Accelerating the rate of economic growth in developing countries has been the important aim of almost all development policies implemented over the past three decades. Experience has shown that such growth is often not sustainable and is likely to be interrupted due to the occurrence of violent political changes. The paper attempts to identify the organizational factors which limit economic growth and which create conditions conducive to the outbreak of political violence. A mathematical model of the socio-political system of the developing country is developed and its behavior is studied using simulation.
This paper examines the role of food producers, population, and the government on the present availability of food in Bangladesh. The study employs a system dynamics model of the population-food-production system for its analysis. This model incorporates mechanisms of production and consumption of food, and population growth. Government policies are considered exogenously. The analysis suggests that, due to the presence of a feedback relationship between food availability and population growth, any policy for improving food supply cannot be considered independently of time. In the long run, none of the policies tested alleviates the shortage, although in the short and intermediate runs, agricultural development and population control policies may improve food consumption per capita. The paper thus seriously questions the rationale of agricultural development policies aimed at increasing food production. However, since many food surplus countries support small populations which are also growing at slow rates, points of entry for policies that effectively alleviate the food shortage should exist. Thus, food policy models for the developing countries should aim at identifying such entry points into the system instead of attempting to increase the food supply.
Socio-economic planning primarily addresses the solution of problems relating to inherently indeterminate systems. The class of systems exhibits two sources of complexity which can be conceptualized as the complexity of the idea system and the complexity of the actual physical system. The idea system introduces a multiplicity of available theories, disciplinary differences between the stakeholder roles. The actual system is complex because there usually is not sufficient empirical data relevant to the particular problem since the situational context is unprecedented and non-repeating.It can be argued that problem solving in this context involves designing a new system structure to facilitate social learning, using a heuristic approach. Such a heuristic is different from the more conventional approaches to modeling and problem solving in that it bounds the search space and enhances further inquiry rather than just reflecting the real world conditions. In this paper the main characteristics of this approach are discussed and methodological implications for System Dynamics modeling are drawn.
System dynamics has been taught for over two years in two doctoral programs offered by Nova University, Fort Lauderdale , Florida. These programs are designed for working professionals in public and business administration and feature the inverse of the usual arrangement in which instruction is given on the university campus. For this reason, a traditional teaching approach cannot be used. This paper describes the Nova teaching environment, the format and teaching materials used for system dynamics, student characteristics and performance, and the present trends which affect instruction in system dynamics at Nova University.The introduction of the course in system dynamics has generated a positive response among the students and a limited amount of turbulence in the organization and administration of the program.
Planning tourist facilities is a highly complex task. It is necessary to evaluate carefully, with an interdisciplinary approach, all the variables of a technical, architectural, commercial, economical and financial nature that may be involved in a given project, without however ignoring the natural resources of the environment where facilities are to be set up. For a correct evaluation, these resources must be considered limited and seen as a wealth that can be exploited but not wasted, used but not destroyed. The approach outlined above is all the more important in countries like Italy, for instance, where there is a risk of over-exploiting the natural resources of the environment. In all but exceptional cases, an evaluation that does not take the above principles into account will result in a tourist enterprise that is ultimately a failure, as it degrades, often irreparably, the natural environment until it ceases to be an adequate source of revenue. This paper describes an integrated approach which provides, by means of simulation techniques, tools for a proper implementation of tourist facilities taking into due account all the variables and constraints involved, and likewise for the assessment by the Public Administration authorities of the wisdom and soundness of projects submitted to them for approval.
The purpose of this paper is to expand our thinking about the possible role system dynamics may play in the evolution of western thought and society. While such a theme may seem presumptuous when applied to a toll known to only a small fraction of people at present, it is my intention to give it some credibility by showing that western society may already be in the midst of evolving fundamental assumptions, beliefs and perceptions more consistent with a systemic world view. Pulled by this undercurrent, tools like system dynamics can focus the forces of change and bring them to bear more directly on pressing societal problems.
Visicalc, the original spreadsheet program for microcomputers is explored for suitability as a vehicle for system dynamics models. It is shown that Visicalc can support most of the model features that DYNAMO allows, but at the price of some inconvenience and care needed when setting up the model. However, with the widespread distribution of spreadsheet programs among decision makers, there maybe situations where they may be the vehicle of choice for implementing a dynamic model.
