study. In particular, we calculate the likelihood of hedge fund failure and survival given different statistical arbitrage opportunities and hedge fund risk management decisions. Dynamic relationships between a hedge fund, dealer, and market (investor) are modeled.
This workshop discusses how advances in technology allow modelers to develop and share their own dynamic simulations on the web. New tools have made creating web interfaces to system dynamics models simpler and inexpensive, but model developers still face hurdles developing web simulations because of the design expectations of Web users.
Simulations that run in web browsers have the advantages of global accessibility, simple distribution, and the ability to monitor simulation usage. However, simulations previously delivered in other formats need to be modified in order to effectively use the online medium. Simulations need to engage the user, be simple to navigate, and correspond to the user's learning objectives.
This workshop will consist of presentation and a hands on workshop. During the presentation, Will Glass-Husain will demonstrate how to create web simulations and discuss commonly occurring web simulation design challenges and potential solutions. The session will also include a hands-on session where participants will create a paper outline of potential simulation design for a model of their choosing.
When demand exceeds supply, customers often hedge against shortages by placing multiple orders with multiple suppliers. The resulting demand bubbles creates instability leading to excess capacity, excess inventory, low capacity utilization, and financial and reputation losses for suppliers and customers. This research contributes to the understanding of phantom demand caused by shortages by developing a formal model of the relationship between a single supplier and multiple retailers. The research combines simulation and game theory to explore equilibrium strategies that arise as a result of a dynamic game.
When retailers must commit to a single strategy in a static retailer game, our analyses suggest that a prisoners dilemma arises if appropriate incentives are not in place, allowing retailers to reach equilibrium with an aggressive ordering strategy (inflating their orders and later canceling them) even though a conservative ordering strategy (ordering just what they need) is mutually more profitable. The conservative strategy dominates the aggressive one when sufficient incentives are in place. In addition, we investigate a number of strategies (e.g. tit-for-tat, severe punishment, etc.) for retailers in an infinitely repeated game and we explore the static and dynamic games for the supplier-retailer interactions.
The session consists of four papers: Real Time Diagnostics of Problem-Solving Behavior for System Dynamics-Based Business Simulations; Sensitivity Analysis of an Infectious Disease Model; Leveraging a High Fidelity Switched Network Model to Inform a System Dynamics Model of the Telecommunications Infrastructure; and Critical Infrastructure Protection Decision Support System.
The first paper concerned supporting learning in and about complex problems. The paper describes the diagnostics of the problem solving process, i.e. of the information-retrieval and decision-making processes, as prerequisite for effective feedback to the learner.
The second paper describes a model of infectious diseases that has been developed for integration within a larger simulation structure to assess the interdependencies of critical infrastructures. This paper presents the preliminary sensitivity analyses of the effects of inputs to the infectious disease model on the calculated consequences.
The third paper summarizes the results of a collaborative effort with Bell Laboratories, Lucent Technologies to leverage a detailed switched network simulation to inform the telecommunications system dynamics model in a Critical Infrastructure Protection Decision Support System (CIP/DSS).
The fourth paper describes CIP/DSS and simulates the dynamics of individual infrastructures and couples separate infrastructures to each other according to their interdependencies.
Cormorant fisherman on the Li River, China . Farmers tilling the rice terraces of Bali, Indonesia A red seahorse in the waters of St Vincent in the Southern Caribbean Alpenglow in the Dolomite mountains of Northern Italy these are some of the remarkable moments and amazing places that I have been privileged to photograph in my world travels and am delighted to share with you. They are all part of the wonderful but fragile systems that make up our world.
Hutchison Telecom Hong Kong had a problem. The telecoms Regulator, OFTA, wanted to take away some of its spectrum and use it to add yet another competitor into this already highly-competed market. Hutchison perceived that the proposed action would not only be unfavourable for Hutchison, but also for the consumer. But this view hadnt been accepted by the Regulator, when expressed in the form of traditional regulatory arguments. This case study describes how Hutchison commissioned and used a System Dynamics simulator of the Hong Kong wireless markets (2G and 3G, voice and data) to rigorously and transparently quantify the situation. The simulator used 1) interviews with many experts and stakeholders, including the regulator, 2) confidential company data, appropriately protected, 3) judicious calibration against 2G history and 3G plans, 4) optimization of 3G competitors pricing and investment strategies to game out future market evolution, under different regulatory decisions. Sensitivity testing showed that the remaining uncertainties did not alter the fundamental results: The regulators proposed action would not benefit the public. After due consideration, OFTA dropped its plans and will not bring in more 3G carriers. Both Hutchison and OFTA have done well for their respective stakeholders.
