In response to the need for an integrated look at the problems of electric utilities, Pugh-Roberts Associates, Inc. has developed a strategic planning model for electric utilities. In various forms, it has been used by utility industry investors, by individual utilities, and by research organizations for analyzing alternative investment, management, and regulatory strategies.
The application of management science techniques to problems of managing libraries has been a relatively recent development. The paper describes construction, development, and application of an interactive System Dynamics computer simulation model to a large university library system. Actual experience gained in developing and applying this System Dynamics model is reported. Operational tactics and strategies a library might be considering in it's daily operation are simulated and evaluated. Possible improvements to this model are also discussed.
Validation testing provides the tool for building confidence in a model. It enables an analyst to verify the correctness and usefulness of a model and to gain better insight into, and understanding of, the system being modeled. Although important, validation testing is sometimes difficult to conduct. This paper presents the author’s experiences with using the model validation tests to validate a system dynamics model. The paper describes the tests and applications that were most useful in examining the validity of the model, identifies difficulties that can arise during validation testing and offers suggestions for reducing their impact on the process of model validation.
This paper compares and contrasts the philosophical and methodological paradigms used by psychologists and system dynamicists. Currently, psychologists collect huge amounts of data, use open loop methods of experimental design, and think that classical statistical models, such as analysis of variance and regression analysis, provide the most useful methods for studying social phenomina. Behavioral approaches to psychology differ sharply with the system dynamicists concerning the relative importance of external vs. internal sources of influence on behavior.The behaviorists focus on controlling the external environment, even denying the existance or importance of internal states. The problems of using external control are illustrate by contrasting two simple attitude change models; one which modifies attitudes solely through outside influences and another which makes the change in attitudes a function of the state variables. System dynamicists attempt to understand the dynamics of social processes through the study and analysis of dynamic loop structure. These techniques would be extremely useful for those psychologists using correlational analysis and causal modeling methods, where the implications of dynamic structure are not always fully understood.
The System Dynamics Method has been applied to simulate the flow of production in a steel plant. This model has been designed to be an aid in long term planning. The model is driven by a time variant input i.e. incoming orders of nine different types of finished steel products. The internal dynamics is generated by six negative feed back loops of a production shop. The material flow takes place through 16 such shops each having its own dynamics which gets induced to other shops as material flows from coke ovens to finishing mills. The model makes explicit the environmental influences, policy parameters and their relationships with production. Together these explain the dynamic behaviour of monthly production. It can now be used to experiment with all that can be thought of to influence the parameters and improve upon the production performance of the steel plant. The extended version of this model which includes the financial aspects is a top management laboratory for experimentation with different scenarios of environmental influences and counteracting strategies.
The paper concludes that the general models of business performance should greatly benefit from analysis within a dynamic framework. The work has already indicated possible relationships between existing theories and formed the basis of a simulation model which may identify the possible consequences of certain strategic actions combined with alternative organization structures.
This paper presents the discussion and the application of system dynamic methodology to study the consequences of government regulations on small surface coal operators. In 1977 Congress promulgated the surface Mining and Reclamation Act, which brought about some critical changes such as lengthy and costly permit application procedures, lengthy local and state review of permits and lands, increased bond fees and costly reclamation requirements. Small surface coal operators appeared to be particularly vulnerable. Policies frequently considered by the surface mining industry and the government to alleviate the hardship caused by the regulations are mechanisms to offset increased bond fees. It is a purpose of this paper to demonstrate the utility of system dynamics as any effective methodology to study the long term effects of such policies.
The strengths of the SD approach are as follows: explicit use of causal relations, the admission of qualitative information into the model and the potential for methodological ‘merges’. The drawback of the methodology is that it is difficult for the uninitiated and considerable effort is required in the modeling of SD. The purpose of strategic planning is to find a new product/market combination which accurately reflects the company’s strengths and weaknesses. In our case the SD community is the “company’; the methodology of SD is the product and different types of models correspond to market areas.
This paper presents a system dynamics model of human factors in the implementation of office automation in the Job Service. The model includes sectors representing model acceptance by managers, supervisors, professionals, and clerks with the various factors impacting on such acceptance. Since the perceived usefulness of the automated system for office performance is quite important (especially for managers), sectors representing workflow and efficiency are also included.
Proper data management is an essential component of system dynamic modeling. The authors have developed an approach to data management, as set forth in this article. The article first describes the modeling and data management activities from a critical path point of view. The approach to handling the data associated activities is then developed. This approach asserts the following: 1. it is appropriate to address data relates activities at each stage of the model development process, and 2. when properly linked, a synergism exists between each model development stage and its associated data handling activity. It is claimed that this approach, including sequenced data handling and synergism between data and modeling activities, can produce a more comprehensive and timely model.
The most basic problem of sociology as an empirical science is the difficulty of replicating studies within reasonable time limits and in genuinely comparable conditions. Sociologists aspire to make correct predictions based on verifiable statements about causal relationships, but cannot, the nature of macro-social phenomena precluding experimental designs with adequate controls. System Dynamics promises a way out of this dilemma. Four things need to be done. (1) Formulate the sociological theory as a causal loop diagram, making all causal reasoning explicit. (2) State what variables are involved in the functioning of the system. Calibrate the model until it is internally consistent. (3) Refine and adjust the constants until the model can reproduce a known time-series of relevant data. Repeat this on number of data-sets. (4) Systematically vary each constant in turn while controlling for the others. This is, in fact, the quasi-experimental procedure for testing the conditions under which the theory will stand or fall, and why. An illustrative example of the proposed strategy is presented, with encouraging results.
This paper discusses an approach to model refinement which involves testing the behavior of individual pieces of a model in response to empirical input data for comparison with empirical output data. Partial-model tests should be used for selecting formulations or estimating parameters only when appropriate case-specific or logical information is not available for this purpose. The smaller the model components used for partial-model testing, the more likely it is that the model will prove useful for anticipating events outside the historical experience and the less likely it is that observed behavior will be incorrectly attributed to certain relationships or parameters. Thus, from the standpoint of structural validity, partial-model testing is an improvement over whole-model testing for the purpose of structural adjustment. The paper presents a detailed example of partial-model testing in the context of a generic model of the evolving use of a new medical technology. Specifically, the technique is used for adjusting and validating a model subsystem that can explain why the reporting of clinical information on cardiac pacemakers has been marked by regular oscillations over time.
It is envisaged that although the rabies system is a special case whereby there is no recovery from the disease, the principles generated by the analysis may be applicable to epidemiology in general. Such applications providing a definition of a disease system such that effective control policies may be elucidated. The work presented here is complete in itself forming a qualitative analysis of the system. It also provides the basis for a quantitative analysis using a derived computer simulation model.