The paper discusses an application of SD to the modelling of ground force combat at about Corps level. The model is based on Lanchester’s equation incorporating concepts for the build-up of combat-ready forces and alternative strategies for their commitment in relation to beak-through criteria. These alternative strategies, together with the appropriate tactical rules for force employment and deployment, determine what may be regarded as policies for the use of forces. The model has been used to investigate these policies and the effect of delays in their implementation. Some illustrative results and conclusions are also discussed.Note: There is no paper available.
System Dynamics models are often faulted for their reluctance to employ formal measures of goodness-of-fit when assessing the historical behavior of models. As a result, the validity of system dynamics models is often questioned even when the model’s correspondence to historical behavior is quite good. This paper argues that the failure to present formal analysis of historical behavior creates an impression of sloppiness and unprofessionalism. After reviewing the concept of validity in simulation modeling, the paper proposes a simple set of summary statistics appropriate for system dynamics models (the root-mean-square error and Theil inequality statistics). The statistics allow the error due to individual behavior modes to be analyzed, do not require the use of formal parameter estimation procedures, and can be conveniently computed. A large model of the U.S. economy is used to illustrate the use of statistics.
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.
Many firms use financial ratio analysis to monitor their control over the operating cycle and to serve as the basis for policy formation. Ratios are based on data produced through the accounting information system which is analyzed according to intuitively plausible concepts in order to make normative judgement about the financial health of the firm. A model is constructed to simulate the operating cycle of a business which generates financial ratios in a manner analogous to the accounting system. It is shown that noise and seasonality produce distortions in the ratio measures are spread throughout the system in a dynamic and complex fashion. Further experiments reveal that plausible control policies based upon financial ratios may make performance worse rather than better. System Dynamics appears to be a useful approach both to redesigning financial ratio measures and testing policies which could enhance out ability to manage such systems.
In this paper some of the ideas of Ortega y Gasset about the dynamics of history have been gathered and organized according to the system dynamics diagrams. A cyclic process, characteristic of every normal course of history, is described as well as the dynamics hypothesis responsible for it. Human life, as far as it affects history, is shown as being composed of five age groups each of them covering fifteen years of life. Two of these groups, two generations acting simultaneously in the field of history, are presented as taking the main responsibility for the dynamics of history.
:One of the traditional obstacles to effective utilization of simulation models has been the great deal of time spent learning languages in which models are written and keeping track of the specific variable names and equations within models. To remove the excessive psychological burden from busy executives and to refocus attention towards the actual behavior being replicated, Inter/Consult has been researching development of highly supportive user interfaces to models. These interfaces prompt users by stating the nature of the model’s assumptions then asking what changes they would like to make. Through this on-line question-and-answer dialog users can build and compare scenarios without prior knowledge of computer languages and mathematical formulas or specific model components. Our paper presents reactions to the interface by members of the graphic arts industry who have used it. We discuss further improvements which are being made to the interface to make our models more accessible to non-expert users. Finally we explain why we feel that tightly-focused, easy-to-use, dynamic simulation models are of invaluable benefit to any industry such as graphic arts where craft-oriented skills are being replaced by rapidly evolving new technologies.
This paper uses a system dynamics simulation methodology to assess the potential effects of new accounting policies being considered by rule formulating bodies. The key objective of this paper is to demonstrate that current ex-ante intuitive assessment of the effect of proposed accounting rules is inadequate due to the counterintuitive nature of economic consequences in a complex social system. For this purpose a very simplified model of he US economy is developed and its parameters varied to reflect potential accounting policy changes. The effects of these policy changes are shown to be counterintuitive in nature, requiring consideration of second and third harmonics of the feedback loops for adequate ex-ante impact assessment. This paper is divided into six parts: the first part describes alternate approaches to economic consequence assessment and the advantages and disadvantages of utilizing the system dynamics methodology; the second part describes the skeleton of the system dynamics model; the third part examines the measurement problems of rates, levels, and delays as well as reviews the details of their computation for model formulation; the fourth part discusses the problems and results of model validation efforts; the fifth part describes some of the results obtained from application of the model, and their meaning in comparison with traditional methodologies for accounting impact analysis; the sixth part concludes by suggesting the next step for macro-accounting modeling: evaluating the potential and shortcomings of this methodology.
