Equilibrium models of organizational change are contrasted with a new model derived from nonequilibrium, nonlinear and dynamical system research. Kurt Lewin’s force-field theory is used as an example of the traditional equilibrium-seeking model. The characteristics of the new model are: nonlinearity; change in attractors; environmental gradience and nonequilibrium constraints; internal gradience; bifurcation; and self-organization. Advantages of the new model are described.
Freud’s theories are shown to rely on an equilibrium-seeking model derived from nineteenth century physics. This model is traced through Freud’s concepts of neuronal inertia; the pleasure principle; the primarily and secondary systems; instincts; the compulsion to repeat; the Nirvana Principle; the death instinct; and resistance. Quandaries concerning adaptation as well as the delay of discharge are attributed to the limitations of Freud’s equilibrium model. Next, the main features of far-from-equilibrium research are recounted, primarily from the work of Prigogine but properties of chaotic systems. The concepts of self-organization and dissipative structure, sensitivity to the environment, energy exchange, and nonlinearity help resolve the quandaries of adaptation in Freud’s theories.
The market place derives its dynamism from the inherent willingness of a consuming population to innovate. Many technological firms have been exploiting the consumer markets with their technology based discontinuous innovations. Several companies have been marketing small computers that, in pricing and programming structure, are amenable to adoption by individual consumers. This study is an attempt to study the diffusion/adoption process of personal computers in the Indian context from both a behavioral theory and marketing strategy perspective.
The author suggests that a combination of System Dynamics (SD) thinking combined with Monte Carlo simulation models can yield new insight and be a useful tool. Systems with feedback loops often contain elements of uncertainty or randomness which can be modeled by Monte Carlo methods. On the other hand, feedback loop analysis could certainly benefit Mont Carlo simulation models. Studying single runs of SD models may yield considerable insight. But when a parameter is set to a constant or average value, variance is lost. Variance plays an important role in portraying any risk involved in a system.These points will be illustrated by an example from an analysis performed at NDRE where SD thinking applied to a Monte Carlo model was the key to solving an important question. The example concerns dimensioning Airfield Damage Repair (ADR) capacity on Norwegian airbases subject to hostile attacks. One key question was: How long time must the runway be open per day in order to obtain acceptable operating conditions for air defense fighter aircraft? Does there exist some minimum threshold?The main feedback loops concern damage on the runway and attribution between attacking aircraft, ground based air defense and defending air defense aircraft (depending on open runways). The elements of randomness concern the damage inflicted on the runway, and the repair time.It is shown that under certain conditions (too low repair capacity) there is a risk of defending aircraft either being pinned in or wining the battle. The feedback loop between defending aircraft and the runway state plays a key role along with the randomness in the early damage. The statistical distribution of the fraction of day open may over time develop into having one peak close to 0 (closed), one peak close to 1 (open), and little in between. The average value is merely a weighted average between two extremes.On the other hand, with sufficient repair capacity, the risk of being pinned in was eliminated. The effects were easily understood when thinking in terms of feedback loops, but the element of randomness was essential in order to recognize the threshold when the risk of being pinned in occurred.The author believes that a similar combination of techniques could benefit traditional SD models, too.
This paper describes the application of the system dynamics method to the study of a conceptual military Command, Control, Communications and Information System (CIS) in the early phases of procurement. The work from which this paper was drawn constitutes one half of two parallel study streams to investigate the usefulness of the system dynamics technique in this area (the work did not attempt to assess the CIS itself). The conclusions from both streams are discussed in a separate paper (Gavine, 1990).
This paper describes the development of a System Dynamics model of cocaine use in the United States of America. The model’s evolution is presented chronologically as a story in which theory and data have interacted and changed over time. This story may be particularly instructive for those System Dynamics modelers working, under conditions of some change and uncertainty, on extended studies of social behavior. An approach which combines skepticism, flexibility and attention to detail throughout such studies is advocated. When a variety of alternative theories and hypotheses is available, as in many social science applications, it is important to gather a wide spectrum of relevant evidence in order to reduce the risk of model misspecification and improve the study’s effectiveness.