The paper is concerned with describing an investigation of information usage in the control of colliery operations. The premise of the work is that to make the most of new information retrieval technology currently being installed in collieries research is needed to provide compatible advances in the methods of information usage. The approach adopted was to construct a continuous simulation model using system dynamics capable of providing a laboratory assessment of alternative managerial control policies based on alternative sources and levels of aggregation of information. The model developed represents a typical colliery situation composed of three working coalfaces and incorporating planning production, development and manpower sectors. The face sectors transform coal reserves to mined coal output, under manpower constraints and geological shocks, and these are all interlinked by means of allocation policies for manpower and shifts. A range of policies for for the exercise of control through these allocations are considered subject to a range of shocks. It is concluded that, although there are difficulties in designing single policies which are universally best, there are clear advantages associated with fully integrated colliery policies based on information inputs from all aspects of the operations.
Among the most stable phase relationships between economic variables is that between money, the change in money, and general economic activity. Both the change in money and money itself lead production over the business cycle. This relationship buttressed with results of the Granger/Sims test for causality, has been used to support the notion that money causes real activity. This notion, in turn, is used to argue both that monetary policy causes the business cycle and that monetary policy can ameliorate the business cycle. This paper examines a hypothesis for the phase relationships which assume that money does not cause real activity, but, rather, real activity causes money. According to the hypothesis inventory assessment, which leads business activity, induces corporate borrowing, which in turn causes a money expansion with a lead similar to that observed. This has been a working hypothesis for the phasing in money of the System Dynamics National Model project. It is concluded that the hypothesis, by itself, is insufficient to account for the observed timing relationships. However, the inventory investment hypothesis combined with additional hypotheses such as a mechanism for household portfolio adjustment, can account for the phasing. These results do not depend on a causal flow from money to real activity. As a consequence, business cycle phase relationships should not be taken to imply money causes the business cycle nor that monetary policy can influence the business cycle.
A process-theoretic approach, seldom used but not without promise for organizational behavior research, is employed to postulate a process model of the natural logic evident in organizational policy making. The model is used to explain how the policies of a sample firm (for which twenty years of data are available) became adopted and how, together with critical events, this caused the firm to evolve in particular directions rather than others. Implications of the study are put forward in terms of identifying the pathologies of the policy making process. Some prescriptions are put forward for the proper control of organizations by supervisory bodies, such as boards of directors. It is suggested that Management Science, in the form of systematic procedures for adaptive organizational design and updatable cause maps, may have an important future role to play in senior management affairs. Questions are raised for government and society concerning sustaining and regulating firms in both the public and private sectors in the light of the study.
A steel demand model consisting of 15 sub-sectors was formulated by the authors to dynamically estimate the steel demand from GNP per capita. Attempt is now being made to develop a more general consumer demand model specific to India, which, among other things, takes into consideration inflation as caused by increase in money supply to finance development plans of the country, remittances from expatriate workers, foreign loans, and wage increase to increase in production ratio. Existing model has been further modified by giving due weightage to the effect of income distribution among low, middle and high income groups of population on the dynamics of demand. Attempt has also been made to study the sensitivity of the economy, and hence the consumer demand, to changes in the saving to consumption ratio. The positive effect of increase in saving on capital formation on the one side, and negative effect of decrease in demand on the other side, has been discussed.
For four years, the authers have been studying agricultural products markets with this year a development on lumber market. Search goals are not only to understand market working processes but also to define for each of then the M.I.S. necessary to permit some control by interprofessional organisations specially on price levels. The paper presents in a first step two building model approaches: One is a pragmatic approach, formalised by Buffa, Cuzo, Bonini, Boulden, Cetenick, Rosenzweig, on San Diego meeting, A.M.A., in 1970, the other is a theoretical approach by Bross, Schoderbeck, New -York in 1971, and Kaplan, Scranton in 1964. In a second type, the use of System Dynamics approach is confronted with these two first methods specially on noted research area, In conclusion, results of our models are discussed.
An experimental software package is being used as an extension to the DYNAMO IV compiler to linearize the model at any point during a simulation, compute the eigenvalues and eigenvectors of the linearized system, identify the levels important in producing each behavior mode, and compute the elasticity of a given eigenvalue (corresponding to elasticiy of period and damping) with respect to all model parameters. The package is intended to help modelers understand the causes of behavior in very complex models, both for debugging implausible behavior, and for presenting the causes of plausible behavior more convincingly. The package is able to work for the System Dynamics National Model, a model of around 300 levels. Practical experience has uncovered some difficulties in making the analysis useful,, but these are being surmounted. The experience suggests that mathematical methods should be used extensively “in the field” before being offered as candidates for expanding the paradigm of System Dynamics modeling.
A number of challenges face firms that need to decide when and whether to convert from technologies to new computer-based technologies. Such is the case with lithographic setup shops, which prepare photos for color printing; they must choose between continuing with traditional craft methods or acquiring digital image-processing equipment. Pioneering firms can be saddled with experimental, undependable, and expensive prototype systems. Rapid technological changes still occurring in digital systems can allow competitors who invest later to obtain cheaper, more effective equipment. But firms investing later may find themselves paying for the large investment just when most competitors are established in the new technology and competition has forced prices and profits to low levels.In order to create an organizing framework for analyzing and developing conversion strategies for these firms, we worked in collaboration with Inter/Consult, the project's sponsor, to build a system dynamics model of the color process industry, its market, and a typical firm. The primary purpose of the moel is to provide a clear understanding of the impact these major capital investments will have on the profit structure of lithographic setup shops and to help these shops develop effective conversion strategies. A secondary purpose of the model is to aid digital image-processing equipment suppliers in understanding their market and to provide them with a toll for generating alternative scenarios given different assumptions about economic trends, technological developments, prices, market size and composition. The model serves as a strategy support system that allows clients to derive scenarios explicitly from causal assumptions and to evaluate alternative investment strategies.