A disaggregate population model of China is presented. The age structure is represented by one-year cohorts. Urban and rural populations are distinguished. Birth and death rates, family size, life expectancy, and other demographic variables are determined endogenously. The model can be used to analyze population problems and to project population size, the age structure, the adult labor force, the elderly population, and so on. The model can be used in two modes. It can be used to project the consequences of various exogenous fertility levels. Alternatively, birth rates and fertility can be determined endogenously by economic inputs such as food supply, GDP, and services. The model incorporates socioeconomic factors important in the demographic transition, such as the effect of perceived life expectancy on fertility, the effects of traditional values, and the ability of government to influence family fertility choices. The model can be used to evaluate policies and programs designed to control population growth, such as delayed marriage age, improved contraception, and restrictions on family size. The model requires industrial, service, and food output per worker as inputs, and also the level of pollution. The model should be thought of as a component of a comprehensive planning model which generates these inputs endogenously. Based on the system dynamics approach to modeling complex systems, the model is implemented in the DYNAMO simulation language.
Much of the literature on model evaluation focuses on what amount to absolute measures, that are independent of the context in which a particular model is used. This paper argues in favor of situation-dependent measures. Whether or not a model is “good enough” depends on the job it is being asked to do and the mid set of the people who must use the results. The relationships between model adequacy and successful implementation of model-based recommendations are discussed. While rejecting the classical paradigm, the author emphasizes model realism and historical accuracy as important determinants of implementation. The life of the model involves many evaluations of whether it is “worth the costs”, “believable”, “useful”, and “right”. Issues surrounding these judgements are explored. How differences in circumstances can lead to different, but in each case quite adequate, models is illustrated by contrasting two models developed five years apart for the same organization. The paper concludes that successful models are persuasive, not simply to modeling technicians but to high-level decision makers.
In the health sciences, concepts are shifting toward system models which recognize multiple factors interacting to determine health phenomena. The hybrid biomedical disease model has proven insufficient for the analysis of modern health problems. A population perspective and an expansion in the influence of the behavioral and social sciences have required conceptual models with greater breadth, and facility in relations between models. Morbidity is portrayed here as two domains of phenomena, the disease process and the illness state, each seen as part of a socio-ecological dynamic. Applied to major disease problems, the utility of these propositions can be examined. In the McMaster M.D. program, this set of models has been translated into a curricular structure which has the individual in all her/his healthy or morbid aspects as the interface between biological and social systems. Perplexing dilemmas in health care thus become not only understandable but predictable. Adopting this approach creates a new generation of problems. Just as our students have become familiar with the critical appraisal of evidence, the testing of conceptual models becomes a necessary skill. The background of this analysis is the socio-ecological niche of concepts. A model of models is proposed in which concepts interact with problem environments and modern medicine emerges as a case study for socio-ecological epistemology.
The premise of this paper is that System Dynamics has, in the past, been primarily perceived, both by external observers and by most of its own practitioners, as a technique of computer simulation. Although this situation is changing, there is still little wide scale recognition of its true generality and relevance as a complete subject of systemic enquiry. The purpose of this paper is to explore the merits of system Dynamics as a total systems methodology. Specifically the presentation will undertake to review the need for and the requirements demanded of such problem solving methodologies, to briefly explore the dilemma resulting from historic attempts to create them and to present changes to the existing Systems Dynamics method which might improve its conformity and acceptability as such a methodology. These include the formal definition of Qualitative System Dynamics and the presentation of a set of rigorous rules to provide much needed guidance in its application; firstly, Stepwise Influence Diagramming, aimed at enhancing problem exploration and model development and secondly, Qualitative analysis, aimed at identifying critical system components and exploring the effects of change.
System Dynamics as a methodology has traditionally been concerned with the study of processes that can be described by continuous variables. Discrete or integer events, such as the number of sales made in a day or the number of factory closings in a year have either been approximated as continuous variables or else not dealt with. This paper examines another way of dealing with discrete events through the realization that any discrete event has a certain probability of occurance. These probabilities are continuous and conserved quantities and can be modeled as system dynamic levels. Treating probabilities as levels in dynamic simulations is a standard technique in stochastic modeling, markov models being one example. System dynamics' advantage over these other methods is that it can represent the impact of the results of the probabilistic study of the social feedback systems. This paper focuses on examples demonstrating the use of system dynamics to model uncertain events. These examples deal with the simple case of a Poisson process with a time varying event arrival rate. Extensions incorporating conditional and independent probabilities are also considered.
