Using System Dynamics as the primary tool of investigation, an attempt has been made in this paper to present (i) a general model of commodity price fluctuation, (ii) a price stabilization policy based on buffer stock, and (iii) the impact of this policy on the long term growth of the commodity industry. The model has been tested for the case of Indian Tea.Average unit cost of the commodity at the point of sale, operating profit margin desired by the sellers (computed on the basis of average quality of supply), actual inventory, and the average sales rate are considered as the chief determinants of the commodity price. Circular relationships among these variables have been considered to generate the price fluctuation over time. While testing the price stabilization policy, the model considers its operation phase. It is shown in this paper that such a price stabilization policy tremendously boosts the overall long term growth of the industry.
The simple two-sector Kondratieff model developed by John Sterman has contributed significantly to our understanding of some of the basic mechanisms underlying the economic long wave. The dynamic hypothesis of this model is that the positive feed-back associated with the so-called self-ordering of capital reinforces and prolongs the characteristic expansions and contractions of the capital sector as it adjusts its capacity to the required production. It is assumed that this feed-back can be strong enough to produce a self-sustained oscillation (a limit cycle) with a period which is about twice as long as usual capital lifetimes. Concentrating on the ordering and production of capital, the Sterman model only depicts a relatively small fraction of our economic system. At least in its original version, the model doesn't deal with several of the basic phenomena involved in the verbal description of the economic long wave, as it is usually presented. There is no account of variations in employment, buying power or political attitudes, for instance, and changes in the rate of innovations are also outside the model boundary. We do not think that one can presently develop a complete and satisfactory model of the economic long wave. We have therefore adopted an alternative starting point by assuming that the alternating phases of economic expansion and stagnation arrise from the succession of technical-economic cultures each characterized by its own infrastructure, leading industrial sectors, typical production methods and main products. Even the geographical location of the dominant political-economic center may shift from wave to wave. This is Mensch's process of metamorphosis. Where the Sterman approach emphasizes the cyclic character of the wave, our model is meant to describe the qualitative changes through which one set of technologies replaces the next. In our model, the economic system has no equilibrium point to oscillate around. As long as technology develops and new discoveries are made, the potential for economic activity continues to grow. A purpose of the model is therefore to show how randomly distributed discoveries can be bunched into waves of innovations with a relatively well defined period.
This paper presents a flexible, model-based approach to strategic program design--the process of putting together consistent business programs and policies to support new strategic initiatives. The new approach combines ideas from administrative theory and feedback theory. Administrative theory reveals the organizational and diffusion processes that connect business programs and customers. Feedback theory reveals patterns (feedback loops) in the connections between programs and policies of a business and its market. This conceptual framework is applied to strategic program design in a two-phase analysis which is much more flexible than traditional system dynamics business modeling. Phase 1 is a descriptive analysis that explores business-market structure in terms of organizational and diffusion processes, showing where conflicts of responsibility, confused incentives, misinformation, and administrative inertia may degrade business performance. Phase 2 uses simulation modeling and the descriptive information from phase 1 to debate policy options and program design. The style of analysis is illustrated with business cases and applications projects.
How should a causal loop diagram be drawn to explain structure as clearly as possible? Two basic rules are formulated: Feedback-loops should be drawn with loop-form, and influence should be unidirectional through each variable. An example shows that application of the two rules leads to enhanced clarity. Artistic derivations from the two rules can be used to produce memorable figures. Current practice in causal loops diagramming indicates a potential for improvements.
A static and a dynamic model of the oil market are compared. Three major differences appear in forecasts. The dynamic model fluctuates around the static mode equilibrium price. The dynamic model shows greater uncertainty in trend development. The dynamic model forecast overshoots the cost level of synthetic oil.
A division of a large textile company was chosen as the focus of a system dynamics study to determine how management would respond to any capacity adjustment problem. The company produces fabrics for household as well as industrial uses and the annual sales of the company are several billion dollars. The division under study produces yarn and piece dyed draperies, mattress tickings, and upholstery fabrics. The four major manufacturing processes in the division are spinning, yarn preparation, fabric formation and fabric dyeing and finishing. Although not aimed at any particular perceived problems, the study was undertaken with two purposes, firstly to develop a system dynamics model that would describe the performance of the division and secondly to use the mode to investigate the effects of demand changes on various capacity adjustment policies practiced in the division. The study includes interactions among a large number of factors in forecasting and inventory control, raw material supplies, employment, and production capacity. These factors related to some ten points and four processes of the division. Data and other information have been collected by questionnaires and interviews with management. The model has been tested for its validity in representing the actual operations. The model is now being used in testing some of the policies in response to change in customer order rate.