Several interactive computer graphics technologies are now available that can provide powerful tools which enhance our ability to conceptualize, implement, and communicate complicated system dynamics model structure and behavior thereby giving us opportunities to improve our effectiveness as researchers, consultants and educators. This paper gives an overview of several projects utilizing interactive computer graphics and evaluates their significance for system dynamics. Included in this discussion are: 1) computer aided design systems for “automagic” design and updating of overview, policy structure, flow, and causal loop diagrams, 2) computer teaching games and self-paced interactive computer aided instruction packages designed for personal computers; 3) review of the new Micro-DYNAMO and Hewlett-Packard plotting software from Pugh-Roberts, 4) computer networks, computer conference based academic programs for the general public, and network indexed video cassette extension libraries of system dynamics presentations and seminars; 5) interactive computer driven video disk processors with touch sensitive screens allowing a modeller multimodal access to overview, subsystem, policy-structure, causal loop and flow diagrams, table functions, documentors, and DYNAMO equations on the same system; and 6) two- and three- dimensional representations and animations of model behavior on multicolor dynamic displays driven by computer and video disks. These developments are assessed with respect to their possible contribution to the growth of system dynamics as a field, dissemination of system dynamics methodologies and to the implementation of policy recommendations. Because of falling prices for software and hardware, the explosion in interest in personal computers, the exponential growth in their functionality, and the current state of the field, we believe the next two decades will be the phase of most rapid growth for system dynamics.
In 1981 a preliminary system dynamics model was developed for the Norwegian State Railways to study passenger and freight traffic for the complete network. In addition, a particular model was developed to study commuter traffic in Oslo. This paper describes modeling work done for the Norwegian State Railways (NSB).
Certain medical interventions may result in reducesd costs to society. Others, however, by keeping people alive longer, may cause higher costs to be incurred for continuing health care and disability and retirement payments. A generic disease process model for projecting the implications of various medical interventions is presented. The model is applied to myocardial infarction in the U.S. male population and results of simulating several interventions specific to that disease process are discussed. Conclusions are drawn and it is argued that this model is useful for identifying interventions that result in higher costs to society in order that adequate resources be set aside to cover these costs. The work reported in this paper was funded by a grant from the Kaiser Family Foundation.
The model described in this report is meant to show how some of the practical problems of combining hydrological and biological processes can be addressed, how models can be used to examine specific questions, and along what lines the present model ought to be developed to eventually arrive at a useful policy tool.
At the last System Dynamics research conference held in the United States, we presented a paper which described a computer simulation model of an elementary school. The purpose of the model was to examine the structural differences between schools which are effective and ineffective for what we have come to call “initially low-achieving children.” In that paper (Clauset & Gaynor, 1981), in a subsequent paper (Clauset and Gaynor, 1982), and in a book manuscript (Clauset and Gaynor, in preparation), we have described in varying degrees of details tests which examined a number of school improvement policies. Policies testes included the following: Changing policies affection time allocations, Improving teacher skills, Encouraging teachers to place more emphasis on low achievers, Raising teacher expectations for low-achievers, Improving classroom of school-wide behavior, Changing class size, Changing the demographics of the student body (e.g., size low achievers).
This paper will address the relative utility of employing the linguistic structure used by system dynamics compared to translating the modeler’s perception of reality into other symbolic language systems. The first section will review the relation of language to the method of scientific inquiry. This will include a discussion of the debate over the problem of evaluating policy alternatives of social systems. The final section of the paper will specifically identify some of the differences between the imposed linguistic structure of system dynamic models and the symbolic language systems often employed in orthodox economic analysis.
Eigenvalue analysis of dominant feedback loops promises to be a powerful new tool for identifying the structural origins of behavior in system dynamics models. Traditional simulation methods for dominant loop analysis are time-consuming and error-prone. A new technique permits calculating the marginal contribution of each feedback loop to each mode of behavior in a model. The technique computes the numbers showing the percentage change in natural frequency and damping of each eigenvalue resulting from a one percent change in loop gain. The magnitude of an elasticity measures the overall importance of a loop to a mode of behavior. The magnitudes can be used to rank loops by relative dominance over each mode, or to rank; modes by relative importance to each loop. The techniques can be used to analyze both linear and some nonlinear behavior modes.
Sensitivity testing, according to the glossary of terms in a Congressional manual on simulation modeling, is defined as the “running of a simulation model by successively changing the states of the system…and comparing the model outputs to determine the effects of these changes” (Congress 1975, p. 129). Sensitivity testing is generally viewed as an important part of the modeling process because it helps researchers narrow down those areas where more data gathering would be useful. In our introductory remarks, we argue that detailed sensitivity testing is particularly important in system dynamics modeling efforts, and we list several obstacles that make detailed sensitivity testing difficult. We introduce a set of testing procedures developed at the Los Alamos National Laboratory and verified by the Control Data Corporation that can help system dynamicists perform detailed sensitivity testing on a routine basis. In the body of the paper, we present an illustrative application of the testing procedures, and we list six specific uses of the procedures. We describe the availability of the testing package, and we conclude with a set of practical guidelines for investigators wishing to make use of this unique set of procedures.
As a step towards increasing our understanding of the dynamics of growth in solar markets, a simlpe generic System Dynamics model describing market penetration by a characteristic renewable energy technology is employed. The analysis demonstrates that for some classes of renewable energy, incentives are now adequate to provide for the necessary rates of growth. Technologies with slightly different features in our model are never able to sustain themselves in the market, no matter what federal subsidies they receive. A third group of solar technologies still needs support, even though it will evolve to become very competitive in the market without any subsidies as little as a decade from now. Relatively modest federal supports of these technologies now can bring them quickly to levels where they are economically, environmentally, and socially attractive energy options that provide significant oil savings. For these technologies federal support through initial stages of commercialization would be appropriate.
In this paper we outline and evaluate a simple technique for analyzing the ability of a model to reproduce an oscillatory behavior mode. The technique consists of using a model as a predictor, and then performing spectral analysis on the prediction errors. The technique is referred to as the spectral analysis of residuals or SAR test. The paper motivates the use of prediction residuals and illustrates the technique with a simple model of inventory oscillation. The SAR test appears to yield a substantial amount of information about the performance of a model. However, the technique breaks down if the observed behavior is a result of the system being subjected to shocks with similar dynamic characteristics to the system output or if the system has more than one set of mechanisms generating the behavior of interest. The SAR test is not capable of distinguishing between models which can explain the behavior equally well using different state space representations.