Case studies of regulatory and social programs suggest that policy systems are dynamic. In the systems described, outcomes depend on how variables interact over time, and feedback among variables--“simultaneous” causation over multiple time periods--is more a rule than an exception. However, the most influential evaluations of public programs are studies using multiple regression. A recognized limitation of multiple regression is its relative insensitivity to multiperiod strategies, feedback among variables, and other dynamics. Accordingly, we maintain, the findings of regression-based and case studies commonly conflict. Simulation modeling can serve as a methodological bridge between case studies and regression-based studies of policy systems, improving theoretical models of the system and providing a way to evaluate the robustness of alternative regression models. The results of some early experiments along these lines are presented.
The Algarve province in southern Portugal has been undergoing a rapid growth due to a large increase in tourist demand. The mismanagement of the region’s water resources is leading those growth trends to halt. This paper introduces a model developed to provide a needed rational framework for Algarve water resources management, interfacing a system dynamics model with multiobjective programming formulations. The definition of water supply and demand sectors, on a spatially disaggregated basis, is an essential component of the model, with attempts to provide a tool to evaluate the effects of different strategies controlling water supply and demand upon a set of impact variables. To select an optimal strategy one has to solve a multiobjective programming problem, where the components of the objective function are the impact variables referred above. Solution methods include the analytic hierarchy process and the value display approach. The model written in Z-BASIC was run using a simulation period of 10 years.
Practitioners of system dynamics working in the government sector will often operate in environments filled with administrative complexities and bureaucratic inconsistencies. Some examples of less than ideal conditions encountered in a fairly large policy planning effort are here offered for the student of system dynamics.
The purpose of this model is to gain insight into the relationship between poverty and AFDC assistance, to diagnose and explain causes and- on the basis of these findings- to test policy alternatives to alleviate poverty.
The interaction between the speaker and his audience is a subject of universal interest, especially to professionals. It is a subject, moreover, requiring a dynamic method of analysis. This paper presents a conceptual model of public speaking. The purpose of this preliminary study is to identify the essential factors needed for (1) the effective delivery of a prepared speech in a conversational manner and (2) the growth of the speaker's abilities over time. As a result of my preliminary analysis of the feedback loops operating during a technical presentation, my approach to teaching novice speakers has changed. One benefit of my new approach is that it accelerates the process by which novices develop the competencies they need to give successful informative speeches. Further study of the interaction between speaker and audience using System Dynamics will contribute significantly to our understanding of human communication.
The System Dynamics National Model represents a typical, modern, industrial economy. Although parameters have been chosen for the United States, the behavior modes exhibited by the model are those being experienced in most economies in Western developed countries. The National Model incorporates a wide range of dynamic structures that allow its behavior to span from the short-term business cycle of 3-to-7 year periodicity to the much longer-term behaviors represented by growth and by major depressions that recur at intervals of some fifty years. The System Dynamics National Model has been under development for about twelve years. An evolutionary process has been followed during which we have extended the scope of the model, added sectors, identified and corrected misbehavior, and simplified unnecessarily complex structures. There have been more than a thousand modifications and extensions of the Model. The National Model is now close to meeting our primary objectives, and we have started writing four books describing the Model and its implications for economic behavior.
The acronym “MDS” refers to the methodology and a series of computing techniques which are suitable for the simulation of corporate processes. These “Dynamic Models for Corporate Strategies” allow the description of such processes as structures of a unified nature, into which one may insert all the necessary data (real or hypothetical) deriving from the initial and boundary conditions, to clearly define the possible future developments being studied. With respect to other, currently available, decisional aids, MDS differs both by its purely simulative approach and by its use of the basic descriptive structure capable of completely representing the dynamism of corporate phenomena. Compared to a “company microcosm” description using the now classical methods of Industrial Dynamics, MDS offers open and interactive systems also introducing several “corporate variants”. (These correspond both to certain types of sub-division of the complete system into given sub-system, and to relationships which may also be described in the same terms, such as the ‘accounts plan’, for example). The main aim of this paper is to analyse the effects of promotional activity- recently developed in Italy amongst medium and large companies- whose main objective is the introduction of MDS as an imprtant instrument in the practice of corporate planning.
