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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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 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 .
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 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 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.