The emergence of powerful personal computers and CAD/CAM machines offers a new opportunity for DYNAMO. Although users are generally satisfies with the language, a survey shows they want expanded simulation capabilities including single simulations, eigenvalue analysis, sensitivity analysis, and the optimization by multiple simulation and hill climbing. Novices want easier access to models and simulation. The modular version of DYNAMO now in development will meet these goals. It will break DYNAMO’s normal functions into separate programs that users can reassemble in different ways. For example, one compiler will translate both conventional models and games. The simulation controller will work with a regular rerun, a game, or a sensitivity analysis package. The report generator will display output from any of these packages. These modules will communicate through standard data files, which users can also access for other purposes such as statistical analysis.
A dynamic simulation model of the Indian economy has been developed which captures the important linkages between economic growth and the development of various forms of energy. Non-commercial forms of energy which supplied the bulk of total energy requirements of the economy so far have clearly reached their saturation limits. Capital costs for coal and petroleum increase with resource depletion. The cost of hydroelectricity increases as the cheaper and more accessible resources are exhausted. The costs of renewable energy sources such as solar, wind and biomass decrease with cumulative production due to technical progress. Such sources of energy become more important sources in the future though their current share of the total energy production is negligible. The thesis examines the dynamics of the transition to the new era as well as responses of the economy to energy shocks such as steep increases in international oil prices. It investigates the possibility of an interim crisis if the domestic energy industry is slow to develop or if the response of energy demand to rising energy prices is sluggish. Such a difficult transition may be marked by persistent import dependence, high energy prices and high outlays in the energy sectors that reduce the resources available to the non-energy sectors for consumption and growth. An aggregate production function utilizing capital, labour and energy as factor inputs has been utilized for the economy along with a neo-classical formulation for consumption and saving in the economy. The model generates the energy demand of the economy endogenously and incorporates the adaptation of energy intensity to rising real energy prices through more efficient new capital equipment as well as retrofits of inefficient equipment. The model has been calibrated using Indian data. Where parameters or assumptions are based on uncertain facts, sensitivity tests have been carried out. The effect of government policies such as taxation of energy or emphasis on conservation have been investigated.
During the summer of 1982 the author made predictions of wood pulp prices for the period 1982 to 1986. The predictions were part of a decision on whether to sell a large pulping plant in Norway. This paper presents the predictions and the basis on which they were made. Next, the predictions are compared with actual data for the period 1982 to 1984.
This paper presents a total stability analysis of a simplified Kondratieff-wave model. The purpose is to show how such an analysis can be carried out and to illustrate the kind of information one obtains. For normal parameter values the Kondratieff wave model has a single unstable equilibrium point. Combined with non-linear constraints in the model's table-functions, this instability creates a characteristic limit cycle behavior. For other parameter values, however, the model is stable and generates damped oscillations instead of the limit cycle. For yet other combinations of parameters, the non-linear constraints yield to the instability, and sustained exponential growth or total collapse result. By means of linear stability analysis we first determine the conditions for the transition between a stable and an unstable equilibrium to take place. This transition is known as a Hopf-bifurcation. Using global analysis we outline the phase-portrait of a fully developed limit cycle. By the same method, we examine the conditions under which the non-linear functions fail to contain the system so that exponential run-away or collapse occur. A DYNAMO-program is then developed which calculates the Lyapunov exponents of the system during a simulation, and we discuss how these exponents can be used as a measure of the divergence or convergence of nearby trajectories. Finally, we illustrate how subsequent period doublings and chaotic behaviour can occur if the model is driven exogenously by a weak sine-wave, representing for instance the short term business cycle.
