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- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 227da936724c4223c5a64764d3922694, ca4810593b2703dcaa087957ab13af91, and 23d738ba88f8333bc39725f9cb5bd0b8
- Description:
- The domain of strategic decision making involves very complex issues with action-reaction relationships. In reality, there are system dynamics -based stimulation tools that help business managers understand t he fundamental processes of their businesses. In this research paper, we have studied the strategic market in the passenger airline industry for an international city pair between Perth and Singapore. Based on the study of major players on this route sector, we have attempted to model all the significant market elements and forces that demonstrate their explicit and implicit behaviours. The model developed in "iThink", a system dynamics-based stimulation software, provides an interactive capability to the business manager for the exploration of alternative scenarios so that the decision maker can understand how the pricing or competitive positioning activities of other players affect the market leader and vice-versa.
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- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 227da936724c4223c5a64764d3922694, ca4810593b2703dcaa087957ab13af91, and 23d738ba88f8333bc39725f9cb5bd0b8
- Description:
- The spread of an innovation in the market is a highly dynamics process. Management science has developed a plenty of descriptive or normative methods, models and instruments to model this process. The research reaches back to 2960 with the models developed by Fourt/Woodlock, Mansfield and Bass (Fourt/Woodlock 1960; Mansfield 1961; Bass 1969). These models regard the diffusion of an innovation over time as a quasi natural process--like the spread a disease--neglecting variables that allow to control the speed of innovation diffusion through corporate decisions. However, these fundamental models have been the basis for a variety of developments in this particular field. However, only a few of them consider the variety of influencing elements of the innovation diffusion (for an overview on the different models see e.g., Manhajan/Peterson 1985; Mahajan/Muller/Bass 1990:Maier 1995a) They concentrate on one or a combination of some of the decision variables, e.g., some models have been developed to seek for the optimum pricing or advertising strategies. Some models are simple in structure, regarding only monopolistic markets and neglecting important management decision variables. Some models are little more complex, considering oligopolistic or dynamic market structures. However, management decision variables are mostly exogenous inputs into the model, no feedback between management decisions and the spread of a new product in the market, and the success of a product exists.
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- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- Companies are complex and dynamic systems that have to be managed: information about the actual state of the systems has to be analyzed, decisions have to be drawn and then transformed into actions. However, due to the complexity and the dynamics of the systems, company, management is a very difficult venture. Therefore, tools, theories and methods are needed to make management easier and more effective. In our system dynamics community of researchers, lectures and practitioners it is a fundamental and clear paradigm that system dynamics bases modeling and simulation can enhance the understanding of complex systems and because of that it can improve decision making.
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- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- This Graduate Level Course for k-12 Teachers will introduce them to the General Systems Theory method of Thinking. This thought process is different from the analytical Mechanistic Method of Thinking from the Renaissance Period which produced the Industrial Revolution. The use of General Systems Theory, System Thinking and System Dynamics is aimed at bringing cohesion, meaning and interdependence to the k-12 curriculum. This process can introduce thinking, curiosity, creativity, and real world meaningful learning experiences in the classroom. The k-12 education establishment in the U.S. which is criticized for not preparing the students properly for college and the workplace could make a giant step forward by using System Thinking across the curriculum in the classroom. This is an introductory course in System Thinking and the Philosophy of the Systems View of Reality. The history of the thought process of Systems thinking and its application in the past, the present and the future is explored. Comparison with the Mechanistic View of Reality is presented. In depth studies of open, closed and feedback systems are developed and applied to social science, ecology, economics, biology, health care, physics, chemistry, mathematics, literature, government, business and etc.. Some of the graphical and software tool which have been developed for the study of systems will be uses. About 50% of the course will involve working on the application of system thinking and the computer simulation of systems. A new text was written for this course. The following twelve overheads summarizes the material and structure of this course. The text will be in draft form by the middle of 1996.