This paper is based on the results of experience working with a small firm, which experienced loss of key customers due to quality problems. One another large customer threatened to take their business somewhere else. These customers had been doing business with the firm for at least 10 years. It is at this point in time, i.e., Summer of 1986, the author was brought in to help the management develop a quality assurance program. After initial discussion, it became clear that the clamor for quality as found in popular and professional media did not permeate the management thinking. The expectation was to have someone install SPC charts and initiate Quality Circle Activities. Ultimately, the responsibility for maintenance of these black boxes would be assigned to their Quality Supervisor. It was clear that if the plant manager and the production supervisor did not assume the responsibility by making serious efforts to develop the quality perspective and did not involve in the learning process, the probability of successful implementation would be close to zero. The paper discusses how system dynamics symbols were used to map the mental models and to provide focus for generating dialogue. There was never any need to build a full scale model.
The problem of labor employment is a major problem of global issues. It is also an especially pronounced problem in a country such as ours, with tremendous population and relatively poor background of economy. Under the leadership of the Central Committee and the State Council, and with the coordinated effort of all the localities, departments in society, we have achieved in the area of labor employment a tremendous success that has captured the attention of the entire world. However, owing to some reasons of irrational policies, we have also got the experience of failure in it.The problem of employment is becoming more and more urgent and serious with the policy of deepening reformation. Showing by the experience and theory, any effort that merely aims at resolving the employment problem can be effective only in a short-term and have less success when it faces new situation.To resolve the employment problem at present, we must begin with our employment philosophy and set up a system of strategic management in terms of employment that keeps on defending and promoting the stability and unity of society. The tremendous population of China is both a huge obstacle and a great motive force for the development of our society. We are facing selection-- challenge and opportunity-- that only depends on our effort and creation.
In this paper, we will sum up the situation, the achievements and successes of System Dynamics in France, but we will also analyze some of the practical difficulties to which it is confronted.This expose will include three parts: -the teaching of S.D.,-its practical applications, particularly within industry,- an example of a successful application, illustrating some the practical difficulties in using our S.D. models.
Total Quality (TQ) has received a great deal of attention in the business world in recent years. American companies, slow to enhance it at first, are joining in the TQ movement as they become convinced of its ability to enhance competitiveness. TQ is based on a philosophy and set of tools that focus on continuous improvement, and the fuel that drives the quality improvement engine is measurable data. TQ can be viewed as an effective means for advancing organizational learning whose current bag of tools are especially well-equipped to advance learning at the operational level. These TQ tools, however, are not as effective in dealing with problems that are ill-defined, where variables are fuzzy and hard to quantify or measure, where time delays are long, and where the system is loosely coupled but highly inter-related. These types of issues are precisely the ones for which system dynamics is well suited-- issues of a dynamically complex nature where feedback loops drive the behavior of interest. Complementing the TQ approach, system dynamics focuses on advancing organizational learning at the conceptual level. Organizational learning, however, requires learning at both the conceptual and operational level. This paper briefly lays out the background of both fields, compares their common holistic approach, and provides examples of possible integration of the two approaches to enhance organizational learning.
Today’s investment decisions in the production industry require - as this industry becomes more and more integrated by information systems - a careful long-range planning. Investment projects have to be seen within the network of their environment, and their interdependent impacts can be assessed in a systematic investigation, as part of a Technology Strategy. Furthermore a Systems approach helps to clarify the complex process of Technology Innovations.
In the Netherlands, ammonia emissions from agriculture contribute significantly to the acidification of soil and water. A 50-70 % reduction of these emissions within the next ten years is one of the great challenges for agricultural practice. This paper presents an outline of a combined system dynamics-optimization model of this problem, which will be used to study the effect of three different abatement scenarios.A concise analysis of the acidification problem is given. The main causes of the current environmental problems of the agricultural system are described.Next the choice of modeling techniques is discussed. System dynamics was applied because of the many (non-linear) interactions and delayed feedback relations in the agricultural system. The flexible responses to policy measures shown by the system’s actors in the past, urged including economic optimization procedures in the model.Some remarks are made on technical problems, using Professional DYNAMO linked with a FORTRAN optimization module.The model contains an integrated description of the ecological problem in its economic context, with links to the related policy field of eutrophication. Interaction with reference groups consisting of experts and governmental officials, and interviews with representatives of interest groups have greatly contributed to the development of the model.Only tentative conclusions can be presented at this stage, as results are still being worked on. However, a better understanding of the acidification problem had been reached, by the reference groups and the researchers. An interesting aspect is the link between emission reduction policy scenarios and possible shifts in land-related agricultural activities.