The German Health Insurance System is balanced on the edge. Decision makers seem not successful in developing and implementing sustainable health policies, which ensure at least a balanced health insurance fund. Highly dynamic factors influence the health insurance fund situation and complicate the decision making. The System Dynamics Methodology is used to examine first possible causes of the enduring problem. In the formal simulation model, we include among other variables the population dynamics, personal income, contribution fraction and health expenses per capita as well as behavioral states of the agents. Second, the model is used to conduct simulation-based policy testing to find improved decision rules. The policy expenses reduction pressure forces the government to reduce health insurance ex-penses per request. It can improve the health insurance system situation best. The result will be a reduction of the health insurance fund shortfall. Other policies worsen the problem sig-nificantly due to increased oscillatory tendency in the health insurance system. As result of the study, the different policies are discussed separately.
Keywords: Soft System Dynamics, German Health Insurance, Sustainable Policy,
Co-Payment Policy
The Methodology of System Dynamics claims to promote understanding of complex systems. Accepting this claim, the question Does experience or an education in System Dynamics help people to solve simple, dynamic problems? arises. It guides the conduction of our experiment. The first hypothesis about no influence of additional information for problem solving has to be accepted. The performances of two different information treatment groups are not significantly different. Our second hypothesis, that people with and without experience in System Dynamics will have the same performance, has to be rejected. A significant difference between the performances of experienced people and people with no or little experience exists. A possible reason for this circumstance is that an education in System Dynamics doesnt immediately, but over a longer time horizon, enables people to comprehend dynamic systems. At last, the experimental design will be discussed and several weaknesses will be pointed out.
Keywords: Experiment, Applicability of System Dynamics, Hypothesis Testing, Dynamic Problem, Education, Comprehension
This paper investigates the dynamics of accumulation processes of strategic capabilities in manufacturing, i.e. cost, quality, time orientation and flexibility. The analysis is conducted with the help of an exploratory system dynamics model that represents a hierarchy of these accumulative capabilities. By applying a dynamic view, concepts from the operations management literature are tested and shortcomings are identified. In a further step, the exploratory model is parameterized with empirical data from a large international survey of manufacturing plants. Implications concern the distribution of managerial attention on the different capabilities and its dynamic consequences. The value of this paper lies in the insights gained by the transformation of a verbal model in a quantified simulation model and the learning resulting from simulation experiments.
Formal model analysis tools are essential elements in understanding how structure drives behavior. Conventional model analysis relies heavily on a time-consuming experimental iterative process. Current formal tools are not mature enough for application to most models. This paper presents a loop dominance analysis approach based on eigenvalue elasticity analysis (EEA). EEA, although a potentially strong formal model analysis tool, has drawn criticisms over the years for a number of reasons. The approach proposed in this study attempts to bring proper solutions to the issues raised by those criticisms. To this end, a ten-step procedure is proposed. Among the most prominent features of the proposed procedure is the ability to track the influences of feedback loops on a specific variable of interest. Others include the ability to track the loop dominance dynamics over time and an attempt to the codification of the proposed features of the EEA. The application of the proposed approach is demonstrated using a simple economic long wave model and two other models, all chosen from earlier methodological studies on formal loop dominance analysis. The results of these applications also facilitate the comparison of the proposed approach to other formal model analysis tools.
A new archetype, The Tyranny of Small Steps (TYST) has been observed. Explained through a system dynamics perspective, the archetypical behaviour TYST is an unwanted change to a system through a series of small activities that may be independent from one another. These activities are small enough not to be detected by the surveillance within the system, but significant enough to encroach upon the tolerance zone of the system and compromise the integrity of the system. TYST is an unintentional process that is experienced within the system and made possible by the lack of transparency between an overarching level and a local level where the encroachment is taking place. The Örby case study illustrates a real life manifestation of the TYST archetype in planning. The TYST illustrates the necessity for total transparency in any systems in order to avoid unintended consequence of the archetype. The TYST process may be regarded as a part of wide range of complex systems but depending on the conditions, it can remain dormant, and only become active when the conditions for lack of transparency are fulfilled.