The aircraft survivability model developed is comprised of five submodels: 1) Economy Submodel, 2) Budget Submodel, 3) Procurement Submodel, 4) Attrition Submodel, and 5) Survivability Submodel. The economy submodel generates the annual “Gross National Product” of the United States and “Federal Government Budget”. The budget Submodel uses the military output of the economy Submodel to determine the “Department of Defense Military Budget”. The DOD budget is broken down by service and function (Procurement, Operations and Maintenance, and RDT&E). In the Procurement Submodel, the “Procurement Budget for combat Aircraft” determined in the Budget Submodel is used to generate the parameters: “Acquisition Budget for Combat Aircraft” and “Modification Budget for Combat Aircraft”. The outputs of this submodel are the “Procurement Rate for Combat Aircraft”, and the “Modification Rate for Combat Aircraft”. The Attrition Submodel acts on the inventory of “Combat Aircraft” in the event of war. The number of combat aircraft increased by the outputs of the Procurement Submodel over years of peacetime are reduced in wartime through the “Attrition rate for Combat Aircraft”, which depends on the number of “Combat Aircraft”, the “Sortie Rate for Combat Aircraft”, “Mission Survivability for Combat Aircraft”, and the “Availability of Combat Aircraft”. The Survivability Submodel outputs are the “Mission Survivability for Combat Aircraft” and the “Availability of Combat Aircraft”. The former is the product of the “Susceptibility of Combat Aircraft” and “Vulnerability of Combat Aircraft”, both of which depend on the magnitude of the “Aircraft Survivability RDT&E Budget” outputed from the Budget Submodel. Reductions in the “Susceptibility of Combat Aircraft” and “Vulnerability of Combat Aircraft” affect the “Acquisition Cost of combat Aircraft” and “Modification Cost of Combat Aircraft” used in the Procurement Submodel. Additional feedback lops between the submodels are generated by monitoring the “Relative Strengths of U.S.S.R./U.S. Airpower” and incorporating the effects of this perception on the Economy Submodel, the Budget Submodel, the Procurement Submodel, and the Survivability Submodel. Thus the five submodels interact to form a series of interacting positive and negative feedback loops. The positive loops reinforce themselves leading to increased air power over time. The negative loops act through such constraints as resource availability and spiraling procurement costs to suppress the growth of air power.
The need for grand unifying principles of the evolution of societal systems is stressed. Examples of such principles from other sciences are given. The economic long-wave or Kondratieff cycle is taken as a reference basis for the study fo the evolution of contemporary technological societies. A number of qualifications to the basic paradigm are made. Several areas of recent structural stability theory are discussed in terms their relevance to societal evolution. Particular stress is placed on the nonequilibrium and bifurcation situations. Structure-function-behavior interrelationships at and near critical points are considered the most important features pertinent to system change or reconfiguration. Attempts are made to provide a fuller integrated theory of societal evolution and structural change. A number of problems relative to system dynamics theory and modeling, and to the use of models in societal management, are introduced and suggestions for improvements are made.
Recent developments in mathematics show that more-or-less random behavior and spontaneously evolving structures can be given analytical and deterministic representations. Both empirical simulation and theoretical models have been developed in economics that have similar capacities. This suggests that we are entering a new period when structural change and inherently unpredictable events can be explained or understood in terms of endogenous economic forces.
The Argentine energy authorities elaborated a Plan for the Electricity National Sector, made known in 1979, where the policies to be followed for the period 1979-2000, were established. The Plan proposed basically a dramatic change in the structure of the present generating capacity configuration at the national level, toward a scheme predominantly hydro based. Apparently, the idea of an Electricity Sector less oil dependent, together with the utilization of a huge hydro-potential, which had been neglected until that moment, appeared promising. However, the study of the robustness of such plan, that is, its capability to perform well under different scenarios, became indispensible. The System Dynamics technique provided the possibility of analysing such robustness, by means of a continuous-time simulation model of the Argentine Electricity Sector. This paper presents the results of experimenting with that model, in order to determine the soundness of the policies proposed.
The present paper carries these converging strands of work forward to address the problem of parameter selection for a given control structure and the comparison of the resultant performance of two competing policy designs.
Just as the cobbler's children are the last to have their shoes repaired, simulators—individuals who spend careers structuring the world into systematic models—have not developed tools and techniques to systematize and structure their own procedures. As a result, quick and easy communication among all interested parties during modek development is often made extremely difficult. Inputs which might be helpful to the modeller are consequently lost. It is also typically impossible for a client to maintain control over the implementation of his or her model design especially when the client and model builder are physically separated. Finally, when a version of the model is completed, there can be a considerable delay while an entirely new model description, in laymans terms, is prepared. Unfortunately, as a result of time constraints such as a description is sometimes never completed. Based on the work done at Purdue University and the frustration of designing and overseeing the implementation of a system dynamics simulation model at the Department of Energy, this paper describes a structured development and documentation approach to modelling. A systematic approach of this type forces the analyst to think out the implications of a given representation of the world before sitting down at a terminal. It provides a living (continually updated), standardized, written document which not only helps improve the quality of the work but allows for efficient communication between the client and the implementor and eliminates the need for most post model development documentation efforts.
The research reported in this paper was directed toward understanding and modeling acquisition policy within the DOD. The acquisition model presented was developed at the departmental level and primarily is intended to portray the strategic policy structure of the acquisition system. Lower levels of aggregation were used only where the detail involved was required to capture a major concept. The model parameters and outputs were designated to show what trends would be associated with the implementation of various policy alternatives. Emphasis was placed on the dynamic nature of the relationships within the acquisition system and how they are affected by the policies and external pressures. Exogenous factors input to the model include broad representations of the United States and Soviet economic conditions. The Soviet threat, so key to many of the political battles surrounding weapon acquisition, is generated in the model as a response to threat perceived by them, subject to the economic and political constraints. Incorporation of these and other key relationships was controlled through careful application of a design methodology.
The U.S. Navy's need for better long-range planning is discussed in light of recent dynamic increases to force plans. The difficulties embedded in the current planning and programming process, and the problems they cause in developing valid approaches are reviewed. The ongoing “Navy Resource Dynamics” project at The George Washington University is then presented as a means of overcoming the difficulties, and providing a timely planning model. The basis of the model is a lagged feedback analysis linking budget “flows” over time to weapon system asset “stocks.” The trade-off between naval force levels and the cost of owning the forces is emphasized with force readiness being a relevant measure.
In this paper we present a formal system S∆, in order to characterise the evolution of knowledge. In addition to the connectors of classical logic, we introduce two dynamic connectors- the mediate future and the immediate future-expressing the transformations that may affect data in the course of time. The axiomatisation of these connectors and their semantic characterisation lead us to define a model of interpretation for the formal system which is comparable to that of Kripke for modal logic. With this model we prove the intrinsic consistence and the validity of S∆. Similarly we demonstrate completeness and other propositions connecting the immediate future and the mediate future.The formal system S∆ is one of the component modules of the ARCHES system, a symbolic system for the representation and treatment of knowledge whose objective is to produce new knowledge through two modes of reasoning-deduction and analogy-based upon specific processes of inference.
