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.
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.
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.
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.
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.
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.
This report builds on a previous epidemiological model of a pneumonic plague outbreak that incorporated three behavioral responses as exogenous drivers and evaluated their importance in allowing us to replicate the actual outbreak (Heinbokel& Potash, ISDC-2003). The current paper describes our subsequent efforts to incorporate those critical and controlling behavioral dimensions into this model as critical feedback loops. We conceptually deconstructed the event into four segments: becoming aware of the outbreak, deciding to act in response, choosing a specific response, and returning to normal behavior. We utilized current psychological theories, such as the Psychometric Paradigm and Brunswiks Lens Model, to build small, conceptually clear, transferable, and combinable behavioral submodels to simulate the first three segments involving information and social networks, social trust, and risk perceptions. We believe these modeling efforts comprise first steps in a critical process of translating current, frequently static, risk theories to dynamically responsive vehicles that can be flexibly and quantitatively applied to reliably aid in understanding and influencing responses to such public health threats, other extreme events, and other dynamic risk scenarios in general.
The use of System Dynamic software tools are becoming a popular way of investigating complex problems. However, along with the use of these tools exists the risk of relying too heavily on the numerical part of the analysis and neglecting the preparation phase for analysis. Any modelling procedure in System Dynamic modelling goes through a conceptual phase that uses the Learning Loop approach. This phase is most often done unintentionally. Using the Learning Loop approach consciously facilitates the group modelling process to acquire four successive phases, i.e. Definition, Clarification, Confirmation and Implementation. This enables a clear structure in the process, from acquiring the task to documenting the results. Only by intentionally using the Learning Loop approach in a managed manner, can the full potential of the process be exploited. Qualitative analysis does not replace simulations with a computer model but simulations should serve as a continuation to reconfirm or refute qualitative hypothesis and a simulation should only occur when the mental model has been tested. Systems Analysis, including its thinking, analysis and dynamics, is not a method, but rather an adaptive learning behaviour. It is a behaviour that finds the optimally adapted method, applying at some times SD computer tools.
Microfinance institutions (MFIs) provide credit, savings, and other financial services to the poor and must successfully manage large volumes of small transactions. SymBanc is a system dynamics simulator designed to introduce students to the complexities of managing a Microfinance Institution (MFI) or to engage experienced practitioners in a discussion of the key determinants of success in such a dynamic environment. The simulator allows students and practitioners to grow an MFI from a single branch to a large network by making a variety of decisions about target market, staffing and facilities, loan and savings product design, and sources of external funding. Detailed feedback enables them to fine-tune their strategies during a simulation. This paper begins with some background on Microfinance Institutions and then presents the structure of the model underlying SymBanc and results of typical simulations. Initial experience using SymBanc and future enhancements contemplated for it are also described.
We were at the Lyons Pub. Peterson walked in with a presentable young man.
This is Randy, she said, pulling up a chair. Hes just back from Egypt. Ordering a beer, Peterson fished a photo from her pocket. Doesnt Randy look grand in front of the Sphinx?
Sedgewick turned to the young man Tell us about your trip.
Randy smiled in recollection. I stayed at Le Meridien in Giza. Costs a bloody fortune, but its worth it. Has a swim-in bar, dont you know.
And the Sphinx? Sedgewick prompted.
Randys expression turned weighty. Big. Damn big.
So youve never actually been to Egypt. Sedgewick said sadly. And, never seen the Sphinx.
Like Randy, many of us return from a model without true insight. In this workshop well deeply explore a model or two. You will see how eigenanalysis complements and speeds traditional approaches to understanding models. Math-phobics and math-lovers are equally welcome.
A number of papers have been published describing various System Dynamics (SD) models of Higher Education institutions and issues, on topics including the role of SD in Corporate Governance, Planning, Resourcing & Budgeting, Teaching Quality, Teaching Practice, Microworlds and Enrolment Demand. This paper builds on previous papers that provided a catalogue and classification of this work in order to highlight potential areas of research in this field of study and to identify system archetypes at different hierarchical levels and discover new ones. This paper therefore presents an updated taxonomy of System Dynamics Models in Higher Education. This paper builds on the earlier taxonomy by widening the scope of the survey of completed SD investigations in higher education management. The findings from these investigations are briefly described. The taxonomy classifies the completed investigations into six specific areas of concern and five hierarchical levels.
This paper proposes a model that gives deeper insights into the dynamics of interorganizational learning at the example of an alliance of two partnering firms. Current alliance research often tends to neglect a feedback-perspective which might be the reason why certain behavioral effects cannot be explained. However, we identify some major feedback-loops that influence interorganizational learning dynamics based on literature-based alliance research. Here, we focus on the concept of common and private benefits. According to literature findings the dilemma between the two kinds of benefits determines how many resources the parent companies invest in the alliance. We show how gatekeepers might lead a learning alliance to common success. We also show how short-term views of potential private benefits might not only lead to failed common goal attainment but also ruin a firms collaborative reputation in the industry.