There is a conspicuous gap in the literature about feedback and circular causality between intuitive statements about shifts in loop dominance and precise statements about how to define and detect such important nonlinear phenomena. This paper provides a consistent, rigorous, and useful set of definitions of loop polarities, dominant polarity, shift in dominant polarity, and shift in loop dominance, and illustrates their application in a range of system dynamics models. Consistent with the usual intuitive definitions, the polarity of a first-order feedback loop involving a level x and a single inflow ẋ is defined to be the sign dẋ/dx. Loop polarity is shown to depend upon the sign of parameters not usually considered part of the loop itself. This expression of loop polarity is then applied to multi-loop first-order systems to define the polarity of such systems. All positive loops with gain less than one, such as economic multipliers, are shown to be multi-loop systems with dominant negative polarity. The shifts in loop dominance that occur in nonlinear systems arise naturally as changes in the sign of the dominant polarity. Examples applying the notion of dominant polarity reveal a useful geometric characterization of shifts in loop dominance in nonlinear first-order systems. The concepts developed in the paper are then applied to simple higher-order nonlinear feedback systems. The final application to a bifurcating system suggests that all bifurcations in continuous systems can be understood as consequences of shifts in loop dominance at equilibrium points.
The methodology which this article deals with, is the fruit of the experience gathered thanks to the contributions of experts in the fields of programming, personnel and organisation. The willingness of such people has given rise to the instruments now available in the field of Industrial Dynamics. It is thus possible to design a methodology and simulation models which, with the help of a computer, offer an instrument which can answer the needs of those involved in the planning of human resources in a company environment. This model has so far been applied with satisfactory results in two technically different realities. At the present time, other applications are in progress which confirm the validity of this instrument.
Businessmen, bankers, private citizens, and government officials share deep concerns over the high values of interest rates in today’s economy. Of particular concern has been real interest rate, the rate of interest adjusted for inflation. Although nominal interest rates have followed a generally declining trend over the past year, this decline has generally lagged declining inflation and has failed to keep pace with the drop in inflation. This paper is the first of two on the problem of high real interest rates. It focuses on developing a theoretical framework for understanding the role played by real interest rates in the long wave. The second part of the study will focus on the effects of government deficits and alternative monetary policies. The primary purpose of this study is to show that the downturn of the long wave can cause rising real interest rates even with no government deficit or change in monetary policy.
In order to study the long term behaviour of complex systems, such as industrial enterprises, it is necessary to use reduced models with a limited number of variables. Here we investigate theoretically the relationship between these “mesoscopic” models and more detailed, “microscopic” models of the same physical systems. When the relevant variables evolve more slowly than the irrelevant degrees of freedom, a powerful projection technique is presented (Adiabatic Elimination Procedure). A pedagogical example is discussed, dealing with a large company in the field of computer science, which wants to increase its presence in a particular market segment by starting a cooperation with a small but aggressive company, already in that market segment.
The production of cement pays the most important role in all the construction activities in the country. Due to rapid growth in the industrialisation and the development there is fast growing internal demand of cement. However, cement industry in India has not been able to cope up with the demand. Therefore, it is essential to study the demand and production aspects in order to evolve strategies to meet the demand. For this purpose, a System Dynamics model for cement production is developed. The production model is run for 16 years covering a period from 1974 to 1990 at three conditions, such as basic, optimistic and pessimistic. The different sensitivity runs are also carried out by changing the different parameters influencing the production. Different scenarios are generated and the gap between demand and production is analysed at different conditions. It is observed that this gap is closed under certain conditions.
The economic crisis of the 1980s has revived interest in the economic long wave or Kondratiev cycle. Since 1975 the System Dynamics National Model has been the vehicle for development of an endogenous, dynamic theory of the economic long wave. The model has now reached the point where an integrated theory of the long wave can be described. The theory incorporates many of he partial theories that have been proposed by others. Simulations of the model are presented to show the wide range of empirical evidence accounted for by the model. In particular, the theory suggests the long wave arises from the interaction of two fundamental facets of modern industrial economies. First, the existence of physical lags in the economy, limited information available to decisionmakers, and bounded rationality in economic decisionmaking creates the potential for inherently oscillatory behavior. Second, a wide range of self-reinforcing processes exist which destabilize the inherently oscillatory tendencies of our economy, leading to the long wave. These processes involve many sectors of the economy including capital investment, labor markets and workforce participation, real interest rates, inflation, debt, savings and consumption, and international trade. The paper discusses the relative strengths of these mechanisms and the amplification of the long wave through their interactions. The linkages of the long wave theory to innovation, technological progress, and political value change are discussed.