This study has illustrated that simulating an aggregate model, using the same data set at the same level of aggregation, can lead to different model conclusions when different aggregation criteria are applied. This study's conclusion to the effect of aggregation of individuals can have significant influence on the results of the model is expected to have different implications for system-dynamics modeling. For the field of system-dynamics modeling, the study has identified a kind of model sensitivity that can not be tested by the methods of sensitivity testing presently used. For future research in the field, the concept of aggregation of individuals has to be clearly established and differentiated from the concept of aggregation of variables before general rules for this type of sensitivity testing can be identified. Similar sensitivity testing should be adopted in the system-dynamics modeling technique. If this has not been done, this simulation approach should be interpreted conservatively. This paper also discusses the problem of whether a universal aggregation scheme is the only highest aggregation scheme.
A preliminary mathematical model of fluid dynamics in acute large area burns presently incorporates plasma water, urine output, burn water loss, insensible losses via the non-burned skin, lungs, and G-I tract, as well as inputs of maintenance water and theraputic (Brooke Formula) fluids. The model is an initial step in a longer-term project to identify the pathogenetic mechanisms that control fluid shifts and to evaluate the effects of crystalloid (sodium ion), colloid (albumin), and other guidelines for fluid resuscitation. The model is initialized in homeodynamic equilibrium for a standard 70 KG person, and gives reasonable, realistic responses to a wide range of parameter variations (body sizes, burn wound loss factors), step functions (burn size, discontinuation of maintenance water), and rates of therapeutic fluid administration, given its present structure. The addition of burn and nonburn interstitial and intracellular spaces and their constituents (water, sodium, albumin and potassium) will: 1) permit validation against a wide body of clinical and experimental data, 2) suggest refinements of current resuscitation guidelines, 3) suggest more incisive research on pathogenetic mechanisms and treatment modalities, and 4) permit comparison of System Dynamics with alternative modeling and simulation approaches.
:We present a technico-economical simulation model focusing on enhances recovery in oil fields. The model simulates several assumptions on the quantity of injected fluids, the operation’s start date, as well as the incidence on recovery. It is also possible to place one’s interest on financial and economical parameters. It can also be used for any oil field for which precise physical data may be obtained. Paper: N/A
An exemplary model has been formulated using a methodology which casts a modified version of input-output analysis into system dynamics format. The intent is to utilize the methodology for further study of the concept of a geeignet (appropriate) population for a society. The exemplary model represents a highly aggregated socio-economic system with six sectors. Evaluation of the quality of the society is an important issue in the geeignet population study, and to that end the technique of multi-attribute utility measurement (MAUM) has been included in the model. In order to study a mechanism that can minimize the marginal production cost during the time evolution of the system, a Cobb-Douglas production function that permits substitution between two factors has been incorporated into the agricultural sector. Model runs are shown which demonstrate the approach to equilibrium for the society and the time evolution of the society as the agricultural sector changes from a labor intensive to a capital intensive configuration.
This paper describes the development of a limited resource, backward scheduling, network model for an assembly department using DYNAMO. The model evolved in three stages: a calculation device, a policy exploration tool and a planning and scheduling system. An interesting feature of the model is the representation of the complex flow through various disassembly operations. Graphics and report interfaces with DYNAMO are discussed. The enclosed programs are provided on an as-is basis, without warranty either express or implied. No assurance of successful installation can be given.
The paper reviews, briefly, the development of system dynamics (SD) and presents a modern control approach. It formulates and solves the SD policy design problem as a model-following control system design problem in an adaptive control framework. A computationally simple policy algorithm based on variable-structure system theory is used as an illustrative example of the stabilization of the dynamic characteristics of a production/raw materials system. Computer simulation results are given for the modern control approach as well as the classical SD techniques. Directions in which the modern control approach could be developed are indicated.
Corporate modeling in general and System Dynamics modeling in particular have now a history of more than two decades. Despite this fact impacts on the corporate planning process have not been very satisfactory. The reason is that in many cases system dynamics models (as well as other types of corporate models) had not been constructed, validated and implemented adequately for managerial use. They did not provide the information support which is needed in order to make the necessary decision in the various phases of a complex planning process that has a lot to do with major changes in markets, products, production processes, technologies, governmental regulations etc. Here, formal decisions rules as used in operation planning are impractical in most cases.
This paper describes the application of System Dynamics in what is traditionally a hard engineering area, but where the application of analytical techniques are limited by the stochastic nature of the system driving forces (coalface output rates) and the need for highly credible, management orientated results. Methods and analysis have thus centered on using discrete simulation techniques based on open system models, primarily to assist in capacity design. The use of System Dynamics in this context is based on two premises. The first of these is that System Dynamics has, in addition to it s softer areas of application, considerable potential to both supplement and enhance Operational Research approaches in the analysis of such systems. Secondly, it is the author’s belief that the key to further development and acceptance of System Dynamics lies in bridging the gap between itself and associated subject fields, such as Operational Research, by direct demonstration of the approach within these fields. Recent technological advances within the coal clearance field have provided an excellent form for such a demonstration.
There is a growing interest in energy and energy policy analysis because of the gap between the United States’ energy consumption and energy production. Numerous policies for dealing with America’s “energy crisis” have been discussed and evaluated. Underlying these policy investigations have been a variety of simulation models designed to analyze energy demand, energy supply, and the interaction between the two. Several of the models used for energy policy analysis do not couple the energy sector to the rest of the economy. Some modeling efforts even assume that there is no causality from energy to GNP. The purpose of this study is to examine the structural relationships that govern the interaction between the energy sector and the rest of the energy policies, so as to contribute to the development of more effective national energy policies. A computer simulation model that illuminates the feedback coupling between the energy sector and the rest of the U.S. economy is used in the analysis. The model is used to analyze the effects of increasing capital intensity of the energy sector on the level of economic output and the efficiency of a general class of conservation initiatives in mitigating those effects. When conservation initiatives are introduced, cumulative energy consumption is reduced and sales and profits of the producing sectors are lower. Average GNP is lower and average general unemployment is higher when conservation is introduced.
This paper introduces an aggregate view of factors and policies that can influence the development of military forces in two international alliances which see each other as potential adversaries. The growth of forces observed in the NATO and Warsaw Pact alliances is taken as a reference mode. A conceptual System Dynamics Model is described which can accommodate a number of different perspectives on this issue.