A generic model of adaptive systems behaviour is developed in causal loop form. Examples from many different living systems are given. Living systems do adapt: plants turn towards the light; birds fly south in the winter; people acquire a taste for champagne; revolutionaries become government bureaucrats; and cultures have dealt with horseless carriages and jet travel. Living systems also collapse: lakes get polluted and die; dinosaurs are no more; people commit suicide; there is no more Federalist party; and the Indian Nations of North America have all disappeared. As a system dynamist I am interested in the attribute or, more exactly, the minimal set of attributes of all these systems that can explain the capability to adapt and also the obvious limits to that same capability.
The paper describes eight problems within the Cable Division of Standard Telefon og Kablefabrik A/S which are currently being analyzed using system dynamics. Problem 7, concerned with information system projects, is described in detail.
The System Dynamics National Model is a large computer simulation model of a typical industrialized economy, with its parameters adjusted to reflect the size and character of the United States. The model's purpose is twofold: understanding the major difficulties of the aggregate economy such as inflation, business cycles, and slowing productivity growth; and to facilitate the evaluation of policies to influence those behaviors. In the existing publications on results from the National Model, the structure of the model is described in a page or two, doing no more than supplying a flavor for the scope of the model. This paper goes to the next stage in describing the content and structure of the model for those readers with some previous exposure to the results of the National Model research. The discussion starts with the overall architecture, then goes through the major connections among the sectors of the model, and concludes with one example of more detailed structure: the interrelations among selected decisions in the corporate sector of the model.
The scope of this paper is to present our views on teaching System Dynamics and Dynamo in our courses in System Analysis at Uppsala University. We treat the pedagogical aspects as well as the hardware and software system we built around Dynamo. A large part of this article is devoted to ideas and constructive criticism of System Dynamics and Dynamo which we have acquired from our experiences in education and research.
This paper examines the dynamics of “worker burnout”, the process in which a hard-working individual becomes increasingly exhausted, frustrated, and unproductive. The author’s own two-year experience with repeated cycles of burnout is qualitatively reproduced by a small system dynamics model which portrays the underlying psychology of “workaholism”. Model tests demonstrate that the limit cycle seen in the base run can be stabilized through techniques which diminish work related stress or enhance relaxation. These stabilizing techniques also serve to raise overall productivity, since they support a higher level of energy and more working hours on average. One important policy lever is the maximum workweek or “work limit”; an “optimal work limit” at which overall productivity is at its peak is shown to exist within a region of stability where burnout is avoided. The paper concludes with a strategy for preventing burnout which emphasizes the individual’s responsibility for understanding the self-inflicted nature of this problem and pursuing an effective course of stability.
The System Dynamics model described in this paper presents a new approach to the mechanisms of subcutaneous absorption of dissolved insulin. Experimental investigations have shown that the apparent absorption constant varies in time, and that this variation depends both on the volume and the concentration of the injected insulin. Our model assumes that insulin is present in the subcutaneous depot in three forms: (i) a dimeric form, (ii) a hexameric form, and (iii) an immobile form in which the molecules are bound in the tissue. The model describes how diffusion and absorption gradually reduce the insulin concentrations and thereby shift the balance between three forms according to usual laws of chemical kinetics. By assuming that only dimeric molecules can penetrate the capillary wall, we have found that the model can fully account for the observed variations in the absorption rate. At the same time the model can be used to determine at least 5 parameters characterizing the involved processes: the diffusion constant for insulin in the subcutaneous tissue, the absorption constant for dimeric insulin, the equilibrium constant for the dimeric/hexameric polymerization process, the binding capacity for the insulin in the tissue, and the average life time for insulin in bound state. Combined with a simplified model of the distribution and degradation of insulin in the body, the diffusion-absorption model has been used to simulate different insulin delivery schedules, i.e. a single major injection contra dosage with infusion pump. The model has shown that a pump repetition frequency of 1-2/hr can secure a sufficiently constant plasma insulin concentration.
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.