In order to examine different strategies in the search for more resistant bacterial cultures, we have simulated a variety of growth, mutation, competition and selection processes that may arise in interacting populations of bacteria and phages. Our model considers a culture containing several variants of the same bacterium, each sensitive to attacks from a specific phage. The culture is growing in a chemostat with a continuous supply of nutrients. Surplus bacteria and vira are removed through dilution. Depending on the rate of dilution, the model exhibits a stable equilibrium, self-sustained oscillations, quasi-periodic behavior, deterministic chaos, or extinction of certain species. The model can also be used to describe evolutionary changes in the composition of the microbiological system.
In the near future the organization of home care in the Netherlands will be reorganized. In order to show some of the dynamic consequences of these changes, a preliminary model was developed. In this paper we will discuss the use of the preliminary model to elicit the ideas from policy makers about future changes in the organization of home care. This is done by conducting a Delphi study to keep the time investment of the policy makers as limited as possible.
Corporate planning process uses tools that are inadequate for present day environment of complexity and rapid change. Managements must supplement their intuition and experience with planning using corporate planning models. The key to assist managements to plan effectively lies in better and greater use of computerized corporate planning models. System Dynamics is one of the latest modeling innovations that provide a flexible framework in which to view the interdependent operations of a system in a coherent and orderly manner. With this in view, a modular approach using System Dynamics principles has been adopted to model an integrated steel plant. The model so developed has been applied to conduct simulation experiments in the area of corporate planning. For the purpose of modular construction the corporate model has been considered to be constituted of three modules of marketing production and finance. The production system has been taken for detailed investigation in this model. The physical flow of men, materials and machines in various capacity centers of the steel plant have been separately modeled and then integrated. The financial consequences of these flows have also been considered to simulate indicators of corporate performance such as profit and return on investment. The model has been applied to study the behavior of a large number of variables of interest in response to controllable as well as uncontrollable variables. The model has also been used to conduct “what if” type simulation experiments. It also has been used to identify debottlenecking priorities and evaluate modernization, expansion and debottlenecking projects.
This study introduces the concept of linking together the Urban Transportation Planning (UTP) and urban Dynamic (UD) models by means of some key indices, such as transportation accessibility, population and economic development (i.e. Gross Provincial Project, GPP). It is found that, by repeating the procedure several times, a certain level of socio-economic development can be achieved which will reflect future transportation conditions in the city. In addition, this study also found some new MOE’s (Measures of Effectiveness) concerned with socio-economic development which can be used to measure and evaluate the effectiveness of transportation investment policies on urban growth.
There is growing application of simulation to practical training in management of business on strategic and operational level. In use are simple models where a business is immersed in a much bigger market which sets the context, and others where the context is set dynamically by the actions of the competitors (3), (4).The simulation exercises reported are centered on the question of how to appreciate the impact of a reactive context in managing a business (1). The Implementation of Simulation with continuous simulation (Dynamo, etc.) gives easy appreciation of the impact of operational dynamics in a reactive strategic context.
Changing and improving manufacturing operations in such a way that optimum flexibility is achieved is a standard task nowadays.Enhanced by the availability of CIM concepts and techniques the pervading paradigm how to solve the problem tends to be based on the structure of the data processing systems.Since management of data systems and inventory are often handled as different functional entities the complex relations of the effects of goods flows and data flows that make up the dynamic behavior of the operations as a whole often evade appropriate treatment.CIM related practice, doing the easy things first, is to follow a hands-on bottom-up approach in optimizing first individual process steps using preferably discrete simulations and then trying to add those optimized islands to a system.If we follow the original ideas of J. Forrester and his group a quite different approach is proposed. In a combination of top-down analysis and bottom-up implementation we would first apply S.D.A. with continuous simulation to understand the operations in their context as is. After optimization we would implement the upgraded system bottom-up.The approach used two levels of imaging the real system to a model. Top level simulation with a continuous model is used to analyze and define dynamic behavior, feed back loops and embedding of operations in the context of sales and supply.Bottom level simulation thereafter serves to check detailed implementation of single tasks within the dynamic specifications arrived at by the continuous overlay model.The procedure allows to exploit the strong points of both continuous and discrete simulation, namely analysis of the dynamic behavior of complex and intertwined systems of flows of goods and data on the one hand and detailed analysis of process steps involving clearly defined operations with work pieces handled.A few examples serve as illustration how this first step of a top-down optimizing with the aid of S.D.A. worked in defining manufacturing systems as a whole before starting bottom-up implementation.As the S.D.A. model is a lumped together model of the real system, its use for on-line prognosis can be a welcome byproduct.