A number of papers have been published describing various System Dynamics (SD) models of the Information Systems Investment Appraisal Process from several academic and professional viewpoints. This paper builds on previous papers that provided a catalogue and classification of this work in order to highlight potential areas of research in this field of study and to identify system archetypes at different hierarchical levels and discover new ones. This paper therefore presents an updated taxonomy of System Dynamics Models of Information Systems Investment Appraisal. This paper builds on the earlier taxonomy by widening the scope of the survey of completed SD investigations in the field. The findings from these investigations are briefly described. The taxonomy classifies the completed investigations into five specific areas of concern and six viewpoints.
A policy for rapid deployment of fiber-to-the-home may be in direct conflict with the health of the transceiver component supplier industry. The interests of consumers, regulators, and even service providers are in conflict with the industry that provides a critical component necessary for the service. The industry needs to recognize this conflict and explore strategies to keep itself viable in light of these conflicts. A system dynamics model is used to explore the effects of government policy on the deployment of fiber-to-the-home as a broadband technology. Specifically this article investigates the effects of a policy for rapid broadband deployment on the component supplier that is farthest from the consumer in the value chain.
This research tries to offer a design of the cash waqf management system in a system dynamics model. The Cash Waqf Management is expected to become one of the alternative instruments for the poverty alleviation programs in Indonesia. These programs require huge amount of fund that cannot be provided thoroughly by the government. Therefore, initiation of new sources of fund for such a program is inevitable. In the Islamic sosio-economic concept, there is a source of social fund that is economically and politically free of charge, namely cash waqf. In this concept, Nadzir (cash waqf fund manager) collects the fund from Waqif (cash waqf payer) and invest the money in the real sector and in any syariah-based investment opportunities. Nadzir could allocate profits and returns gained from the investments to poverty alleviation programs. Nadzir is obliged to maintain the amount of fund in such a way that it does not go below the initial amount. Therefore, Nadzir not only should be highly capable, but also needs an experienced financial institution in helping SMEs development efforts. Using the system dynamics methodology, we tries to know the structure of cash waqf system and simulate the behaviour of cash waqf model.
This paper describes a systems dynamics model that reflects the possibility of having three levels of complexity together and articulated on a synchronous synergy of all relevant participants of value added systems: the activities at the firm level, networks of industries, and supporting organizations at the regional level. Following a systemic approach, we have identified eight parameters to measure the attractiveness effect of a region: Clustering and associativeness, Value added, Differentiation value, EVA, Attractiveness leverage, Global market coverage, Innovation and Social Capital. Based on these indicators, we have developed dynamic models for emergent industries which have uncertain trends and no previous regional developments. At this moment we are working on models for the Software, Biotechnology, Aerospace and Autoparts Industries that are currently in the process of clustering in the State of Nuevo Leon (Mexico).
This paper uses a system dynamics model to analyze rule compliance in organizations. The analysis takes securities regulation as an illustrative case but applies to other private, nonprofit, and public activities complying with rules overseen by external bodies in the course of producing goods and services. We consider how three levels of behaviorproducers, internal organizational controllers, and external regulatorsinteract in shaping compliance with rules.
This paper explores the history of the Beer Game, its rules, and lessons. By triangulating information from the literature, archival analysis, and interviews with experts in the field, we have identified the main changes in the game over its almost 50-year history. Additionally, an exploration of possible changes to the game and new games in the field of system dynamics are examined.
How can we build dynamic models to effectively inform our research? The System Dynamics method offers established practices and principles to enable us to do so. This boot camp is directed to expose PhD students to the (iterative) SD modeling process.
The workshop consists of two parts. In the first part participants will engage in the process of model building from a case and getting some basic insights. Issues that will be discussed include problem definition, model boundary, scope/level of aggregation, generating insights from modeling, as well as challenging the research question.
The second part of the boot camp will address actual issues from participants research based on the important themes discussed in the first section. For this we ask participants to submit a one/two page summary of their current research, comprising: abstract, research questions, motivation for model and two or three main issues. We encourage submitting models in whatever stage of progress. The summaries should be in at latest on Monday of the conference (though earlier is strongly suggested!). The case material will be available upfront so that the participants read the case before hand.
Note: this workshop does not involve one-on-one coaching that the modeling assistance workshop offers, nor has it the conference setup of the PhD colloquium. These sessions are complementary to each other and participants are encouraged to participate in all of them.
