A multi-sector, input-output version of Sterman's simple Long Wave Model is developed to investigate the validity of the capital self-ordering theory for a more realistic system with diverse capital types. Simulation experiments with varying capital lifetimes and input-output coefficients tend to reproduce the characteristic fluctuations in capital production, caused by self-ordering, with a period in the 30 to 70 year range. However, complex patterns of oscillation with wide variance in period can emerge, explained by varying dominance of self-ordering loops. The analysis thus confirms the destabilizing effect of self-ordering and its significance for long term fluctuations while raising issues and generating new insights about the-long wave.
The System Dynamics Generalized Substitution Modeling is presented. This modeling considered the influence factors of circumstance by introducting action function. The methodelogy is based on the System Dynamics with econometrics, combining three postulates in product substitution and decomposing multi-product into several two-product substitution. Parameter estimation, which existed in all System Dynamics Modelings, is one important but still unsolved problem. Now this problem has been solved in our paper by orthogonal simulation, it is based on the orthogonal theory and generalized least squares (GLS)
China has the greatest population in the world. The impact of the population on Chinese economic development is great. Based on Chinese National Economic Model NATN3, the relationship between the population control policy in China and Chinese economic development are obtained by simulation of the policy analysis.
The long term success of System Dynamics is largely dependent upon the dissemination of systems thinking to a considerable segment of the general public. A strategy for exposing a non-academic, adult audience to the basic characteristics of systems is developed, using the ADAPT Learning Cycle, System Dynamics, and the Social Fabric Matrix.
In the past, the most popular computer models for the construction management of major buildings were large models based on the graph theory and their consequent discrete event simulation on the mainframe computer to have a view of the operational level. We think that in the future if we want to remain competitive on the world market the trend will be the use of small system dynamics generic models in relation to micro-computers at the strategic management level that can generate the reference modes i.e. the project control baselines.
This paper presents a computerized system dynamics game in which the player makes "annual" decisions controlling the availability and evaluation of a new medical product with uncertain potential and possible (though initially undetected) side effects. The game has been implemented using the popular spreadsheet program Lotus 1-2-3. This program has on-screen display capabilities allowing for the construction of a user-friendly game that requires no knowledge of system dynamics. A detailed discussion of game mechanics is followed by a description of a classroom experience which led to further development of the original version of the game and some general insights about game-building.
Within the MIT System Dynamics National Model, the risk-free interest rate is determined jointly by the normal interest rate and by liquidity. The normal rate is the rate which agents believe would obtain under normal circumstances, in the absence of transitory pressures. The normal rate continually adjusts to new interest rate conditions. During times of deficient liquidity, agents will increase the risk-free rate above the normal rate. The converse also holds. The risk-free rate will continue to adjust until pressures in the system are relaxed. Estimation results support the national model theory of interest rate formation.
Although there are more than 3000 end uses of aluminium in the world and more than 300 in India, yet there are five sectors viz. power, consumer durables, transport, building consturction canning and packaging which account for more than 90% of aluminium consumption. To study the dynamics of demand of aluminium in these sectors, system dynamics model having various sectors viz. Population, economy, power, consumer durables, construction, packaging and canning, transport and aluminium consumption model has been simulated from 1970 to 2000 A.D. using dynamo.
“Generic models,” as the term is emerging, denotes a model representing the underlying causes of commonly occuring sets of problems, whose purpose is for education, rather than for policy analysis per se. Preliminary uses of generic models have been an exciting and efficient means of transmitting insights. This paper is a status report on the modeling of a company's conversion to a new production or product technology. Based on information sources including in-depth interviews within such companies, the authors' previous experiences, and published surveys and cases, the planned model focuses on management goals, staffing, and acquisitions of the skills necessary to deal with the new technology or product. Although the model does not explain every (complete or partial) implementation failure, it seems relevant to a significant fraction of such failures. The authors intend to develop the model and curriculum materials for management education and portions of university courses on technology management.
This paper presents the findings of my research in artificial intelligence applications for system dynamics. The sudden appearance of microcomputers in homes, schools, and businesses has opened an opportunity for dissemination of system dynamics to a wider audience than we could have ever hope to reach with the earlier computer technologies. This opportunity should not be lost by clinging to obsolete, or soon to be obsolete, technologies. User-friendly micro-based software should be immediately available to those individuals, schools, and corporations who are interested in systems thinking. The demand for such systems far surpasses the current supply. Artificial Intelligence software is now available for microcomputers. This new software development can significantly improve current and future systems for the novice and the experienced system dynamicist.