This article expounds the necessity of improving reliability of the S.D. model and based on the concepts of “Big System”, “Strictness” and “Parameter Accuracy” when developing a model puts forward some tentative methods to improve reliability of the S.D. model.
This paper introduces an effective Model, which is the combination of the methods of S.D. – I/O/O (input-occupancy – output) in studying the improvement of regional industrial structure and the problems in economic development.
The reference approach is a new system dynamics support method. This paper explores the possibility of using this method to design strategies that transform the production function into a competitive weapon. First, the requirements of a manufacturing strategy design tool are identified. Next, the manufacturing strategy of a case study is designed using the reference approach. Based on this application, the possibility of using the reference approach as a tool for the design of the manufacturing strategy is discussed. The analysis concludes that the reference approach is a valuable tool for the computer aided design of a manufacturing strategy.
The progress experimented by the Systems Approach and by its instruments is in our judgments well known and undeniable. Nevertheless, the economic analysis seems to remain immune to such advances and is maintained, for the most part, within an analytical-reductionist framework quite far from reality. In this work, we intend to use the Systems Approach and, within it, the methodology offered by the stage of conceptualization of System Dynamics modeling in order to relate the different objectives of the Economic Policy in Spain, as well as to relate those objectives with the Monetary Policy, whose goals should always be subordinated to the former. By this example, we will try to show the weaknesses and deficiencies which appear with the conventional approach traditionally used in the study of the Economy.
The paper reports the findings of an ongoing project on manpower modeling for a government research organization. The flow of scientists from one grade to an other has been modeled considering recruitment, promotion and retirement policies. Age distributions of scientists have been incorporated in the formulations and it has helped in retirement calculations from various grades. Future scenarios with alternative policies are generated and discussed.
The SYSTEMS Thinking and Curriculum Innovation Network (STACI n) Project is a multi-year implementation and research effort intended to examine the impact of implementing and learning from a systems thinking approach to instruction and from using simulation modeling software. Systems thinking is an analytic problem solving tool that can be integrated into courses to enhance instruction. The purpose of the project is to test the potentials and effects of using the technology-based approach in precollege curricula to teach problem solving skills as well as content-specific knowledge .
One approach to strategic planning is called “gap analysis”. In gap analysis, the future of an organization under its present strategy is forecasted. Then, objectives, or the desired future for that organization, is identified and the gap between the objectives and the future conditions under current strategy is determined. Finally, new strategies which will help to close the gap will be designed. System Dynamics can be used two important ways in the gap analysis. First, System Dynamics model can be used to forecast the future of an organization under current strategies and identify the gap between that future and the objectives. Second, System Dynamics model can be used to examine how much each strategy can be helpful to close the gap. The application of System Dynamics in gap analysis method is shown by an example of developing a strategy for water resource development in Iran.
The analysis unit of the New York State Division for Youth is responsible for providing admission forecasts to allow the Division to anticipate changes in demands for facility space. Arrests of the most serious offenders had shown a 38% growth between 1987 and 1988, yet the annual admission rate declined 19%. In an effort to understand the reasons and account for this difference, a Stella model of the offender processing system was created and simulated using historical exogenous time serious inputs. Utilizing linear processing ratios and simple causal assumptions, the model reproduced the historical admission rates without any changes in processing trends. The results indicate that the admission rate was proportional to the arrest rate, given the long lag time involved in the conviction process. Further, the growth in cases backlogged due to an increase in processing time during 1987 did not imply that a small increase in processing resources would cause a surge of admissions.