Product development (PD) is a crucial capability for firms in competitive markets. Building on case studies of software development constructed from fieldwork at a large firm, this paper explores the interaction among the different stages of the PD process, the underlying architecture of the product, and the products in the field. The study corroborates the dynamics of tipping into firefighting (Repenning 2001) that follows quality-productivity tradeoffs under pressure. Moreover, we introduce the concept of the adaptation trap, where intendedly functional adaptation of workload can overload the PD organization and force it into firefighting because there is a delay in seeing the additional resource need from the field and underlying code-base. Finally, the study highlights the importance of architecture and underlying product-base in platform-based product development, through their impact on quality of new models under development, as well as resource requirements for bug-fixing. Put together, these dynamics elucidate some of the reasons why PD capability is hard to build and how it erodes. Consequently, we offer hypotheses on the characteristics of the PD process that increase its strategic significance and discuss some practical challenges in the face of these dynamics.
This paper provides an example of a system dynamics model that incorporates soft variables. The model examines the challenges that a superpower faces while maintaining its position in the global economic system. The effects on aggregate welfare of the population at home and abroad, as well as, issues of sustaining authority in the long run are explored through experimentation with a computer model. This theory is an extension of the framework developed by Saeed(1990), which was used to understand political instability and the failure of the government to stay committed to welfare agendas in the
developing countries. The present model captures the interaction between several institutional actors involved with the economic and the governance systems. They include the public, the authoritarian regime, the reformist movements that seek change within the existing framework, and the dissident movements that turn to violent methods.
A novel archetype, abstracted from published work and supported by anecdotal analogies is proposed. Its novelty is evidenced by a comparison with the 'Relative Control' archetype from Wolstenholme's classification. The significant difference is the erasure of the system boundary from 'Relative Control'. The effect is to bring the dynamics entirely within the system thereby creating a 'political' archetype: a structure internalizing the struggle between two opposed policies.
Pressures from human induced climate-change, pollution, and fossil fuel scarcity stimulate interest in alternative fuel vehicles, and in particular hydrogen fuel cell vehicles (HFCVs). The transition from internal combustion engine vehicles to HFCVs is complex as various chicken-egg mechanisms interact in a highly integrated fashion, and the mechanisms are highly non-linear. This paper focuses on one of the most critical chicken-egg problems: the mutualistic dynamics of HFCV adoption and its fueling infrastructure. The effects of local demand-supply interactions on these dynamics are explored in depth. This paper develops a dynamic, behavioral model of vehicle adoption and fueling infrastructure with explicit spatial structure. Simulations are performed for a reduced version. A homogeneous market with strategically locating fuel-station entrants yields fast transition through the formation of adoption clusters (niches). However, under heterogeneous conditions the same micro-mechanisms can counteract the emergence of a sustainable market. Policy implications are significant. This spatial behavioral dynamic model (SBDM) can be used to compare targeted entrance strategies for hydrogen fuel supply. Insights can be used for an aggregate HFCV transition model that includes other mechanisms. Finally, the paper should stimulate a discussion on merits and limitations of spatial modeling as applied to more general socio-economic issues.
This paper discusses a model developed to assess the effects of land-use changes on traffic congestion and air quality. The inputs are characteristics of development and the outputs are time in traffic per capita, and tons of carbon monoxide from vehicles. As previously developed urban dynamics models have done, the model includes a relationship between the output variables and the attractiveness of the area as a place to live. Particular attention is paid in this paper to challenges associated with modeling the relationship between population and land development in urban areas where alternative land-uses are being contemplated. The evolution of an approach to overcoming the challenges is presented.
Though evaluation of public policy and projects of government-to-government assistance are quite common in Japan, evaluator use logical model bases for evaluation that is simple tree type model without incorporate loop or feed back effects. Author has insisting that SD modeling is applicable for quantitative evaluation of public policy but find some difficulty with traditional group model building method. In this paper, we wish to discuss new style SD/ST model building for public policy evaluation.
The researchers attempt to visualize the complexity and dynamic behaviour of SME clusters in Egypt throughout the process of transferring a clusters state from static (idle) to dynamic (productive). This research constitutes the second of two complementary phases of a more comprehensive research that tries to quantify the qualitative measures of dynamic clusters through extending the application of the business dynamics tool to simulate the effect of different cluster-based economic development policy scenarios. After developing the mental model and during the conceptualization phase, the researchers highlighted the key-leverage causal loops showing feedback effects and uncovering the hidden cause effect relationships existing between the most important elements such as trust level inside the cluster, competition and the number of supporting industries. After validating the model, the researchers designed the policy analysis runs and undertook different scenario analysis over a time span of 50 years. Scenario analysis included studying the effect of elements such as institutions for collaboration (IFCs) on cooperation; effect of broker efficiency and success stories on trust building; and effect of trust on learning.