This paper presents a computerized system dynamics game in which the player makes "annual" decisions controlling the availability and evaluation of a new medical product with uncertain potential and possible (though initially undetected) side effects. The game has been implemented using the popular spreadsheet program Lotus 1-2-3. This program has on-screen display capabilities allowing for the construction of a user-friendly game that requires no knowledge of system dynamics. A detailed discussion of game mechanics is followed by a description of a classroom experience which led to further development of the original version of the game and some general insights about game-building.
In the past, the most popular computer models for the construction management of major buildings were large models based on the graph theory and their consequent discrete event simulation on the mainframe computer to have a view of the operational level. We think that in the future if we want to remain competitive on the world market the trend will be the use of small system dynamics generic models in relation to micro-computers at the strategic management level that can generate the reference modes i.e. the project control baselines.
The long term success of System Dynamics is largely dependent upon the dissemination of systems thinking to a considerable segment of the general public. A strategy for exposing a non-academic, adult audience to the basic characteristics of systems is developed, using the ADAPT Learning Cycle, System Dynamics, and the Social Fabric Matrix.
China has the greatest population in the world. The impact of the population on Chinese economic development is great. Based on Chinese National Economic Model NATN3, the relationship between the population control policy in China and Chinese economic development are obtained by simulation of the policy analysis.
The System Dynamics Generalized Substitution Modeling is presented. This modeling considered the influence factors of circumstance by introducting action function. The methodelogy is based on the System Dynamics with econometrics, combining three postulates in product substitution and decomposing multi-product into several two-product substitution. Parameter estimation, which existed in all System Dynamics Modelings, is one important but still unsolved problem. Now this problem has been solved in our paper by orthogonal simulation, it is based on the orthogonal theory and generalized least squares (GLS)
A multi-sector, input-output version of Sterman's simple Long Wave Model is developed to investigate the validity of the capital self-ordering theory for a more realistic system with diverse capital types. Simulation experiments with varying capital lifetimes and input-output coefficients tend to reproduce the characteristic fluctuations in capital production, caused by self-ordering, with a period in the 30 to 70 year range. However, complex patterns of oscillation with wide variance in period can emerge, explained by varying dominance of self-ordering loops. The analysis thus confirms the destabilizing effect of self-ordering and its significance for long term fluctuations while raising issues and generating new insights about the-long wave.
A simulation model of the passenger transportation system is presented. The model has been built in order to carry out a series of simulation experiments. The purpose of these experiments is to compare the effects of sore transportation policies on road congestion, modal-split, air pollution and transportation fuel consumption. System dynamics principles have been used for simulating the model. The statistics of Delhi urban area have been used to calibrate the model.
This microcomputer workshop is being developed to encourage exploration, testing, and discussion of the impact of alternative arms-building policies. The model allows participants to adjust parameters that reflect a number of psychological, technical, and political factors. For example, participants can represent one country's tendency to overestimate the strength of the other and underestimate its own strength. Before releasing the model to the public, we are reviewing its conceptual soundness and its educational effectiveness to be sure that it reflects empirically supported technical, psychological, and political realities. The presentation of this paper and the early versions of the workshop are part of this preliminary review process.
With a new information system, the "order-production-distribution" system can be managed as a whole in terms of corporate performance. But there is a possibility that such a system can be damaged easily from degraded information conveyed through an information network. This paper is concerned with an approach to dealing with degraded information in light of risk management with the system dynamics philosophy.
Burnout is a problem associated with work in social service organizations. It is characterized by loss of energy, negative attitudes, and decreased performance. This system dynamics model encompasses the literature on burnout and belongs to a general class of stress and motivational models which describe problems of alcoholism and sexual harassment in the work place, etc. The gap between performance and professional expectations generates physical and psychological fatigue, which decreases involvement and performance. Supervisors frequently ignore the workers' problems, but will initiate structure when quality is perceived to decrease. The gap between expectations and performance may account for burnout initially, but cannot account for maintaining burnout after expectations decrease. Learned helpless may be the mechanisms that sustains burnout.
A method is described and illustrated for explicit incorporation of and computation with ranges of initial conditions, functions, and parameter values in dynamic models using interval analysis. This approach is neither a statistical nor fuzzy set analysis but instead utilizes interval arithmetic which is particularly well suited for computerization. When a dynamic model is couched in interval analytic terms, ranges of all possible solutions are generated allowing not only an analysis of ranges of behavior modes but for sensitivity and stability analysis to be performed as a natural part of the model. Moreover, uncertainties such as specification, numerical method (e.g., numerical integration), and roundoff errors can also be analyzed in conjunction with or separate from the interval dynamic model.
