This paper describes the use of System Dynamics models to manage the very substantial risks associated with complex design, development and production projects. The authors present a systematic approach to controlling the risks associated with a project’s cost, schedule and technical performance.
Researchers for complex systems become more and more important in modern science. System dynamics has done its significant work for the integration of System Theory and Computer Science in this field. Each dynamic system forms a complex causality network. Now we can use the panweighted network in Pansystems Theory for the dynamic system modeling, and further perform the automatic reasoning on this model. This new ideal may be developed into a deep seated issue in AI. In this article, the method of both modeling and automatic reasoning on a panweighted network in dynamic systems will be introducted together with a simple and typical example in System dynamics. The further extention of this new method will be discussed in other articles.
“Commons-type” computer simulations are increasingly popular tools for helping students grasp the underlying trap of individual versus collective rational action in situations of joint ownership and finite resources. Historically, these simulations have been designed on mainframe or mini computers with site limited capacity for either visual or auditory feedback. This paper presents a preliminary commons-type game designed for use with the emerging local extended-area MacIntosh based networks. This paper also tests whether providing diagrammatic and verbal descriptions of the inherent resource and behavioral feedbacks enables players to avoid the fundamental commons trap: Short-term individually rational actions which result in collectively irrational consequences.
This paper focuses on the financial markets crash of October 1987 to examine the effects of trading strategies and other institutional structures on price behavior during this period. It presents a system dynamics model which looks at average, aggregate stock prices. It specifies connections among various trading sites and techniques. In particular, it examines the influence of financial and technological innovations such as stock-index futures and other derivative instruments and high speed order execution and transaction systems on market performance. A major conclusion is that the financial markets are characterized by complex structures only partially economic in nature. This suggests that the interplay between market pricing behavior and institutional behavioral reactions are more complex than is currently believed.
Central Europe faces a decade of restructuring due to the move from centrally planned economies to free markets. Its economic evolution into the current structure of resource utilization and output composition is traced by using a dynamic model. Major production factors and their interaction are simulated to quantify the issues of the transition: these include the transformation of traditional industries and their reorientation towards services, the parallel transfer of ownership of assets and financial intermediaries, restructuring the labor pool, demographic changes and energy efficiency.
Firstly, the network diagram of energy supply and demand system was drawn then a linear optimized model of integrated energy with economy, the target of which is the least cost of energy supply, was developed to optimized the best energy supply structure. Secondly, according to above results, an SD model was built up to predict and to study the developmental changes of the system from the long point of view. Finally, the two models combined was applied to a village with a population of 800 people in the North China Plain and results of computer simulation showed on the base year (1990), if energy transformed devices were invested properly, the cost of energy supply system will be lowest on the condition of meeting the energy demand, at the same time it can save energy, and the energy supply is sufficient. But, with the development of economy and the upgrading of people’s living level, the energy supply will become an important factor for rural economy development. Several alternative plans designed to simulate the system gave different influences of energy to economy.
This study attempts to examine the effectiveness of our proposed learning environment for systems thinking, and the effects of different kinds of task’s screen design for the interactive dynamic decision game to enhancing the learning effect. Two experiments were implemented for the two investigation purposes. In the first experiment, we found that the proposed learning environment was viable for learning resulting from the positive effects of challenging goal setting and causal feedback on the increase of participants’ motivation and understanding of the game. In the second experiment, the effects of causal feedback was examined directly by the comparisons of three different kinds of task’s screen design including causal, hierarchical, and department types. We found causal type of screen design induced more analytical cognitive type just as the prediction of the inducement principle (Hammond,1998) and outperformed the other two screen design as predicted by the correspondence-accuracy principle (Hammond,1998). But the effect of causal type on performance improvement was not significant. The insignificant effect of causal relations task’s screen design on performance improvement revealed that the learning of systems thinking relied mainly on “by doing” or “by failure”, not on “by knowing”. In conclusion, we suggested that the design of dynamic decision game aided systems thinking learning environment should take the motivation factor into account to lead participants make more efforts to learn systems thinking by doing through failures. Although causal relations type could not improve learning effect significantly, however, it induced corresponding causal analytical cognitive type that is beneficial to the learning of systems thinking.
This paper informs the scientific and religious communities about a breakthrough in the study of religion: System Dynamics is being used to model and simulate the experience of a mystic during the time when he traversed the dramatic road to mystical union. The paper briefly presents how his modelling task is being approached and some of the key insights being made by focusing on the dynamics of the important dark night of the soul phase which preceeds mystical union. This gives a synopsis of the essence of my book manuscript, A Meditation of Mystical Union.
Scholars have long attempted to understand the nature of scientific change. Is science characterized by the steady application of universally-accepted norms of logical inquiry, or is it an enterprise that periodically reconstructs itself from new fundamentals? One of the best-known examples of the latter view is Thomas S. Kuhn’s Structure of Scientific Revolutions. Kuhn argues that new theories replace old ones rather than build upon them, and in the process revolutionize science’s very image of itself (1962:84-85). Scientific progress is seen not as a steady accumulation of truths, but “as succession of tradition-bound periods punctuated by non-cumulative breaks” ( Kuhn 1970:208). Kuhn’s theory has had enormous influence in the social sciences, but it is also of enduring interest in the physical sciences (Barnes 1982; Lightman and Gingerich 1992). The notion of paradigm has, rightly or wrongly, been used to legitimate alternative methods of research as well as to delegitimate dominant modes of inquiry. Nonetheless, although ‘paradigm competition’ has become well-established in the academic lexicon, little is known about what such competition actually entails. How do internal and contextual forces interact to shape and constrain the development of new paradigms? Why do some paradigms last for centuries while others quickly wither?
Models and computer-based information systems frequently meet resistance and suspicion by management, because they often do not meet the knowledge demands of management in a company. Solving this problem requires approaching modelling and information systems development as a management discipline. This discipline involves the activities of developing, maintaining, effective using, and conserving of models and systems. The paper concludes with a normative view of the relation between management levels and model management activities, and considers the possible use of computer-based information systems for effective model management.