The tourism industry is considered a very important factor that contributes to the economic development Egypt. The industry has shown growth in the recent years in the number of tourist arrivals to reach a maximum of 6 million in 2003. It could not be denied that government efforts contributed to the growth but nevertheless the devaluation of the pound had a significant influence on the number of visitors. The performance of the industry might look fine in general. But, this is if compared to previous performance only. However, if an in-depth look is taken it is realized that the Egyptian tourism is performing far below capacity. This paper aims at explaining the way to improve the performance of the Egyptian tourism industry using a system dynamics methodology. This will be done by defining the main factors affecting the industry, then explaining how the whole system works and finally proposing a new modified model and required course of action.
Dwindling government resources and demands for increased accountability have challenged nonprofit organizations to meet their primary missions while also creating efficient and effective back-office accounting and information systems. Even though many nonprofits say that accounting and information support systems are mission-critical, they tend to staff these systems weakly and to be less efficient than they could be. The present paper uses a system dynamics model to show how the Limits to Growth and Shifting the Burden systems archetypes help explain this situation. The model runs show that the exercise of leadership is the underlying issuenonprofit managers must challenge organizational cultures and mindsets that act as limiting factors, causing the nonprofits to avoid implementing fundamental solutions to their problems. The paper discusses several action recommendations.
In order to determine whether model testing is as useful as suggested by modeling experts, the full battery of model tests recommended by Forrester, Senge, Sterman, and others was applied retrospectively to a complex previously-published system dynamics model. The time required to carry out each type of test was captured, and the benefits that resulted from applying each test was determined subjectively. The resulting benefit to cost ratios are reported. These ratios suggest that rather than focusing primarily on sensitivity testing, modelers should consider other types of model tests such as extreme condition tests and family member tests. The study also finds that all of the different kinds of tests were either moderately useful or very useful--fully supporting the recommendations of the experts. An interesting diagram called a "tornado diagram" is used to portray the results of the sensitivity testing.
The distinctive role of a delocalized peripheral Public Administration is nowadays commonly acknowledged to be mostly consisting in providing services to its community of citizens. In order to accomplish this mission, the local administration has the evident and constant need of a certain cash amount, which should be basically ensured by incomes due to taxes imposed on citizens and that should hopefully require a regular and continuous cash flow. The last aspect represents a condition which usually is absolutely important and even necessary in order to properly and effectively schedule and manage the services that are then to be provided. Thus, in a complex and evolving legislative and administrative context such as the Italian one, this paper will try to state and show, by means of a system dynamics modelling approach, how a financial operation like the securitization of collectable credits performed by local PAs may constitute an efficient, effective and reliable tool in order to support proper and strategic decisions concerning the operation structuring as well as help reduce the collection delay, thus granting the organization with that sufficient liquidity which will be necessary to manage the actual services to the citizens and to program the provision of new ones on a larger time horizon.
Many transportation agencies have discovered that traditional highway contract administration procedures and project delivery methods do not meet current demands. In response, they are turning to alternative contracting. Four trends are perceived in road management. First, with respect to project delivery, more and more projects are contracted for the whole life cycle of the road. Second, contractors are given increasingly more freedom or design space, as the indicators used for monitoring their work become less operational and more performance based. Third, governments follow a dual track strategy; managing a portfolio of directly and indirectly financed projects; dependent on the project characteristics. Fourth, contracts are granted for longer term. These innovative forms of contracting are expected to yield more flexibility in the road sector; more innovation, higher performance and consequently lower costs while keeping up service levels on public values.
This paper presents how by using a combination of institutional economics theory and engineering design theory, our aim is to build a systems dynamics model that can capture the institutional context and is able to indicate what contracting practices are likely to occur and which ones are likely to succeed in view of the meeting the public values and demands.
The aim of this paper is to demonstrate the potential of using the system dynamics computer simulation methodology to gain insight into the dynamic behavior of insurgencies. To this end, a basic model of insurgencies containing the dynamic mechanisms of incident suppression, insurgent creation, and war weariness is developed. The paper then shows how this model, properly adapted, can explain much of the behavior of insurgencies by examining the Anglo-Irish War of 1916-21. Then, to illustrate the potential usefulness of the system dynamics methodology to policy makers, the paper uses the model to determine which system parameters might have most affected the outcome of the Anglo-Irish War. As one example, the simulation suggests that the lack of British governmental legitimacy in Ireland may have hindered the simulated efficacy of insurgency suppression efforts. As another example, the paper shows how the effects of a good works policy might have aided insurgency suppression in Ireland by separating the insurgents from their supporting population. The paper then concludes by proposing how such a model and the system dynamics methodology in general might be developed to assist policy makers manage current insurgencies throughout the world.