Many electric utilities have a heavily debt-laden capital structure. A number of factors have contributed to this situation, but chief among them is the theory that increased debt improves a corporation's earnings per share. This theory is derived from a relatively simple financial model which relates earnings per share, capital structure, interest costs, and income. Using a more comprehensive model, this paper shows that reducing debt as a percentage of capital structure can improve the interest coverage, earnings per share, and market price per share of electric utilities.
Mid-volume, mid-variety operations characterize flexible manufacturing systems (FMS) or job-shops found in most factories. Profitability of FMS depends upon effective scheduling of material flow, machine use, staffing, and buffer capacities. Many systems adjust to changes in demand and equipment failure in the long term. In the short term, however, large changes may occur in inventories, staffing requirements, and machine utilization. In general, these large changes reduce production efficiency and profits. An approach is demonstrated for attenuating or eliminating changes or swings in a system when there occurs some abrupt change. Delays and delay parameters in the system model are adjusted, subject to practical constraints, to produce a smooth and rapid transition after the change. A simple econometric model is used for illustration. A symbolic and algebraic manipulation language is required to implement the approach.
The work described in this paper is an extension of earlier work by the same authors on analysis of national development planning. A brief description is presented here of the system dynamics model developed for this earlier work as a basis for explaining its recent application to development policy design. A taxonomy of development policies is presented and the results of analysing seven policies, within an adaptive model framework, are presented, which are aimed at improving and achieving both growth and equity. Each policy is examined under conditions of continuous proportional control and discrete control based on a sector criticality.
A conceptual framework for modelling the dynamics of environmental systems is presented. It is argued that apparently stable systems can evolve via bifurcation when critical thresholds are exceeded. When a system is forced further away from equilibrium dissipative structures emerge. These dissipative structures are characterized by stochastic, non-linear feedback mechanisms which have the capacity to transform an apparently stable environmental system into a relatively more complex one which evolves. Some examples of these structures are simulated using system dynamics and the implications for further research are discussed.
Forecasting for complex nonlinear systems has proven to be elusive. Investigators have assumed the causes to be too little data and overly-simplified models. Recent studies in climatology reveal that nonlinear systems behave in ways quite different from the linear or static systems of traditional science and engineering. The behavior of nonlinear systems can be cyclical or essentially stochastic and usually is a mixture of both. New techniques, such as "attractors," are being devised to facilitate analysis. Methodologies must be applied with due consideration to the structure of the system under investigation.
By analysing the dynamics of a simple problem of urban migration, this paper illustrates how chaotic behaviour can be internally generated even in a relatively small (4-level) System Dynamics model. Two different groups of minority families are considered to move around between three sectors of a city. This migration occurs in response to changes in certain social indicators which we take to be related to the number of families already living in the respective sectors. Type I families, for instance, prefer to live in areas with many households of the same kind and tend to avoid neighbourhoods with many type II families. Type II families, on the other hand, although also they like to live together, are at the same time attracted to areas with many type I families. For normal parameter values, this system has an unstable equilibrium point. In base case it exhibits a limit cycle behaviour with the non-linear limiting factors associated with a slowing down in the rate of emigration from a certain sector as the number of remaining families approach zero. We show how the system develops through a Feigenbaum cascade of period doubling bifurcations as the inclination of type II families to move into areas with many type I families is reduced by. 15%. By calculating the largest Lyapunov exponent for the system we finally show how the chaotic behaviour is quantitatively distinguishable even from the most complicated limit cycle behaviour.
A Simulation Model for Corporateing Planning has been designed for a Steel Plant based on System Dynamics principles. This Model has been designed for Material flow that takes place through a group of 12 production shops arranged in six stages of production. The Model requires a time variant input of Demand of 17 categories of finished steel products and 3 categories of Raw materials. The Model generates behaviour of various objectives based on the assumptions of the environment. The Model can be used for simulating the impact of various strategic policy decisions on the corporate objectives. The Model also guides the management in designing their long term investment policies related to expansion, modernisation and debottlenecking.