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.