The impact of structural adjustment programme on the economic situation in many African countries can not be overemphasised. Over more than a decade of implementing neo-liberal economic policies by the Bretton Woods institution it is of great importance to document the lessons learnt. This paper explains how the expected effect of structural adjustment policies produced unintended effects which cut back the gains of the programme. Using causal analyses, the assumptions and hypotheses implicit in the six main structural adjustment policies are clearly elicited with a causal loop diagram. The paper concludes, though structural adjustment programme was not a complete failure, the policies generally did not deliver the expected promises due to lack of systematic analyses and understanding of the policy responses by stakeholders.
Participatory environmental modeling is an adaptive management tool which natural resource managers, those dependent upon natural resources, property owners, and government agencies may use to help them understand the complexities of ecosystem management. Models have been used for sage-grouse, bear and fishery management, estuary systems and watersheds. These models share adaptive management theory, but differ on many other aspects such as the number of stakeholders and the degree to which they are involved. There can be many levels of involvement that are layered in a representative fashion with the modelers and intensely involved participants at the core. Varying physical, social and economic boundaries and the availability of data affect the time spent on different facets of the process. Finally, the intended use of the model may differ. Some processes are designed around group learning while others create tools which will assist with management decisions.
This paper reports the results of a comparison of quantitative and qualitative approaches to systems analysis. The primary goal of the investigation was to test a heuristic for qualitative analysis previously proposed by the author that is intended to improve recognition of potential sources of failure for models used for forecasting. A series of papers published by John Sterman, George Richardson, and Pål Davidsen in the mid- to late-1980s examining resource estimation methods and the petroleum lifecycle were selected for analysis based on their completeness and perceived high quality of the models both quantitative and qualitative. The quantitative results presented in those papers are compared to published data and some potential sources of deviation are identified. The paper then presents an analysis of the qualitative models contained in the papers, highlighting the differences in the nature of insights available from the qualitative and quantitative analyses and illustrating how this expanded logic for qualitative analysis may contribute to the formulation and bounding process for predictive system dynamic models.
Differences regarding the liberalization of agricultural markets are a central issue in the current Doha-round of WTO negotiations. The positions of the individual countries and country groups differ significantly as far as market access is concerned. The positions can be explained by the existing levels of market support and thus by potential agricultural income losses as a consequence of market liberalization.
The purpose of this paper is to analyze the dynamic impacts of different adjustment steps in market access and the resulting interactions between the agricultural markets. Adjustment steps can consist in an expansion of tariff quotas and in a reduction of import tariffs. Our simulations show that price development and thus the development of the revenue from agricultural products depend on several factors. In addition to domestic supply and demand the temporal design of market liberalisation is a key influencing factor.
This paper describes an interdisciplinary approach to computer modeling of large-scale power systems. System dynamics is used to represent the the feedback relationships which govern the long-term evolution of the system, while engineering methods are used to calculate the short-term prices and power flows in the transmission network. This approach has been implemented in a model of the WECC, the Western Electricity Coordinating Council. The paper uses the WECC model to simulate the impact of the carbon allowances market envsioned by the Climate Stewardship Act of 2003. The simulations indicate that the western electricity system could achieve dramatic reductions in carbon emissions over the next two decades. The preliminary results indicate that the large reduction could be achieved with only half the increase in retail electricity rates that have been predicted for the nation as a whole.
In order to find some effective management policy by the feedback loops analysis of a complex system, we transformed the rate variable fundamental in-tree model of SD to a diagonal-0 branch-vector matrix using the method combining graph theory and algebra to work out there are how many newly gained feedback loops in a SD model when a new management activity was introduced into. We created a SD model of a human resource management in an organization, and using this new method, we proved that there were 16 positive and 17 negative newly gained feedback loops by introducing a new HR management of grade-salary incitement on performance level. We proved that the grade-salary-incitement improved the organizational performance, but on the other hand, it restrained the performance of the organization because of the increasing cost. By analyze the growth limited structure model, we find the policy of using the grade-salary-incitement to increase the performance of both the employees and the organization better.
The various purposes for which a dynamic tasks might be constructed, such as to test for knowledge, teach, or to assist professionals or the lay public in understanding the systems they are dealing with (or part of), are discussed. The idea analysis method is suggested as a means to fit a task to its purpose. Idea analysis entails analysing the task in terms of what basic ideas need to be familiar if one is to be able solve the task. It is just as important to know what knowledge a task does not require as to know what it does require, and if the requirements corresponds to the goal(s) motivating the construction of the task. To provide an example, the Computer Security Incident Response Team (CSIRT) task, a close analogue to the one-stock reindeer management task by Moxnes, is analysed, and several issues of general importance are revealed.