Empirical analyses indicate that the firm which is the first in bringing new products to the market has a major competitive advantage. The development time for sophisticated and high quality products is shortening. The time span of the market cycle is decreasing, and for high technology firms, even rather short delays can cause a deep cut in the overall profit performance. In the “Factory of the Future” the capability for immediate and reliable delivery of custom designed products is a crucial aspect.Speed is becoming a decisive factor for corporate management. In Management Science, however, this development is not yet taken into account adequately. Different stages of the same process are still analyzed separately. Models of research and development e.g., do not investigate how delays influence the market performance of the eventually achieved product. Studies of innovation diffusion focus solely on the market cycle, thereby neglecting the lengthy and costly R&D processes. With such a limited perspective, those models must fail to support effectively decision making in a dynamic high technology environment.The paper discusses System Dynamics’ role in such a setting. It presents a model for innovation management which integrates the stages of R&D with the production and marketing cycle. It is designed as a microworld for learning about the system and for studying possible ways of influencing its behavior. The model consists of two modules: a C-written algorithm, based on biological evolution theory, maps the firm’s research and development processes; the second module is a Dynamo-representation of innovation policies and market dynamics. Both modules are tightly coupled through flows of information. Their interactions allow the testing of corporate strategies for R&D planning and innovation management.Although still in the development stage, the model provides insights into the timing of decisions. The results from this integrative view underline the importance of speed in the strive for competitive advantage.
A group of senior managers and planners from a major oil company met to discuss the changing structure of the oil industry stemming from the moves of traditional producers into refining and retailing. This broad ranging discussion led to a system dynamics simulation model of the oil producers. The model produced new insights into the power and stability of OPEC (the major oil producers’ organization), the dynamics of oil prices, and the investment opportunities of non-OPEC producers.The paper traces the model development process, starting from group discussions, to flip chart drawings, to STELLA maps and finally to working simulations models. Particular attention is paid to the methods used to capture team knowledge and to ensure that the STELLA models reflected opinions and ideas from the meetings. The paper describes how diagrams of behavioral decision functions were used to collect ideas about the ‘logic’ of the principal producers’ production decisions. The diagrams served as a record of the meetings and the basis for first-cut STELLA maps. A selection of diagrams is used to illustrate the content of the model.A sub-group of the project team was involved in developing and testing an algebraic model. The paper shows partial model simulations similar to those used by the sub-group to build confidence and a sense of ‘ownership’ in the algebraic formulations. Further simulations show how the full model can simulate thinking about producers’ behavior and oil prices.
The theory of decisions under uncertainty share basic assumptions with system dynamics. Both methods require that decisions are based on only available information, and both methods focus on the development of policy rules that improve system performance. Both methods have other implications for parameter estimation than conventional deterministic analysis. Fluctuations are frequently studied in system dynamics, and fluctuations and randomness are of great importance for decisions under uncertainty. Decisions under uncertainty can be studied by analytical methods, dynamic programming and Monte Carlo simulations. The latter method is quite easily applied to system dynamics models. Using Monte Carlo simulations we show that uncertainty has important implications for decisions influencing the “greenhouse” effect. Note that risk aversion is not an issue in this example. The theory of decisions under uncertainty brings new qualitative insights to system dynamics, and facilitates quantitative improvements of policy rules. Referring to or applying the theory of decisions under uncertainty might help to get a wider academic acceptance of system dynamics models, which are often thought of as being realistic but quite uncertain. The principles of system dynamics might bring the field of decisions under uncertainty in the direction of greater realism. The focus on real life interpretation of system dynamics models is most useful for the application of apriori information. Apriori information is needed to establish important autocorrelation in cases where short time-series do not contain sufficient information.
The business-production managements of shipbuilding- PPBP, namely with one shipyard, in today’s too complex business conditions, is one of the most complex management organization systems. For this organization system, the intuitive collective management is not efficient enough especially today. For the management of such complex systems it is necessary today to apply the most contemporary method of management with obligatory computer support. In this paper, the authors are going to present the results achieved in researching the efficiency of System Dynamics Computer Modeling of the Business-Production Shipbuilding Process-PPBP, which they did in 1988 and are continuing in the “BRODOGRADEVNA INDUSTRIJA SPLIT, YUGOSLAVIA, one of the biggest shipyards in Yugoslavia.
