Although the system dynamics literature covers issues of how to construct, analyze, test, validate, and implement dynamic models, surprisingly little attention has been paid to how managers react to and interpret the output from system dynamics models (see Gardiner and Ford, 1980; Rohrbaugh and Anderson, 1979). That is, system dynamicists construct feedback models that are simplifications of a complex reality and then conduct policy tests on these abridged representations. However, decision makers not trained in system dynamics may find that even these allegedly simplified models may be quite complex and difficult to evaluate, since model output typically consists of scores of variables interwoven over time.
With the goal of introducing system dynamics to high school students, a set of six learning packages were written during the 1979-80 academic year under grant number GOD7903439 from the US Office of Education. Co-authors of the material are Nancy Roberts, David Anderson, Ralph Deal, Michael Garet, and William Shaffer. The evaluations from pilot testing done during the grant year in six Greater Boston high schools suggest that the materials indeed can effectively accomplish this introductory role. The teachers involved generally made very positive comments about both the value of system dynamics as an exciting high school project as well as the appropriateness of particular materials.
System Dynamics models have been used extensively for depicting the dynamic behavior which arises from a given underlying feedback structure. In a typical application, a feedback structure is specified, numerical values for model parameters are specified, and then a base-run simulation is conducted. Following the establishment of a Base Case, initial conditions, table functions, constants, policy variables and exogenous inputs are altered; with the resulting impact on model behavior noted and analyzed.
A number of high technology firms have recently reported increasing delays in the development of computer-related hardware and software. Experiencing increasing product development times and schedule overruns, one such company commissioned a system dynamics study of the management of its product development group. The purpose of this study has been to uncover potential sources for rising product development times in the company and to identify those over which management can exercise some control.
Civil Engineer curricula are made up courses. Curricula also lead to degrees and most engineering curricula provide rather narrow time allocation to fundamental categories of course offering. It is usually a tight curricula, designed to be achieved in four calendar years by the good student, five by the average. It is sequestial in nature. The upper limit of course hours is usually a constraint, the addition of new course material must be at the expense of older material. The present curricula are built on science, math, chemistry physics, tools (drafting, surveying, computer programming, statistics), mechanics, dynamics, thermo and materials followed by general engineering and then the various components of civil engineering, such as hydraulics, transportation, sanitary, water resources, structures, materials, etc. This sequence presently produces a B.S. degree holder, ready to emerge on the scene at $18,000 - $30,000/year.
The oil tanker market is interesting from a system dynamics point of view. The market exhibits regularities which appear to be caused by an underlying structure which has been stable for at least 30 years, and probably longer. This seemingly stable structure is primarily the result of the systematic, but not particularly rational, behaviour of the main actor in the oil tanker market: the community of shipowners. The collective effect of their individualistic actions, I believe, is a rather violent and rhythmic development in the market- on a timescale of years to decades. The regularity is, of course, superimposed on a non-recurring pattern of developments caused by events entirely outside the control of the oil tanker community. In this paper I describe the stable structure and discuss what it means for the likely development of the oil tanker market over the next decade.
Stochastic aspects of systems have generally been ignored in most system dynamics studies except for purposes of sensitivity testing. Yet any model that claims to be more than simply an empirical description of a system must treat the underlying stochasticity explicitly in terms of its contribution to the dynamics. Recent work in chemical, biological, and hydrodynamic systems has shown that the aggregation of stochastic effects can lead to novel behavior (self-organization in dissipative systems). In this paper, an analogy between models of these physical and system dynamics models is developed, in which system dynamics models are seen to be an approximation (to lowest order in an expansion in system size) to a stochastic model for the system. The implications of theoretical results derived for the physical system models are evaluated for their application to the system dynamics models. A research strategy to elaborate this to analyzing systems is proposed.
Mini-DYNAMO has been adapted for the Apple II computer operating under Apple’s PASCAL system. Working within the constraints of a micro-computer, Micro-DYNAMO offers surprising capacity and speed. Models with up to 25 active equations will run in tolerable lengths of time, and models with up to 100 active equations can be run, although the time required to simulate them is rather long.
System Dynamics modeling has been used in the formulation and implementation of strategic planning models for nearly five years within the Long Range and Strategic Studies Division of the British Telecommunications Business. This modelling has proceeded in close collaboration with the Department of Control and Management Systems of Cambridge University. The business itself is a public corporation which means that despite a certain degree of autonomy, it is still ultimately dependent upon the Government for approval of its investment plans and also its investment capital.
An experiment was conducted using DYNAMO simulation to gain an understanding of the relation between the structure and behavior for a well-defined family of nonlinear, second-order systems. The result of the empirical investigation was 1) a taxonomy of structures—a categorization of the structures that give rise to all of the possible behavior modes; and 2) a set of observations and precepts—simply stated guidelines gleaned from the taxonomy that relate structure and behavior.