The current work examines the application of system dynamics to real options through work with a major energy firm to apply real options. Five key challenges facing the real options community are presented and potential system dynamics contributions to these challenges are discussed. Two cases from a BP research project illustrate how system dynamics can be used to develop and value real options. The work shows that the use of systems dynamics in real option development and valuation can 1) address key challenges facing the real options community and increase the use of real options in the oil and gas industry 2) allow system dynamicists to offer increased value in developing and valuing flexibility and 3) open system dynamics to new markets of research collaboration and potential clients.
This paper is a challenge to Jay Forresters Urban Dynamics model. The resulting alternative model is compared to Urban Dynamics by running tests of actual U.S. Housing policies.
World - Grid Type, Continuously Under-development - System Dynamics
The main goal of United Nation is realization of sustainable development world society vision. Such society need to integrate social development with economic development and environmental protection. For this end it is necessary to enable sustained economic growth, internalizing externalities and decoupling the range of economic growth from the range of deficit natural resources depletion growth and degradation of environment.
In order to achieve above UN Goal we have to build WORLDWIDE, COMMONLY ACCESSIBLE, SUSTAINABLE DEVELOPMENT-INFORMATION SYSTEM
for:
- comprehensive monitoring,
- far-sighted forecasting, and
- measurable evaluation,
of policy, economy, work, and other changes effects in life-conditions of human-beings and nature in general. This system ought to be built on the base of System Dynamics.
We propose research program, which allows to describe conditions of creation such big, grid type, multi stage built, information system.
We present results from a preliminary system dynamics model of problems in recruiting clients to a hypothetical HIV prevention program. Efforts in HIV prevention emphasize moving programs of demonstrated efficacy to community settings. However, little is known about how these programs interact with contextual elements of service delivery to determine the feasibility of implementation. The section of the model we present here focuses on the stocks and flows associated with attracting, enrolling, and graduating a steady flow of clients into small-group workshops and highlights paradoxes in providing this type of program in the community. We test two policies that either focus on monitoring the recruitment rate or monitoring the graduation rate. Despite its superiority in real-life experiments for producing behavioral change, our model suggests that small-group workshops are a highly inefficient means to change the behavior of a target population over a ten-year period of time.
Balancing responsiveness to market requirements with overall efficiency is an important issue in supply chain design and management. The objective of the system dynamics model introduced in this paper is to capture generic structures and the intrinsic dynamic behaviour modes of supply chains considering aspects of responsiveness and efficiency. The research strives for a better understanding of these aspects: what are the structural consequences of implementing strategies striving for efficiency or responsiveness in the real world, and how can they be represented in a System Dynamics model? Furthermore, simulations will be used to assess the dynamic consequences of these different strategic alternatives. Future research will then focus on identifying policies to balance responsiveness and efficiency in a specific industry and by that resolve the trade-off between the two.
The paper discusses the representation of expectation formation processes in system dynamics. After a brief overview of current behavioural research on expectation formation, it analyses the implicit assumptions that arise from a representation with exponential smoothing and the TREND function. It addresses the limitations of univariate autoregressive algorithms and illustrates their difficulties in representing the causal reasoning processes that may underlie expectation formation. It is argued that exponential smoothing and TREND actually neglect the importance of causal and systemic reasoning and thus are not in line with the paradigm of systems thinking. Finally, three alternative approaches to modelling expectation formation are outlined.
Why is it that some problem solving tasks in organisations though well posed in principle turn out to be incredibly difficult or impossible to solve when taken on in practice? Why is it that after having followed an otherwise ordered and predictable path we often find ourselves suddenly on an increasingly turbulent stretch of road where we realise to our horror that our ability to intervene in the unfolding chaos is rather limited? Yes, complexity theory provides many important insights into the dynamics of complex organisational systems and over the years we have become familiar with terms like bifurcation points, strange attractors and phase transitions. However, given a concrete organisational or engineering problem, their use remains largely metaphorical. In fact, the complex dynamics is assumed to be given and no account is offered about its actual emergence. This paper, therefore, aims to serve as a kind of magnifying glass that helps us to study the emergence of complex behaviour in organisations. Also, it gives an account why complexity often out-steps us in many problem solving tasks.
Two methods for model behavioural analysis are implemented on a simple 2nd order non-linear model. The results of applying Fords behavioral approach are compared with those obtained using both system-wide and variable-specific loop eigenvalue elasticity analysis. Differences in the division of the time span into analysis intervals are identified as are discrepancies in the outcomes. The effort required for implementation and the necessity for automation also differ substantially. We consider Fords method readily understandable, whereas the mathematically more powerful eigenvalue elasticity analysis poses difficulties in this regard. Future directions for research on model behavioural analysis are identified based on the results of this critical comparison and the learning associated with our development of a prototypical automated model behavioural analysis framework.
The systemic approach in studying tourism is firmly accepted in literature because of the complexity of the topic both from the supply side (the heterogeneity of goods and services making the tourist product) and the demand side (not every operator in the tourism network chain has a direct contact with tourists).