-
- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 227da936724c4223c5a64764d3922694, ca4810593b2703dcaa087957ab13af91, and 23d738ba88f8333bc39725f9cb5bd0b8
-
- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- As we stated in a previous study (see Machuca et al., 1993, p. 289), we have been criticizing, since 1988, the use of black-box simulators (BBBS) and defending the use of transparent-box-business simulators (TBBS), in which the structure (for example, in the form of a casual diagram), and even the main equations of the model on which it is based, are at all times accessible to the user, who will therefore find it easier to make decisions based on previous study of the possible causes of the different behaviour of the variables, and not only on observation of the latter, which are simply effects. Our approach was based on the hypothesis that in this way the learning process and acquisition of systems would be clearly improved (Machuca, 1992). Although other authors have subsequently touched on this topic, directly or indirectly, (Eberlein(1989), Issacs and Senge(1992, p. 195), Kemeny and Kreuter (1992, p. 305), Morecroft (1992, p. 465), Peterson ( 1992, p. 117), Sy-feng and Young (1992, p. 765)), the idea has scarcely been reflected in transferal in practice to game-design. In our view, one of the most valuable tools that System Dynamics offers to the development of systems thinking was being lost (Machuca, 1992p. 176)
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- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 227da936724c4223c5a64764d3922694, ca4810593b2703dcaa087957ab13af91, and 23d738ba88f8333bc39725f9cb5bd0b8
- Description:
- The target organization of a manufacturing system is the one that allows to make products whose managerial attributed (production delay, defective product rate, production cost and product variety) satisfy a target market. A fuzzy controller that generated the target organization of a manufacturing system is presented (Figure 1). This new type of controller, named organizational fuzzy controller (OFC), is an alternative tool to fuzzy expert systems. The OFC does not require membership functions, fuzzy logic and defuzzification procedures. In addition, the OFC can generate target organizations (controls) adapted to structural variation in the desired managerial attributes.
-
- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- The issue of discrete versus continuous formulation of system dynamics models has provided for lively, thought provoking discussion among modeling practitioners for more than thirty years. As early as 1961, Forrester argued that models based in the philosophy that real systems re continuous. Forrester used the example that of a contract signing, normally a discrete event, and explained how contracts can be viewed as continuous when one considers that contracts go through a process of negotiations. As the expectation associated with a contract signing increase the parties begin preparation so that the contract obligation can be fulfilled (1961; p.65). Thus, a contract signing represents a continuous process. The debate of discrete versus continuous has continued into the into the 1990's with Richardson (1991) maintained that the decision to model a problem discretely or continuously depends on the conceptual distance from which one views a problem. Richardson (1991) makes a strong argument for a continuous world perspective when he writes, Only from a more distant perspective in which events behavior is a consequence of feedback structure arise and be perceived to yield powerful insight (p. 346)
-
- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- A necessary part of any system dynamics analysis is the estimation of parameter values which best correspond to the real system. The method of estimating parameters for a typical system dynamic model usually involves two steps (with potentially multiple iterations in the second) 1. Make an a priori estimate based on direct observation, educated guesses by managers, or similar parameters in other settings (Graham (Graham [1980] refers to this as data {at or below the level of aggregation); and 2. Revise those estimates in the process of calibrating the model to aggregate data.
-
- Type:
- Document
- Date Created:
- 1996
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, ca4810593b2703dcaa087957ab13af91, and 227da936724c4223c5a64764d3922694
- Description:
- This paper aims a training tool which permitting different simulated situation would increase the degree of motivation and learning which could be achieved starting from a purely theoretical position. Most interactive modelling tools can be employed in gaming situations and provide a contribution to training by simulating the real world environment. Our model was developed from glass container Spanish market, and it is possible running different simulation to discover the best prices policies. Market interactions are so complex that they cannot be intuitively appreciated. We studied the market composition, the demand evolution, the demand evolution and the prices searching the market structure for the model. The simulated results for a company are: market share, quality, return, costs and best price, capacity, and inventory strategic policies.