A new analytic method combining Piapunov's methods and eigenvalue analysis approach, a technique for identifying dominant loop analysis contributed by Nathan B. Forrester, is developed to search for the feasible and most policies in system dynamics models. The paper briefly introduces the Liapunov methods of stability analysis (the first and second methods of Liapunov). Liapunov's first method, under certain conditions, enables one to arrive at conclusions about a nonlinear system (original system) by studying the behavior of linearized systems. Liapunov's second method gives sufficient conditions for the stability of linear systems. Criteria of Liapunov's first method and Krasovskii's method, an extended method of Liapunov's second method, are both applied in the analytic method. The structure of the method and how the method is used are described. It is expected that the analytic method will become a new approach to testing models in order to seek the best feasible policies automatically in system dynamics.
This paper discusses the impact of the energy supply transition on the U.S. economy. An energy supply transition occurs when one resource base is replaced by a new source of energy due to some shift in the comparative economic attractiveness of the two sources. The effects of an energy transition on an industrial economy are long-term and far-reaching. The recently witnessed depletion of the 1970s may foreshadow a major turn in the path of economic development.
This paper describes a current research project in national development, aimed at constructing a system dynamics model to evaluate development problems in India. The underlying premise on which the model construction is based is that the economy of India can be conveniently divided into two major sectors: those of agriculture and non-agriculture. Both these sectors are defined as being controlled by the government through the use of its own financial policies for generating investment in the development process. The investment is generated by assessing the domestic aspects of the economy and the government ability to borrow from external sources. The performance of the non-agriculture sector is, however, modeled in outline only. This limitation has been imposed since the study is basically concerned with agricultural development problems.
Emphasis on economic effectiveness and benefit in our country results in the emphasis of economic analysis in project planning and evaluation during recent several years. The weakness of existing approaches in project planning and analysis to certain extent is lack of dynamic in nature. The effectiveness of system dynamic approach in project planning and analysis is not only due to its systematic and dynamic analysis, but also due to its value in quantitative analysis and policy analysis. The idea and model of R&D project planning is useful in solving the above-mentioned problems. The learning curve nature in development activities. Adoption of task-performance coefficient as a factor in R&D system dynamics modeling. The labor psychological factor in our country and its characteristics in formulation of system dynamics simulation model. R&D as a major element is involved in the model. Policy analysis through simulation running is an important basis for decision-making in R&D project planning.
Major changes in the demographics of aging in the United States have created demands for geriatric care which cannot be met by existing services. Most states have elected to address this policy issue by offering incentives to providers to promote investment in long term care facilities. These offerings have been only marginally successful due to the relative attractiveness of competing investment options. This paper explores provider reaction to policy incentives using a System Dynamics model derived from Catastrophe Theory. Provider behavior is seen as unstable under competing investment options; a behavioral condition which conforms to the typical “Cusp Catastrophe”.
A fast, interactive, large-scale, data-base-oriented simulation language (LAMDA) for IBM compatible microcomputers has been developed for System Dynamics' applications. Sophisticated output features include high-resolution graphics, full report generation capabilities with textual explanation, and user defined screen menu options, An integrated sensitivity/confidence package allows parameters or structures to be evaluated as a function of time and as a function of all other parameters for their impact on model results. Confidence intervals are determined along with the time and circumstances where certain information is critical. An integrated statistical package can be used to estimate model parameters based on historical information or, in combination with the data base, used to test model hypotheses and statistical inferences. LAMDA can also interface with FORTRAN applications. Extensive dialogue capabilities allow the model builder to make the model user-friendly and fit the need/sophistication of the client.
Model behavior evaluation is an important component of System Dynamics (SD) model validation. SD methodology has often been criticized for its lack of quantitative/formal behavior evaluation tools. System Dynamicists have responded by stating the relative, subjective, qualitative, nature of model validation. We argue that using formal quantitative behavior tools is not inconsistent with a relativist, holistic philosophy of model validation. We suggest a multi-step, quantitative behavior evaluation procedure which focuses on individual pattern components of a composite behavior pattern. The procedure is relatively easy to apply and to interpret. We then test the performance of the procedure through a series of simulation experiments. The experimental results suggest that the multi-step procedure is appropriate for SD model behavior evaluation. The experiments also give us an idea of what the expected value and the variations of suggested quantitative tools are.