To face this complexity the Input-Output analysis, theorized by Wassily Leontief, is widely used in the empirical studies regarding tourism. This methodology, however, gives just a snapshot, even very detailed in some cases, of the economic structure under study but gives very few insights from a dynamic point of view.
To overcome this limitation the Dynamic Input-Output Model (DI-O model), implemented with system dynamics methodology, is introduced in this paper.
Moreover some considerations about the technical sustainability of the production process are made possible by the proposed model.
This workshop will lay the foundation for effective development of large system dynamic modeling projects using Vensim. A key to this development process is the automated combining (merging) of models. Even small system dynamics models can be fairly complex. When the size of the model gets large, such models often become unwieldy, difficult to maintain, and hard to understand by any but the original modeler involved in the development. This workshop will provide specific methods in standardization to alleviate these issues and apply concepts from modern software development practices to system dynamics modeling. Participants will learn techniques for modularization, normalization, and the application of automation tools. While much of the workshop is specific to Vensim, many of the concepts are generic and can be applied to any system dynamics simulation environments.
The cobweb model of competitive market dynamics has been examined in the form of system dynamics model. Separation of the structure elements and introduction of anticipative hyperincursive algorithm was used for transformation of the classical cobweb model to the accelerator based one. The cyclical response of the system that depends on the demand~supply parameters and eigenvalues of the characteristic equation has been numerically examined. The concept of parameter differentiation and time response of the system is transformed to the periodicity concept where periodicity is the main, driven property of the model. As such this is the key attribute in complex discrete agent-based adaptive anticipatory models. The periodic conditions of the model have been analytically determined by the application of z-transform. The periodicity conditions of the initial map have been preserved in the nonlinear case. By the application of the Lyapunov exponents several stability regions of the nonlinear model were numerically determined.
Here, a systems dynamics approach combines the environmental, economic and social aspects of intensive shrimp farming to construct a sustainability forecast. Intensive shrimp farming threatens to cause irreversible damage to water and land resources. High initial investments required are risky to small start-up farmers as ponds are prone to self contamination within a few years. This study is based in Ninh Thuan, one of the poorest regions in Vietnam. Since 1999, local people started to turn to intensive shrimp farming for quick profits. Causal loop diagrams presented focus on the individual shrimp farms and their collective effect at the municipal level. Modelling on the environmental aspect indicates that the current practice of intensive shrimp farming is not sustainable for Ninh Thuan. A combination of lowered stocking densities, pond cleaning and limitation on the land area converted to shrimp ponds will be beneficial for the local community in the long term.
In our study, we looked at how the impact of disruptions may be modelled in a network of chemical manufacturing plants. Given that the number of plants involved is large, it is not time-feasible to model the operation of each plant in detail. However, after 1st round of quick analysis, we can selectively model the identified critical components in greater detail. Hence, the challenge is to develop a standard template that can capture sufficient information about a plant, to give meaningful result. The standard template can be applied to all plants in our study and also allows a non-technical user to easily represent a new plant and integrate into the existing model.
This paper analyses different feedback processes arising from physical and human capital accumulation as well as from technological change, which are considered general factors to promote the growth in any economy by economic literature. A dynamic system is constructed to explain the relative influence of these factors on the rate of economic growth in a generic economy. The development of the model requires to analyse different interactions among variables linked to decisions of the agents that participate in the economy, particularly certain variables associated to the labour market are examined. Using a system dynamics simulation the conditions under which a smaller number of hours devoted to the labour market could imply a greater labour productivity are characterized.
This study investigates the issue of managing quality during production ramp-ups in high-tech supply
chains. It combines an in-depth case study of one particular high-tech supply chain setting with
insights from the recently-emerging literature on behavioral operations and synthesizes these two into
a system dynamics simulation model.
Model analysis suggests that isolated and intuitively appealing quality management policies are
likely to lead to suboptimal or even detrimental results. Of crucial importance is finding the balance
between ramping up production rates sufficiently fast to capture short-lived market demand and
avoiding to increasing production starts so high that workload levels in the supply chain move beyond
the tipping point. This means that when workloads become too high, the entire supply chain can get
bogged down in a vicious cycle of high workloads leading to low quality levels, which lead to high
rework levels and hence to even higher workloads.
Especially promising policies to be used in combination are, firstly, moderate production ramp-up
rates that turn out to generate more timely output than overly aggressive production ramp-ups.
Secondly, policies that leverage the expertise that can be gained from analyzing defective units that
cannot be repaired easily downstream, as these may yield knowledge regarding hidden quality issues
upstream
Many transportation agencies are experimenting with innovative contractual arrangements for the
procurement of construction, maintenance and operation of roads. They are changing from traditional
contracts that prescribe the kind of work that need to be done in a specific section of the network, to
more flexible contracts, increasing the contractors freedom to its maximum level, where the contractor
itself decide which section, when and what kind of work he will perform, with the only condition of
keeping a certain level of performance for a whole road network.