A System Dynamics project for a corporate client generally has three objectives: creation of an analytical tool, transfer of a new analysis technology into client organization, and managerial development. In many ways, the first two objectives are means toward the third. Development of new—and shared- perspectives, attitudes, and behaviors among the senior executives can be the most significant benefit from a System Dynamics project. This paper discusses how the process of System Dynamics has been used to draw out diverse points of view, to test and evaluate the differences, to build a consensus regarding key assumptions, to create confidence in the analytical tool which was developed, and, ultimately, to forge a managerial commitment to a new business strategy. The author draws upon several recent applications in the United States and Europe to illustrate the role of System Dynamics in effecting strategy change, and comments on how the process is affected by differences in organizational “culture”.
In the first lecture of the first system dynamics course I ever took the professor presented a list of the steps of a modeling project. During the rest of the semester it became apparent to all of us that actual projects never follow the list very closely. But it also became apparent that the list was useful anyway. It helped organize effort, gave direction to a stalled modeler, and provided a checklist of activities to be addressed (if not always accomplished).
As a novice System Dynamicist one learns all the textbook rules and advice of system dynamics modeling. As a practicing System Dynamicist one learns the many shades of rules and advice. The latter ones are only occasionally spoken about and seldom written down. The experience gained from applying formal modeling technique to a diffuse ambiguous reality, often exist as vague mental models of the various roles a formal simulation model and a policy analyst can play in the public policy formation process.
There has been a dramatic upheaval in our conception of science in recent years. The old notion that science is a logical, rational enterprise continually adding to the stockpile of knowledge has been challenged; many now recognize that the evolution of science is punctuated by violent disruptions. During such crises, or scientific revolutions, a tried and true theory is abandoned for an untested and often heretical alternative. The new theory destroys the old rather than building upon it, and thought he successor may flourish for centuries eventually another crisis develops and another revolution occurs. Some even claim that science is completely anarchic, more a no-holds-barred brawl than a calm, reasoned investigation of reality.
This paper explores the following questions: 1.What are the economic consequences of escalations in unconventional energy costs on terms of economic growth, inflation, real energy prices, energy production, consumption, and imports? 2. To what extent are escalations internally generated by interactions between the energy sector and the rest of the economy?
Dramatic declines in harvests strengthen the assumption that Long Island’s hard clam fishery may be heading for collapse. A family of predator-prey models has been developed to test and evaluate alternative strategies to reverse the decline in hard clam harvests and/or stabilize the clam population. Harvesting is simulated as a fixed percent of standing stock and the behavior of the baymen in response to price and supply of clams is not included in the models. Five types of policies are evaluated: closed season, maximum size limit, hatchery seeding, bounty on predators, and nursery sanctuaries (closed areas). Effectiveness is judged for both the short term (ten years) and the long term (eleven to twenty years after the policy was instituted). While seeding options produce modest short term improvement in the annual value (8.0 to 10.8 percent), only the two bounty policies produce significant improvement in both the short term (17.0 and 72.6 percent) and the long term (20.4 and 66.4 percent). The results of this model reflect the influence of specific management policies on the biological system alone. A later version, incorporating the behavior of the baymen, will introduce key social and economic factors.
Alcohol abuse and treatment in the United States cost nearly $43 billion in 1975- including $19.64 billion in lost production, $12.74 billion in health and medical costs, $5.4 billion in motor vehicle accidents, $2.86 billion in violent crimes, $1.94 billion in social responses, and $0.43 billion in fire losses. There are about 13 million problem drinkers (including alcoholics) in the United States. Of these, less than 10 percent seek treatment. For those receiving treatment, the overall improvement rate ranges from 30 to 70 percent, depending on how broadly improvement is defined.
This paper attempts to explain the causes of widespread rural poverty which has persisted in Pakistan in spite of the development effort. The paper also analyses the various rural development policies implemented and explains why these policies have had little if any impact on the income of the rural poor. The main instrument of analysis of the study is a system dynamics model incorporating income generation and disbursement processes in an agrarian economy consisting of a capitalist sector and a self-employed sector. The analysis takes into account only the economic factors arising out of the rational decisions of the capitalists and the cultivators. These factors are considered adequate for maintaining rural poverty, although, the role of social and political factors is acknowledged. The study suggests that the absence of an economic force that should encourage ownership of land by its cultivators is a key factor responsible for the poor economic condition of the working rural households. Land is easily separated from cultivators and is concentrated in the capitalist sector. This concentration significantly reduces income in self-employment and thus leaves the cultivators with very little bargaining power for negotiating compensation for labor. Thus, development policies striving to increase productivity may only serve to increase the claim to income on the basis of ownership of resources. If ownership is concentrated outside of the cultivators, such policies may worsen economic condition of the cultivators. The study proposes a general framework for rural development incorporating simultaneously fiscal instruments that should encourage transfer of land ownership to its cultivators and policies that should help increase productivity of land.
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.
Many Congressional and Executive Branch policymakers are becoming discontent with the contribution of models to the policy process. One reason the modeling process and modeling results are being questioned is because of their perceived incomprehensibility and limited utility. This discontent has intensified with the Administration’s proposed reductions in domestic programs. This new mood of austerity is forcing researchers to justify modeling as useful to government policymaking.
My paper focuses on an extension of the basic R&D model. The basic model uses the concept of an average product which the firm develops and eventually sells. The extended model used in my paper diaggregates products into products and architectures. In the extended model, products are developed and sold just as they are in the basic model. An “architecture” is a basic engineering development which, when completed, enables the firm to develop a large number of products. An investment of resources in architectural development is necessary before marketable products can be created.
This study proposes to compare two types of computer simulation techniques, namely tactical and strategic simulations. It explores the advantages and disadvantages of the two methods and stresses the importance of the insight to be gained by combining both approaches in the evaluation of public policies. A school finance reform policy is presented as a case study. More specifically, the research evaluates the implementation of a cost-of- education index (a mechanism to adjust for disparities in educational costs among school districts in a state) in the New York State aid formula. The study investigates, using two computer simulation techniques, the impact of this policy in terms of organizing per pupil expenditures.
This paper examines the linkages between system dynamics and the Carnegie school in their treatment of human decision making. It is argued that the structure of system dynamics models implicitly assumes bounded rationality in decision making and that the recognition of this assumption would aid system dynamicists in model construction and in communication to other social science disciplines. The paper begins by examining Simon’s “Principles of Bounded Rationality” which draws attention to the cognitive limitations on the information gathering and processing powers of human decision makers. Forrester’s “Market Growth Model” is used to illustrate the central theme that system dynamics models are portrayals of bounded rationality. Close examination of the model reveals that the information content of decision functions is limited and that the information is processed through simple rules of thumb. In the final part of the paper there is a discussion of the implications of Carnegie philosophy for system dynamics, as it affects communication, model structuring and analysis, and future research.