Many features are necessary in a behavioural model of household car ownership and usage patterns. A description is given of the features of conventional equilibrium-based models, followed by a discussion of the most important dynamic issues underlying travel choice. These issues include household travel and activity budgets; state-dependent factors such as information search, cognitive processes, habits, attitudes, and inertia; and the role of the household lifecycle as a choice catalyst. Recent dynamic modelling approaches are described, followed by a description of a system dynamics modelling approach which incorporates the dynamic hypotheses discussed throughout. Finally, a direction of research is laid out, in which the model can be used to simulate household panel data as a basis for hypothesis training.
This paper discusses the reasons why Systems' Dynamics models frequently encounter considerable difficulties in gaining acceptance and suggests several ways for overcoming this obstacle. Resistance to models within organizations is usually generated by one or several of the following causes: insufficient credibility of model's proponents, inability to grasp model's usefulness, cultural background, fear of losing power and negative previous experience with models. In the special case of models addressing issues of wide public interest suggestions are presented on how to plan a communications strategy designed to generate support for the model or for the conclusions derived with its help.
This paper discusses some dynamic effects of robot's introduction on a company in the electric appliances industry. Two key aspects are analysed. The effects on cash flow are explored first, the conclusion is reached that under certain conditions it could represent a controlling element that would slow down the rate of robots' introduction with the respect to the ideal rate suggested on the sole basis of economic convenience. The availability of skilled personnel is considered next. This availability increases through on the job training as more robots are installed. Under most circumstances, however, the availability of skilled technicians represents a controlling element that definitely slows down the introduction of robots. The effectiveness of training technicians therefore represents a variable of strategic importance.
This paper describes the importance of feedback loops included in a policy model constructed for the Office of Conservation of the Bonneville Power Administration (BPA). First there is the description of the region and the responsibilities for conservation planning at the BPA, and then a description of the purpose, structure, and use of the policy model. Several feedback loops involving customer response to higher electric rates are selected for our discussion of feedback. The system dynamics treatment of these feedback loops is contrasted with the treatment found in most electric utility planning models in the USA. The paper concludes with an assessment of whether the inclusion of feedback has been important in BPA's application of the model.
This paper reviews techniques that may assist the system dynamics modeller in defining variables and functional relationships, parameter estimation, validation, sensitivity and policy analysis. The evaluation was made in the context of water resources management modeling effort for the Guadiana basin in Algarve and based on scientific, economic and operational criteria. In general, it was difficult to point out the most appropriate technique but rather recommend combinations of methods for each modeling stage.
This paper introduces a new linguistic dynamic simulation methodology, SLIN which deals with systems defined in either qualitative or quantitative terms. The simulation mechanisms proposed in SLIN include a set of logical rules and fuzzy set theory. An application of SLIN to Sado estuary showed its promise but also some of its present limitations. Future developments including an appropriate diagrammatic representation, a new linguistic simulation computer language, implementation in parallel computers and subsequent real-time multi-expert based simulation are also discussed.
Low Back Pain (LBP) is the most common cause of work loss after the ordinary cold, and it is the single greatest source of compensation payments. In the U.S., it is estimated that one million workers sustain a low back injury every year, and that 217 million work days are lost annually at a cost of 11 billion dollars for males aged 18-55 alone. In an effort to better understand how to control the economic impact of this disorder, a System Dynamics model is being developed. It is hoped that the model, by generating scenarios on the cost effectiveness of different interventions, will provide useful insight into specific policies to fun research addressing the causes of LBP disability.
The techniques currently used for the management of urban road transportation systems are briefly reviewed, and the extent to which they take account of the dynamics of the system examined. Recent work on the development of mathematical models of urban traffic systems is described and the applicability of the model to real-life traffic systems explored. In particular, the ability of these models to reflect temporal as opposed to spacial properties of the system is examined, as well as their ability to assist in the formulation of strategies for system control. The role of system dynamics might play in overcoming some of the problems encountered is then discussed.
Models based on a logic relating military ownership costs to active force assets were developed. Historical budget analyses provided relationships to tailor the models to each military service. The models, validated through projection of the 1980-85 defense growth period, were then used to predict 1986 to 1995 appropriations using top line fiscal levels as inputs. The models can explore policy options such as reduced fiscal growth, altered readiness policy, and changed innovation plans.