Advanced computer models have been developed that estimate what would be the resulting road
condition for given investment decisions and maintenance actions. Nevertheless it remains uncertain if
contractors are given the freedom: What trade-offs would they make? Will road quality decrease? Will
road agencies be able to monitor or control contractors?
Before all these choices and freedom are transferred to the private sector, it is urgent to develop a clear
view of the most important trade-offs that are now already made by the public authority. In order to
contribute to the building of this understanding this paper explores the issue of road condition and
some of the most the relevant and conflicting aspects of it.
Paper describes an ongoing applied research project at KPN Telecom, the leading mobile and fixed
telephony operator in the Netherlands. The project describes is aimed at developing a collaborative
sales & operations planning business process at KPN that will support the ramp-up of new IP-based
service offerings through KPNs service supply network.
Paper discusses root causes for why coordinating capacity and sales ramp-ups in the various
stages of the chain is far more difficult in service than in manufacturing. Introduces workload as a key
organising concept in collaborative supply chain coordination during ramp-ups. Describes project
findings so far, which are still limited to conceptual simulation model development through group
model-building workshops. Subsequent project results will be incorporated in the paper as these
become available.
A pandemic is likely to occur in the near future, and it could cause significant disruptions in society creating deaths, despair, fear, and monetary cost, among other losses. Firms would also be negatively affected by a pandemic through loss of revenue, profit, employees, and even through a reduction in the value of the business itself. Especially for service-intensive businesses, employee absenteeism is a key factor that impacts firms when a pandemic occurs, hampering various business operations. In this paper, we describe a system dynamics model that describes dynamics of workforce absenteeism resulting from a pandemic, and also effectiveness of corporate mitigation actions.
Technological substitution is the process by which disruptive technologies replace the dominant ones in an industry. Such paradigmatic shifts have a great effect on the strategic planning. The formulations of classical models of diffusion and substitution impose simplification constraints to reach analytical solvability. We use the System Dynamics methodology to build upon existing models by integrating dynamic aspects derived from a broad theoretical framework and to explore the links between social dynamics, technological developments and substitution patterns. Our simulation model generates a substitutive drop in the life cycle: a Sydney opera shape which is not replicated by classical models but which is substantiated by empirical data from the successive generations of DRAM. The generic structure can generate the dynamics of a sailing ship effect and account for the non-uniformity of interpersonal communications. The more general theory embodied in the model allows to better understand the underlying dynamics of technological substitutions.
Adaptive requirements are system requirements that change either internally, or externally in the environment, where environment includes the users and other systems interacting with the subject system. Modeling and analyzing adaptive requirements are important because change is a ubiquitous phenomenon in social-technical systems. Engineering adaptive requirements is also difficult because many contextual factors need to be taken account of, and some of these factors (e.g., human intentional changes) are hard to quantify. This paper investigates an approach to modeling adaptive requirements by integrating system dynamics modeling into i* goal-oriented modeling. We illustrate that each modeling method has its advantages that are difficult or impossible to achieve using the other method, and each has its limitations that can be overcome using the other method. We then propose a goal-oriented adaptive requirements engineering (GARE) approach that integrates desirable features of system dynamics into i*, taking advantage of the goal-oriented modeling initiatives in i* and the built-in constructs in system dynamics for modeling time-based system evolution and adaptation.
Despite the availability of policy tools to mitigate property damage, relief costs for disasters continue to rise. This paper presents a framework for analyzing flood mitigation policies and policy design challenges in the United States. The system dynamics model prepared for this research was developed from qualitative data collected from over 300 sources, including the extant literature on natural disasters, statements made by disaster experts, government documents, policy analyses, and federal disaster mitigation policies. The generic structure developed for this research, the flood-1 model, explains the dynamics of major pressures in any flood-prone community. Eleven policies were analyzed against three scenarios to show the benefits and burdens of several types of mitigation policies. The policies selected in this analysis reflect the incentives established in the federal governments Community Rating System (CRS). In this paper, I show how the system dynamics model was used as a theoretical framework and policy analysis tool to explain the policy design challenges in every flood-prone community.
Women have comprised over half of US university students since the 1980s. Women make up 45% of the US workforce. However women are poorly represented in senior and leadership positions both in industry and on university faculties. Only 16% of corporate officers and only 2% of CEOs at major companies are women. If increasing numbers of women have been in the pipeline for over 25 years should more have emerged at the other end as leaders? A simple model indicates that the pipeline delay hypothesis is not sufficient to explain the relatively small numbers of women in senior and leadership roles.