The issue of global warming has sparked debate among scientists and policy makers over the last two years. Many studies have been undertaken in the U.S. and other nations to determine the potential severity of global climate change and appropriate policy responses.The U.S. Department of Energy is now conducting one such study of energy technology and policy options to mitigate greenhouse gas emissions. The study is an attempt to assess the emissions reductions potential and costs of several policies, using the FOSSIL2 integrated energy model. This paper focuses on preliminary results of a subset of eight policy cases. It discusses the modeling methodology, the formulation of these policies, draft results and some policy insights gained.
Negotiating group can use generic computer tools to aid decision-making and problem solving activities in negotiation management. In attempting to create, apply, and evaluate such computer tools, the authors have had to address the issue of user acceptance. This paper reviews the basic framework of negotiation management and locates the issue of user acceptance within that framework. Focusing on system dynamic simulation models as tools for negotiators, the paper analyzes the reactions of potential and prospective users.
In this study, a decision support system for system dynamics modeling is designed. The intelligent part of the system is composed of a knowledge base, a data base and an inference engine. The function part of the system is composed of some modules for model construction, model generation, model simulation, model interpretation, model management, and PD interface. The proposed system is a production system written in PROLOG, and it can join up with the professional Dynamo plus software by means of the PD interface. Whole process from modeling to simulation can be realized by the support of the system. An application example is given in this paper.
The paper presents some results of research regarding the relationship between the centralization degree and the efficiency of economic systems. A simple system dynamics model has been used in these studies. The model has applied certain J.Kornai’s ideas concerning economic systems. Simulation experiments have confirmed the viewpoint that overall economic behavior arises from within feedback loops creating microstructure of each system. Two basic kinds of microstructure have been distinguished: centralized and decentralized. Macro behavior generated by them is close to these observed in planned and market economies. The paper is divided into four parts. In the first one, basic Kornai’s ideas are outlined. In the second part, model is presented, whereas in the third one, some results of simulation are analyzed. Conclusions drawn from the experiments are presented in the fourth part.
Behavioral simulation models of OPEC have typically been built on the assumption that OPEC price changes are determined by capacity utilization. We evaluate this model by examining its empirical and behavioral justifications, and by observing how it performs in a simple world oil market model. We also briefly explore and evaluate alternative behavioral rules for OPEC.
Building large dynamic simulation model of an industry requires sound organizing principles and appropriate tools combined with a thorough understanding of the industry being modeled. In this paper I will describe how we build a simulation model for a client’s business to answer the client’s key strategic questions.The models are large because they are based on physical, observable phenomena in the industry. They must take into account the stocks and flows of product and money as well as represent managers’ decision-making processes and the key variables that impact each producer’s decisions. Most corporate decisions are based on physical or financial parameters, so the model structure is clearly understandable to the final user.At Federal Group we use an effective methodology for building large-scale structural dynamic simulation models to address the real world problems of business decision makers. This paper presents how we have successfully constructed such models for oligopolistic, capital-intensive industries. However, our methodology can be generalized to a broad range of other business environments.
PASION is a process- and event-oriented simulation language designed for those who already know and use PASCAL. The language has a two level (process/event) structure and permits the use of all the Pascal Structures. It also offers the main features of object-oriented programming. PASION provides necessary facilities to handle sequences of random events, queues and quasi-parallel processes, both discrete and continuous. A PASION source program consists of a sequence of process declarations and a main segment which initializes the simulation. At run time the program generates objects which represent model processes due to the process declarations. PASION provides tools which facilitate the building of complex models by the mechanism of inheritance.
In previous papers, various approaches to studying the relationships between an aggregate dynamic model and an underlying, stochastic system have been reported. These approaches include the use of a Master Equation model to derive the aggregate model from stochastic hypotheses, and the summation over a population of dynamic sub-models to estimate the aggregate behavior. In this paper, a commodity cycle model is re-formulated as a stochastic, discrete simulation model to study the effects of stochasticity on the aggregate behavior of the system. Global variables provide aggregate information links to control the arrival and departure of new entities (commodity units and capacity units). A comparison of the aggregate dynamics of the stochastic and the equivalent system dynamics models is made under conditions in which the dynamic models is made under conditions in which the dynamic model is oscillatory and undergoing period-doubling bifurcations leading to chaos.
