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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
As New Year rolls in, many of us take on challenge of personal change. Many set goals to lose weight; do more exercises; watch less television; do more studying; do less partying; or to shed a habit such as smoking. For several years in our Quality Management course students were asked to work on a term-long personal continuous improvement projects. The students were briefly introduced to basic concepts of causal loop diagrams and were encouraged to use them to clarify their theories regarding their own progress or lack of it. The basic premise is that the result students obtain and the dynamics they experience are built into the structure of their worldview and they learn if they can communicate and influence their worldview. This paper uses systems thinking lens to discuss the improvement framework and the experience reported by students. Majority of students did not make the progress toward their goals as much as they would have preferred. The student generated diagrams to explain their theories were either too simple or overly complicated, awkward and partially flawed. However, it can be claimed that the process of using the tool to clarify their thinking itself was worthwhile. After reviewing their narratives and the diagrams, several archetypes were consistently noted.
The Advanced Fuel Cycle Initiative is developing a system dynamics model as part of their broad systems analysis of future nuclear energy in the United States. The model will be used to analyze and compare various proposed technology deployment scenarios. The model will also give a better understanding of the linkages between the various components of the nuclear fuel cycle that includes uranium resources, reactor number and mix, nuclear fuel type and waste management. Each of these components is tightly connected to the nuclear fuel cycle but usually analyzed in isolation of the other parts. This model will attempt to bridge these components into a single model for analysis. This work is part of a multi-national laboratory effort between Argonne National Laboratory, Idaho National Laboratory and United States Department of Energy. This paper summarizes the basics of the system dynamics model and looks at some results from the model.