A particularly interesting area for the application of system dynamics methodology is in business management; especially the interplay of quantitative (financial, economic) and qualitative factors (motivation, morale), and the decision-making choices which confront management. When a firm has a product which can be measured in economic terms, the construction of a model can be quite straight-forward. Even in non-quantitative areas such as research and development, models have provided insight into the decision-making process. While these models have been informative from both a system dynamics and management science perspective, the practical application of the results has been too often lacking. For a businessman, simulations and models are academic exercises unless they provide some measure of practical guidance. It was from a basis of requiring that the system dynamics model provide practical decision-making guidance in real-world environments that we have attempted several studies of R&D projects.
Both in incipient and later phases of developing a model, unexpected behavior is frequently encountered—that is, behavior which is at odds with the initial expectations of the model builder or client. The appearance of such surprise behavior immediately raises two possibilities: either the behavior is implausible, and the model therefore must be revised; or the behavior withstands scrutiny and reveals previously unappreciated aspects of the system. In either instance, the process of diagnosing and interpreting surprise behavior gives a powerful basis for model for model evolution and generating policy insights. But frequently, it is quite difficult in practice to discern whether the incidence of surprise model behavior reveals errors or suggests insights. The paper is designed to contribute to the literature on model formulation, testing, and policy analysis, by discussing the criteria for diagnosing surprise model behavior. Several case examples are presented in which appropriate resolution of surprise model behavior led to significant model improvements and/or behavior insights. Moreover, operational guidelines are presented to increase the likelihood of uncovering and successfully treating surprise behavior.
The background of this paper is an analysis carried out on the occasion of an election within an academic self-administration in West Berlin in 1980/81. This analysis considers (1) papers presented during the time before the election with opposing opinions as to image and efficiency of this administration, and (2) statistical data concerning possibilities within the structure of this administration and the realization of these possibilities by members of the staff over a period of seven years.
The philosophy of constructing models requires that the models be sufficiently detailed in order for them to have a significant impact on the development of detailed corporate plans. Although dynamic behavior may adequately be captured by a “simple” model, our experience in preparing models for a number of corporations indicates that detail is useful to facilitate initial acceptance of the model, and is often essential in assuring the model’s continued use by the client.
The motivation for developing this model came from an academic interest in the dynamics of recreational behavior as well as in responding to passing recreational problems faced by state officials and tourist industry planners. The current energy picture and economic climate in Midwestern United States appears to be relatively bleak. Michigan, for example, whose economic life revolves around the state of the automobile industry, is reeling from sharp declines in auto sales. The cost of energy, for the most part, has been increasing over the past eight years at a phenomenal rate, not only increasing the cost of automobiles, but also affecting consumer choices and preferences for smaller and more economical cars.
This abstract describes the further development of the project “Introduction `of innovative Products into a competitive Market”, the former stages of which have been already described into the Proceedings of the 1980 International Conference on Cybernetics Society, Cambridge 1980 (Krallmann (1980)). The management of the company we cooperated with wanted to get support in the decision making process of introducing innovative but similar products into a competitive market.
The scientific technique known as the method of multiple hypotheses can be adapted to suit the purposes of system dynamics policy modeling. This method would allow determination of a model’s value through comparison with other competing models. It would also diminish modelers’ emotional attachment to any single theory. But in adopting this method, system dynamicists would need to develop a new philosophy of model evaluation, emphasizing disproof over verification and comparison among theories over improvement or elaboration on a single model.
The SD approach is based on control theory. As with general system theories, it postulates that system structure causes system behavior. Computer simulation used to be the only means of solving complicated models at the time SD was invented. Therefore: (1) only system structure and system behavior could be used as yardsticks in model validation (2) without an intuitive or intelligent guess, that related structural explanation to model behavior, all modelling work would have been fruitless or at least extremely laborious. In computer simulation, no automatic feedback from model behavior to structural changes is feasible. A human link is needed and, therefore, system dynamists have rightly argued about the significance of insights gained from the very modelling process. Without insights, no feedback mechanism would work properly in model construction. The authoritarian relationship between man and machine, prevailing in SD, is an outgrowth of this situation.
Our work during the past several years leads us to believe that there now exists a small but significant number of American corporations engaged in daring experiments in organizational transformation. These companies fundamentally alter our understanding of how a group of people can work together. They are committed to the absolute highest in organizational performance and human satisfaction. They view themselves as microcosmic demonstrations of how society could work towards everyone’s fulfillment.
This paper is destined not so much for those who are present at this conference than for the members of the business community whose absence constitutes one of the main problem facing System Dynamics. Indeed, since its inception more than 20 years ago, quite a few Industrial or System Dynamics publications have dealt with industry or government related applications. However, very few of those have been effectively developed within and present by business or government representatives.
In order to investigate the regulation of breathing under various conditions, we have developed a dynamic model of the human respiratory and cardio-vascular systems. The model describes the flows of oxygen and carbon dioxide between the atmosphere and the tissues as well as the chemical regulation of breathing in a rather detailed manner. When testing the model with a step increase in muscular metabolism (simulating a transition from rest to physical activity), it reproduces clinical observations for the variation in ventilation and in arterial oxygen and carbon dioxide pressures. The model also reproduces the respiratory response to changes in the composition of the inspired air. Combined with a model of the Hafnia A anaesthetic system, the respiratory system model has finally been used to examine the life-threatening dynamical run-away effects which may occur, if the fresh gas flow is reduced too much, and the patient starts to rebreathe his own expiration.
This paper explores the possible paths of emergence of a new medical technology and how those paths might be altered by government regulations of the sort now promulgated by the Food and Drug Administration (FDA). The purpose of the paper is to help clarify the role of FDA regulation in a dynamic context. The analysis focuses on the idea that an emerging technology’s effectiveness may change over time and that the benefits and losses due to regulation may themselves have a dynamic character. An increasingly complex story of the emergence (or dissemination and development) process is told with the help of causal-loop diagrams. Results from a preliminary system dynamics model based on this story are illustrated and discussed. They suggest that the FDA’s actions may have unintended effects, such as slower development of a technique, which may or may not be harmful. They also suggest that, in certain cases, post-marketing surveillance and communication of results may be at least as important an activity for the FDA as pre-marketing evaluation.
Planning and Control are essential for the success of any human endeavour and are now widely established concepts in most organizations, usually enshrined in formal corporate/planning systems. The process of planning may be analysed in a number of different ways, but generally there is a consensus on the need to split the process up into strategic planning, which directs the organization and tactical or operational planning which deals with the resource allocation for specific operational units and integrates them into the whole.