Successful welfare reform is difficult to achieve in practice and to study in theory because the linkages between policy reforms and the actions of clients of the system are many, long, and loose. Reformers can change organizational structure, funding amounts and requirements, as well as mandates. They hope that these reforms will change the behavior of workers who will implement the reforms. In turn, changed behavior of employees and welfare agencies are presumed to change the behavior of clients. Evaluating welfare reforms requires that information about policy changes, organizational changes, changed behavior by workers, and ultimately changed client behavior all be examined empirically and the results combined into a coherent whole.This paper proposes that system dynamics models may be a new tool in the analyst’s toolchest that can help to create integrated theories of welfare reform as well as help to integrate results from empirical studies of welfare reform. Below we present a first cut system dynamics model of the implementation of portions of the welfare reform legislation of 1988. This effort is designed to illustrate how system changes, changes in worker behavior, and client behavioral choices might be simultaneously analyzed within the context of a singe feedback system. Of course, the hard work of elaborating and empirically validating the structure of this simple model still remains before us.
The problems we are facing at all levels in the world today are growing more intractable. In particular, our problems are becoming increasingly resistant to unilateral solutions. I will argue that this growing resistance and intractability result from the fact that while the evolving web of interdependencies, of which we all are part, is rapidly tightening, the development of our capacity for thinking in terms of dynamic interdependency has not kept pace. As the gap between the nature of our problems, and our ability to grok this nature grows, the planet will face increasing peril on a multitude of fronts. System Dynamics and System Thinking -- the larger framework of which it is a subset -- are an important part of an effective strategy for closing the gap between challenge and capacity for addressing challenge. Unfortunately, we as System Dynamacists and Systems Thinkers have been woefully inadequate in transferring our framework, skills and technology to the population at large. Although we have “seen the light” for some thirty years now, we have not opened the door to our inner sanctum wide enough to let others share in our insight- generation capabilities with respect to the inner workings of closed-loop systems. In order to be more effective in transferring our very valuable capabilities to a broader swath of humanity, we need to see more clearly precisely what these capabilities really are, and also to understand the forces driving the evolution of the education system into which these capabilities -- if they are to be transferred on a board scale -- must be assimilated. My purpose in writing this paper is to shed some (hopefully new) light on both what it is we have to bestow, and also on where the educational system that is to receive our bounty is headed. My intended audience therefore is both Systems Thinkers and educators. My highest hope for the paper is that it will serve to further eradicate the distinction between the two.
The paper considers how students learn commodity production and circulation via gaming experiments. We review two of them.In the first, players run into reproduction on a decreasing scale aggravated if not caused by their non-cooperative behavior. In this economy social and private benefits and costs diverge. Undertaking an investment a capitalist firm chooses typically that technique which maximizes profitability, while the society is interested in that which requires the minimum input of labor.In the second, players bring up extended reproduction receiving incompatible norms and setting new priorities with associated strategies of cooperative behavior. Social and individual interests draw together consequently.
This paper suggests that the possibility to experiment with relationships using system dynamics should lend the method easily to introducing practicum in the theory-based disciplines. This would however, require modifying teaching formats and creating new text materials and user-friendly computer programs suitable for use by students with little computer or mathematical expertise. A simulation laboratory consisting of a text and a user-friendly simulation program developed recently by the author on issues of economic development is presented as an example of material needed for integrating practicum with teaching.
This paper presents results of extended experimentation with selected models of social phenomena widely used by the system dynamicists in their studies on deterministic chaos. The models selected include various versions of a simple model of migratory dynamics and a model of resource allocation in a firm, and a simple model of long-term economic fluctuations. Chaotic modes seem to appear in each of the experimented model, either due to non-robust or unrealistic rate formulation, or from unrealistic parameter or input specifications or both. Minor changes on the models experimented with, which improve their correspondence to reality, eliminate chaotic modes. The paper raises the issue of the relevance of the chaotic models to real-world phenomena and policy design for system improvement.
The use of computer tools to aid in decision-making and problem-solving activities suggests a view of negotiation in which parties collaborate to improve the quality of the information and knowledge on which they base their joint decisions. In this view, negotiation is characterized as a process of discovery and design. The effectiveness of negotiation is defined in three dimensions: legitimacy, feasibility, and efficiency. Computer tools are discussed in the context of information strategies, or ways in which negotiators use information in their efforts to ‘discover and design’ solutions.