Traditional economic theory emphasizes the determination and characterization of static equilibrium. In contrast, understanding of economic behavior can be enhanced through the use of models that explicitly take into consideration the underlying physical and decisionmaking structure of the system and that allow for disequilibrium. This paper presents an example of such a model. A typical static, open input-output model is translated into an equivalent disequilibrium model. It is shown that objective individual decisions can lead to unintended oscillatory modes of behavior of the overall system. An assumption of perfect information can prevent such undesired oscillations. This paper also demonstrates a way of communicating system dynamics thinking to an economics audience. The model is developed in progressive steps, a procedure that is widely found in economic literature. First, stocks are added to a model that originally considers flows alone. Each of three succeeding model changes is then motivated by the results of the previous model and presented as a logical next step towards a more consistent theory. Thus, it is not only the result of the final model as such that is of interest, but also the way the model is developed. Model development is presented as a learning and communication process.
The Le Moigne's theory of General System is presented and applied to the transportation system. A model of this system, using accessibility and generalized cost as the variables to be controlled is also sketched.
In this paper we review the algorithm to identify the type of variables (levels, rates, auxiliaries) which appear in the influence diagram. This algorithm has been implemented on a personal computer at the Cagliari University.
There has been a great deal of work done in the simplification of linear dynamic models. Given that most models that are in use are nonlinear this has restricted the applicability of the available techniques. By concentrating on a particular nonlinear phenomenon, in this case shifting loop dominance, it is possible to use the techniques of linear analysis for the simplification of nonlinear models. The theory for this is developed and it is shown how this can be applied to the model. For purposes of exposition the market growth model is used and the results are encouraging. Though there is still a good deal of work to be done it seems feasible to develop simplification techniques for nonlinear models that address directly the nature of the nonlinearities.
Much of the work done in system dynamics has been criticized for making insufficient use of statistical estimation techniques. There have been various responses to this criticism concentrating on the other sources of information available to the model builder. One of the major hurdles to the use of statistical estimation techniques is an understanding of when they are likely to be useful in system dynamics modeling. In this paper we consider different estimation techniques and how useful they can be in system dynamics modeling. The work is meant to be a practical guide that will allow the modeler interested in statistical estimation to gain some understanding of the different approaches available. We concentrate or attention to the special problems that the system dynamics modeler is likely to encounter in estimation.
Studies of deterministic systems which apparently exhibit chaotic behavior are attracting much interest in disciplines ranging from physics to economics. A particularly interesting case of a simple electrical network has been studied recently in the physics literature with the objective of isolating minimal characteristics essential to chaotic behavior. A system dynamics formulation has been given to the numerical simulation of this system. Instructional laboratory exercises comprising both observations on the electrical circuit and computer simulation of the circuit are being implemented for the upper level undergraduate and graduate students.
The Jutland Technological Institute (JTI), Aarhus, Denmark, has embarked a project to promote the utilization of System Dynamics models in Danish Industries. The vehicle of this projekct is a new type of hybrid computer, the MOSES (Modular Symbolic Electronic Simulator) system, developed at the Technical University of Denmark. In ongoing projects the MOSES system has demonstrated itself as an invaluable “discussion” partner. We have performed a series of seminars with managers from medium and large sized Danish companies. At these seminars some of the generic structures of growth companies have been discussed and related to Danish conditions. This report contains a brief description of the MOSES system and a description of the ongoing project.
This is a report of several applications of System Dynamic Methodology to banks, with particular emphasis given to their structure and their Decision Making in terms of System Dynamic concepts. Aplications range from policy design and long term planning to the design of Decision Support systems. The first part presents relationships between money flows and accounting information. Next, some policy design results are presented. Later on, the estimation of the parameters of the SD model is transformed into the heart of a Decision Support System.
The direction of causality between financial deepening and economic development is tested. Using factor analysis, two indexes are developed to represent the two economic phenomena for the Philippines. Time series causality tests are used to evaluate the direction of causality. The results indicate the causal pattern reverses over the history of the sample. Reversal is viewed as the result of financial repression. The structural dynamics implied by the empirical time series test is evaluated using a system dynamics model. The growth promoting and growth inhibiting roles of the financial sector are simulated in the dynamic structure of a dynamic economic development model.
A representation of socio-economic systems using reduced models allows a “qualitative” type of analysis to be carried out. It is often the case, especially in the long term process, that the main interest is directed towards the asymptotic behavior of the solutions as a function of the initial state and to evaluating the properties of stability of stationary states. In this article, after a short outline of the procedure and methodology adopted, we describe the application of these techniques in the construction and use of a dynamic model for the design of a tourist village. The model, which mainly deals with the impact of man on the environment, serves to evaluate the social and economic effects of the construction of a tourist centre in a national environment which must be conserved.
