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.