The close similarity between the Indian census, Government of India and U.N. population estimates and those from the Constrained Coalition and Logistic Model (CCLM) has been demonstrated which enhances the usage of differential equation modeling for studies on population growth processes. The CCLM incorporates the legitimate requirement of an upper bound for the aggregate population thereby implying the rate of natural increase to reach the zero level. The numerical value assumed for the upper bound is based on food supply - arable land availability, and accounts for advances in agriculture productivity. However, other factors such as quality of life, environmental degradation, per capita income, etc. can also be used to arrive at an upper bound. The model holds good promise for usage for other developing countries.
The automobile fuel market in Italy is appreciably different from that in other European countries and even more unlike the American context.As a matter of fact, the alternative and available automobile fuels in this country are the following: -gasoline (petrol),-gas oil (diesel oil),-liquefied gas (LPG), plus a very small amount of natural gas, each with its own price. In addition, price differences are considerably greater than in other countries.In view of the fact that gasoline is the most expensive fuel and gas oil the least expensive, the Italian Government has adopted a peculiar tax called “Superbollo” meant to penalize car owners with diesel powered engines and those with both gasoline and LPG powered engines, but to a different degree.The alternatives access by drivers (car-users) to different fuel resources has influenced and countries to influence the automobile industry’s approach to the Italian market.On the other hand, the different fuel prices, plus the varying annual amount of the ‘Superbollo” tax, influences the motorist’s decision in buying and using differently powered cars.The decision is obviously affected by the consumption rate for each type of fuel and the driver’s expected mileage per year.This paper aims to underline and analyze the hypothesis on the mix of the three main fuels used in Italy, trying to give results principally on the basis of: -price-changing of each fuel, -tax-value of “Supperbollo”, -different driver-mileage taking into account the pollution-cost of each of the three fuel solutions. The system, which is the subject of the study, will be analyzed using System Dynamics methodology, with a dynamic model.
Eroding competitiveness, declining productivity growth, explosive technological, political and environmental change, and dissolution of market and national boundaries form the familiar litany of problems which threaten traditional organizational structures and management practices. In the turbulence at the close of the century it is widely argued that organizations must change more rapidly than ever before.
The paper suggests a novel approach to policy design in system dynamics models. The approach is based on optimal control theory to evolve synthetic policy structures and then design realistic policies for the famous production - distribution model of Forrester. New policy sets have been presented for purchase decision rate at retail and distributor sectors and manufacturing decision rate at factory. It is shown that the suggested policy sets show a marked improvement of model behavior over that obtained by Forrester. The approach suggested here will enhance the art of policy design.
Japanese old age population is gradually increasing and this tendency weakens economic conditions of Japanese welfare annuity system. Therefore it is important for us to study future conditions of this system.This model contains 4 sectors: Demography, total premium income, total pension expenditure and reserve of the welfare annuity system.The demographic sector covers populations of 5 three-year age groups under 14 years of age and 13 five-year age groups above 15 years of age. This sector was first formulated for a simulation model of dental diseases and is now applied to this model. Total premium income for the welfare annuity system is the sum of premiums of workers, employer contribution and government contribution, for which populations of five-year age groups are used. Total pension expenditure is the sum of base pensions and earning related pensions. Here is used population of 60-64 age group. Total premiums plus interest income of the reserves of the welfare annuity system minus total pension expenditures flow into the reserves of the welfare annuity system.The length of the simulation is 63 years from 1963 to 2025.This study is a research project of the Japan Productivity Center.
Advances in computer software allow modelers to design, with relative ease, sophisticated, realistic educational tools. With these advances, new issues arise about how to make this educational software productive and stimulating, without limiting the freedom of the user or creating simply a computerized workbook.Such simulation games have great educational potential for people who play video and home computer games, and sometimes for students in classrooms. The games must address three information levels: (1) real-world details, (2) simulation of model, and (3) conceptual understanding of structure and dynamics. The systems viewpoint on the particular model must be clearly explained; otherwise users will have much fun but learn little. Feedback during the game teaches this system understanding without requiring textbook readings. Such feedback requires new modes of “expert” computer analysis which need to be developed. Other tools need to be developed to help in creation of simulation games and to give the games abilities that they do not yet have, such as access to database of models, pictures, and text, and connections between simulation games.