The model in this paper is, therefore, directed towards an understanding of the mechanisms at work during the UK business cycle. Its time horizon is no greater than ten years, with the main emphasis on the next five. It is frequently argued that cycles of longer period than the business cycle exist, e.g. the 50 year long wave. It is not intended that this model should try to capture in detail the mechanisms believed to produce them. However, their role in determining the underlying trend must be recognized, and their effects incorporated exogenously, perhaps by reference “off-line” to other models designed to look at these more distant horizons.
Since 1972, Jay Forrester and colleagues at MIT have been evolving the System Dynamics National Model (SDNM). The purpose of this model is to guide policy makers in dealing with today’s major problems. The ambitious scope of the project motivates careful examination of modeling practices and how they contribute to the success of the project. The above paper recounts incidents in the development of the SDNM and discusses the related modeling issues.
The purpose of this paper is to introduce an integrated framework for long-range strategic planning to a railroad. The framework is a computer simulation model designed to be useful to most freight –hauling railroads. The model can help to increase the understanding of problems facing the railroad and to aid in developing strategies for addressing these problems. It is designed to forecast railroad performance and to aid in developing more effective policies for railroad management. It can also be used by Federal agencies to evaluate impacts policy on railroad performance.
To improve matters in the behavioral sciences, system dynamics can play the role of catalyst by providing both the holistic view which is needed to understand the behavior of human beings and not just bits and pieces of their actions and the necessary technical tools to map behavior over into manageable models. In return, system dynamicists will learn how to include a more differentiated and thus more realistic representation of human behavior in their models of social systems.
It was the purpose of this study to describe a modest theory of educational change which could be stated with some precision, which could reproduce observed historical behaviors, which could facilitate an understanding of the structural dynamics giving rise to those behaviors, and which would permit the examination of selected policies which have some historical currency.
The Causal Loop Diagram, a signed diagraph which shows the variables and interactions of a system Dynamic model, has been studied. It has been found convenient to start with the levels and their interactions. Then signed interactions between levels and rates may proceed. The transformation from signed level diagraph into Causal Loops, in terms of levels and rated, is presented. Dynamics properties such as stability, oscillations, controllability, and observability are related to the information contained in the Causal Loop Diagram. These dynamics properties have been found very useful in the synthesis of policies aimed to manipulate structure. Illustrations and examples are inserted in the exposition.
The aggregate demand-aggregate supply (AD-AS) model presented in most intermediate and advanced macroeconomic texts may provide misleading insights into the effects of economic stabilization policies. Conventional analysis of the AD-AS model shows that policies which raise demand during periods of peak unemployment and reduce demand during periods of low unemployment tend to stabilize the economy. This paper: (1) Develops a dynamic model of the AD-AS model; (2) Shows that the model produces a very long period of oscillation (approximately 50 years); (3) Shows that the conventional stabilization policies increase damping of the long cycle; (4) Adds inventories to the base model; (5) Shows that the inventories introduce a business cycle fluctuation to model behavior; (6) Shows that the conventional stabilization policies destabilize the business cycle behavior mode. This paper should help explain why standard “stabilization” policies tend to destabilize the business cycle in the System Dynamics National Model.
The paper is organized in three parts. It begins with a brief review of the substantive exchange of views in the case, including the Company’s position, the Attorney General’s position, and the analyses and counter analyses presented in support of these positions. In Part Two, the paper describes the participants and the schedule of the hearings. It is argued that the rapid pace of these hearings and the background of the participants are important determinants of usefulness of System Dynamics models under adversary proceedings. The third part of the paper concludes with a discussion of the advantages and disadvantages of system dynamics under fast paced, adversary conditions.
This paper describes a System Dynamics model of the foreign trade sector in a small open economy. The model is used to investigate the consequences of various economic policies aimed at solving problems which a high-cost country may experience when its debt-ratio begins to increase. With the model, we simulate some of the economic consequences of currency devaluation, tax increase, restrictive public policy and income freeze. Each of these measures significantly improve the debt-ratio, but only after a delay of 5-8 years, as a result of various bottlenecks in the decision-making process.
After twenty-five years of development and some notable achievements the field of System Dynamics is not as large, well-known, respected and influential as it should be based on the breadth and power of its principles and the need of industry and society for dynamic analysis of this kind. It is suggested that System Dynamics’ methods be used to analyze the growth of the field and improve its development. This paper initiates the self-analysis by presenting a review of performance and preliminary model structure for the field to encourage constructive criticism and to facilitate understanding and cooperative revitalization. The model structure may be general enough to apply to other fields as well.
Lebanon, the country is new; Lebanese society is ancient. Lebanon’s current geographic frontiers and political institutions were defined in the Constitution of 1926 and, except for slight modifications introduced on the eve of Lebanon’s independence 1943, remain in effect. The social and cultural characteristics of Lebanese society have their origins in the Phoenician, Greco-Roman, Arab, and Ottoman civilizations. The Lebanese state, with an area of ten thousand square kilometers, and Lebanese society with a resident population of three million persons (and almost an equal number of expatriates), have a significance in the Middle East and, indeed worldwide, out of proportion to their size, owing to their role as a vital link between East and West.
There is unquestionable need for sound and disciplined methodology of experimenting with SD models. A number of valuable papers shows various ways utilizing sensitivity analysis, programming of experiments and other approaches. But should we not attack the problem more fundamentally before getting into more specific and costly analysis? We would like propose a different kind of approach, it is analysis of SD models based on experiments with families of trajectories.
System Dynamics consists of a body of theory, philosophy, methodology, policy-related applications, and experience. Basic to system dynamics is the theory of the semi-closed, fully closed-loop system in which the feedback loop is the principal construct. In the 20 years of its existence, major emphasis has been placed on the methodology of model-building, on applications, and on philosophical debates involving alternative approaches, particularly the static econometric approach. Experience has produced improvements in the original theory. However, feedback loops are not the only constructs for dynamic theory-building, and cybernetic, self-regulating systems are not the only kinds of living systems, nor is the cybernetic perspective invariably the only or most appropriate perspective over the life history of a particular system. The processes of self-organization and the emergence of new structure deserve equal attention in the evolution of systems. This paper briefly reviews the history of system dynamics. An analysis is then made of present system dynamics theory. This is followed by summaries of three field theories—of critical phenomena, catastrophe theory, and disruptive structures—and attempts at synthesizing these theories and system dynamics. Then ways of enriching existing system dynamics models with fuller use of knowledge from behavioral/social science and sociotechnical systems, with particular relevance to the National Model, are discussed. The paper concludes with an identification of three immediate next steps in research.