Power demand forecasting methodologies which are currently being used by electricity authorities are end use method, trend method and Scheer's formula. These methodologies being static in nature, do not take into account the future power supply position, while becoming an important instrument of economic change the growth of power generation activity itself is totally dependent upon the overall economic development thus forming an important feedback loop in the economic system. Present paper discusses a power economy system dynamic model for estimation of future demand and supply position of Power.
The paper is an attempt at a theory of relations connecting feasible observations/ or measurements/ and feasible decisions/ or controls/ in general cybernetic systems. The theory gives a formal framework and a tool for quantitative analysis of the following facts: 1. An increase in observation possibilities, e.g. an increase of the precision of measurement, enlarging the scope of observation etc., results in an increase in decision possibilities by making more effective decisions possible. This works also in the other direction: if there are more feasible decision, new observations or measurements become available. 2. In the framework of a cybernetic model no decisions and/or observations which generate antinomies can be simultaneously feasible. This creates interesting and important constraints on measurements and decisions in systems which include man or where a human or automatic decision maker is an object of observation, and where the results of observation may be known to this decision maker. 3. The observation/measurement/ takes tome and changes its object and thus the result of observation always refers to past rather than to the present. This normally is due to physical effects through other phenomena, like psychological, may also be important depending on the nature of the object. The facts of group 1 are in a sense opposite to those of groups 2 and 3. This leads to the existence of optimum decision-measurement possibilities. Conditions for this optimum to exist together with its significance for biological and technological system will be discussed. The subject of this paper is of interdisciplinary interest and has been studied, partially and from particular angles, within the framework of control theory/facts of group 1/, mathematical logic/theory of antimonies, principles of mathematics-mainly facts of group 2/, physics/theory of measurement, principles of quantum machanics-mainly facts of group 3/ and philosophy/the classic problems of free will and consciousness/. The relevance of the presented theory to these fields will also be discussed.
This paper presents the findings of my research in artificial intelligence applications for system dynamics. The sudden appearance of microcomputers in homes, schools, and businesses has opened an opportunity for dissemination of system dynamics to a wider audience than we could have ever hope to reach with the earlier computer technologies. This opportunity should not be lost by clinging to obsolete, or soon to be obsolete, technologies. User-friendly micro-based software should be immediately available to those individuals, schools, and corporations who are interested in systems thinking. The demand for such systems far surpasses the current supply. Artificial Intelligence software is now available for microcomputers. This new software development can significantly improve current and future systems for the novice and the experienced system dynamicist.
“Generic models,” as the term is emerging, denotes a model representing the underlying causes of commonly occuring sets of problems, whose purpose is for education, rather than for policy analysis per se. Preliminary uses of generic models have been an exciting and efficient means of transmitting insights. This paper is a status report on the modeling of a company's conversion to a new production or product technology. Based on information sources including in-depth interviews within such companies, the authors' previous experiences, and published surveys and cases, the planned model focuses on management goals, staffing, and acquisitions of the skills necessary to deal with the new technology or product. Although the model does not explain every (complete or partial) implementation failure, it seems relevant to a significant fraction of such failures. The authors intend to develop the model and curriculum materials for management education and portions of university courses on technology management.
Although there are more than 3000 end uses of aluminium in the world and more than 300 in India, yet there are five sectors viz. power, consumer durables, transport, building consturction canning and packaging which account for more than 90% of aluminium consumption. To study the dynamics of demand of aluminium in these sectors, system dynamics model having various sectors viz. Population, economy, power, consumer durables, construction, packaging and canning, transport and aluminium consumption model has been simulated from 1970 to 2000 A.D. using dynamo.
Within the MIT System Dynamics National Model, the risk-free interest rate is determined jointly by the normal interest rate and by liquidity. The normal rate is the rate which agents believe would obtain under normal circumstances, in the absence of transitory pressures. The normal rate continually adjusts to new interest rate conditions. During times of deficient liquidity, agents will increase the risk-free rate above the normal rate. The converse also holds. The risk-free rate will continue to adjust until pressures in the system are relaxed. Estimation results support the national model theory of interest rate formation.