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.
: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
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.
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.
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.
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.
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.
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 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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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.
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.
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.
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.
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.
This paper presents results of a model which has been used to avoid the consequences of a spatial expert opinion concerning the further development of the Berlin School of Economics in West Berlin in the year 1982. Starting point is the so called “HIS-Gutachten” of February 1982. This expert opinion was commissioned by the Senator for Science and Culture of the West Berlin government to show the possibilities of finding free capacity for a different institution in the building used by the Berlin School of Economics during the current period of limited financial resources.
This paper proposes to utilize the Management Technologies' U.S. Economic Model to simulate the same monetary policy tests performed on the three macro-econometric models. Such comparison is likely to be methodologically revealing for several reasons. First, the 'Management Technologies' U.S. model is at least of comparable detail and sophistication to the econometric models. Second, the U.S. Model has been developed for similar purposes of short-term (1-2 years) and medium-term (5-20 years) forecasting and analysis of various industry and government policy measures. Third, the U.S. Model has been extensively validated historically and empirically, so that model details and parameter values are not simply “representative” a priori selections, but meet the dual tests of being a priori satisfactory and historically accurate. Policy tests thus far performed on the U.S. Model in fact illustrate significant differences from the econometric results, both near-term and longer-term.
Our role is to advise senior British Telecom management on strategy for BT as a whole. This requires coherent strategic analysis aided by systems dynamics models. All management levels must have confidence in the models in their results. For analysing alternative futures we find that graphs are easier to appreciate and understand. We have also found that colour graphics greatly enhances the presentation of more than one curve at a time. Interaction with models in real time is a major step in boosting user confidence for it allows rapid confirmation, or rejection, of the user's prejudices. Interfaces to computer models, such as menus, bit pads, etc, are successful if they interface efficiently between the user's mental map and that which is enshrined in the model. If the user can move a 'lever' which exists in the real world and that causes the model to display the effects he expects, then he will have confidence in the model. Decision makers want the best strategy. We shall discuss how we use colour graphics to compare strategies, but that often begs the question 'Why?'. This requires techniques used in artificial intelligence, which can also be used to 'customise' interfaces to individual users.
A system dynamics model of a major telecommunications network has been developed to support managers in the function of long range strategic planning. Application of system dynamics to the strategic planning area was found to be, in some respects, quite unique. The article discusses this type of application in the areas of model requirements, sponsorship, scope, development, and review. In the area of requirements, it was found that a system dynamics model developed to support long range strategic planning should be quite broad in scope, must satisfy a potentially large community of planners, yet also must pass the review of tactical planners as well. A baseline-model approach is proposed as an effective way to satisfy these requirements. Guidelines for the modeler are proposed for obtaining sponsorship, for avoiding pitfalls in the model development process, and for interacting with model users and reviewers. The baseline-model approach, coupled with the guidelines, has been found to work quite effectively within one organization to support long range strategic planning.