A panel of business and industry practitioners will describe how they have and hope to use system dynamics in their organizations. They will discuss which issues they have addressed with system dynamics and also share their perspective on what have been their biggest challenges and most significant successes.
This paper presents insights from an interactive seminar game using system dynamics to help the U.S. Latin American policy community explore issues associated with the process of paramilitary demobilization in Colombia. The game used system dynamics to represent the strategic interactions of the key actors in the Colombian paramilitary peace process, including their pursuit of both competing and complimentary goals. The process leveraged the gaming mode and rapid causal tracing capabilities of the Vensim system dynamics software to generate an interactive event in which players generated a rich set of strategic interactions in a hands-on learning environment. The success of the event suggests a promising new approach for leveraging the power of systems thinking and system dynamics software in policymaking and learning environments.
Health care is a complex dynamic setting suitable for system dynamics analyses. The method has the potential to be an important quality improvement tool in the near future. However, it will be necessary to develop the models beyond the pure production model focus on the clinical care process from a patent perspective and in doing so it is inevitable that variables such as health, communication and care planning are involved. Consequently, useful and valid models for modern health care must involve variables that are unfairly designated as intangible. The present paper describes an exploratory system dynamics model of the care planning process. It draws on a range of studies and theories about the process. The paper discusses how it could be possible to incorporate and validate variables alongside the more traditional way.
The rapid spread of HIV/AIDS is a global crisis one that is particularly devastating to the economies of nations where the disease is most prevalent. Booz Allen Hamilton, in conjunction with the Global Business Coalition on HIV/AIDS (GBC) and the Confederation of Indian Industry (CII), developed an innovative approach for The AIDS Epidemic in India: A Strategic Simulation. Their approach captures the complex interdependencies that drive the HIV/AIDS epidemic and its economic consequences. At the core of this strategic simulation is an analytic framework that leverages epidemiological and economic System Dynamics modeling, partnerships with leading academic centers, and simulation-driven gaming.
Access to energy, particularly through clean and modern technology, can make substantial contributions to promote rural development in the poor areas of developing countries. However, the relationship between energy, poverty alleviation and sustainable development is still unclear. Additionally, while improving access to energy is required for development, the way that this has been supplied has not always warranted a sustained livelihood in rural areas.
With the purpose of gaining a better understanding of the relation between energy and development, the current research Renewable Energy for Sustainable Livelihoods-RESURL, aims to assess and measure the factors that contribute or hinder the development of efficient, viable and appropriate access to energy provision in remote rural areas by using a multidisciplinary and participative perspective.
A System Dynamics model is constructed to evaluate the contribution of energy to rural livelihoods. SD modeling facilitates understanding feedback and control processes, as well as delays in decision making. Simulations show how isolated communities in conditions of poverty could attain a satisfactory level of human, social, physical and financial development by making sustainable use of their natural resources through energy technologies. The study draws on the sustainable livelihoods approach as a framework for assessing community assets and capacities.
System Dynamics simulation models of organizational business system of management of material (raw-materials, orders, money, labor, personnel, population, capital equipment: tools, units and factories e.t.c.) and informational flows in productive company will be presented in this paper. Organizational business-production system is simulated by effective scientific discipline System Dynamic and realized by Dynamo (PD4) and PowerSim program packages, also.
Due to complexity and extensiveness of business management of organizational business process or production-distribution system global simulation models of companies are presented on the modular way, i.e. with seven relevant sub systems:
1. Production-inventory sub system;
2. Credits sub system;
3. Debits sub system;
4. Sub system of productive capacities;
5. Sub system of Cash-Flow;
6. Gross income-net income sub system;
7. Sub system of demand for organization products,
which are common structural characteristic in every productive business organization. These sub system are modelled according to its specific quality.
The paper is conceived as follows: sub systems of business production organization, entire model of productive organization system and its simulation, conclusion and used references.
Multiple Objective Optimisation (MOO) is a proven technique that can be employed by systems dynamicists as they seek to optimise parameters in simulation models. MOO employs genetic algorithms and Pareto-based ranking to find non-dominating sets of optimal solutions to problems that have more than one objective. The aim of this workshop is to: (1) Explain the multiple objective optimisation approach; (2) Show, though an interactive simulation model, how it can be applied to a popular system dynamics model (a two actor version of the beer game); (3) To explore with participants answers to a number of questions, including: (a) What kind of benefits can MOO bring over traditional optimisation approaches? (b) How do modellers decide on the appropriate payoff function? (c) How do decision makers approach the dilemmas of trading off two objectives? All participants will have access to a special purpose simulation application (Windows based) that will allow them to run simulations and optimisations on the two-agent beer game.
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.
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.
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.