This work captures and analyzes the fundamental dynamics of innovative industries with a System Dynamics model. We selectively reviewed the innovation literature, identified the dynamics to be modelled, formulated a conceptual model of these dynamics, and then developed the initial simulation model. By design the conceptual model is simple and generic. It is intended to apply to a broad range of products and services assembled and process-based, complex and simple, physical and digital, business and consumer, early stage and mature, 19th century and 21st century. That is what we mean by the fundamental dynamics of innovative industries. In many variations and combinations they can explain the evolution of most markets. The initial simulation model was developed from the conceptual model. It represents products based on two generations of technology. At this stage the simulation model does not represent a specific market or industry. It is quantified with hypothetical inputs, parameters, and cause/effect relationships. The simulation model recreates well-documented reference modes of market evolution. We currently are building the information base which will enable the initial model to be applied to the photography and display markets.
The, for economists well-known Goodwin model was one of the first models which tried to combine cyclical behavior and economic growth. The basis for this is the predator-prey model a basic structure for every System Dynamicists. The economic literature about the Goodwin model is enormous, but so far, it was mostly concentrate on the mathematical behavior or on some extensions that could be implemented. In addition, there are only two papers from R. Solow and D. Harvie about an econometrical verification of the model and none from a System Dynamics perspective. This article provides therefore two System Dynamics models of Goodwins theory and tests the enhanced one on the German economic situation and on the data provide by Harvie 2000. Additionally there are some suggested modifications of the Goodwin model, tested from different authors, which reveal surprising outcomes for the understanding of Goodwins theory.
In this paper, I will present relatively simple system dynamics models which capture some of the insights of a key critic of the U.S. policy for defending the country, Stephen Flynn. Flynn is especially concerned with the over-reaction to the attacks of September 11, 2001. He warns of the dangers of shutting down legitimate commerce and investing in overseas offensive measures as a knee-jerk reaction to the attacks. It is not that he is advocating a lax approach to security. Rather he is advocating a measured look at the implications of a draconian defense policy which may cause much more damage to our societal infrastructures than the attacks that triggered it. He also presents recommended solutions.
In the modern era, the advances in information technology have been dramatically shaping the ways people live as well as the ways organizations manage their businesses in their professional business domains. Implementing various kinds of information systems, such as Decision Support Systems, has been recognized as one of the most crucial tasks for organizations in order to continue to be competitive or even to survive. Although considerable effort has been devoted to improving the performance of information system implementations, organizations are still constantly suffering from the failures of information system implementations. In this study an extensive framework that depicts the context of information system implementation is developed. A system dynamics approach is used to investigate the dynamic nature of information system implementations. By using the proposed system dynamics model, we contend, executives and information system professionals of organizations can gain comprehensive insights into organizational behaviors and substantial policy-making implications regarding information system implementations.
The pattern of one-shot growth is most seen in software industry. The purpose of this paper is to understand the growth dynamics of a software house and to facilitate the software house to manage its growth. This paper models a major domestic ERP software house in Taiwan that is experiencing the one-shot growth process. Business type-level packages and high quality service is the companys secrets for its success. With a good reputation for high quality systems and services, the companys growth strategy is to expand the market it serves by developing new kinds of packages for more business types. However, how to balance the human resources requirements of R&D and ERP is rather difficult when long delays exist everywhere in a software house. With the system dynamics model built, this paper identifies the archetype of limits to growth hidden inside the software house and illustrates how the problem is worsened by the companys intuitive reactions.
A discussion, with panelists representing different perspectives, facilitated to encourage full participation by everyone present. The field of inquiry dubbed environmental dynamics (ED) includes a broad range of interests, many with differing views of the ecological world. These include, for example, purely ecological studies involving the interactions of organisms and their natural environment, technical studies of the effects of human activities on the environment and different methods employed to limit or counteract those effects, big picture analysis of the human-influenced world and the direction it is headed, plus many others. Popular topics often associated with ED include: environmental regulation, the ecocosm dilemma, the oil crisis, global warming, environmental limits [to growth], etc. The roundtable will explore the relationships among these different topics, emphasizing the role of system dynamics. The goals will be to establish common ground, to create useful distinctions, and to help organize the ED endeavor.
In order to determine whether model testing is as useful as suggested by modeling experts, the full battery of model tests recommended by Forrester, Senge, Sterman, and others was applied retrospectively to a complex previously-published system dynamics model. The time required to carry out each type of test was captured, and the benefits that resulted from applying each test was determined subjectively. The resulting benefit to cost ratios are reported. These ratios suggest that rather than focusing primarily on sensitivity testing, modelers should consider other types of model tests such as extreme condition tests and family member tests. The study also finds that all of the different kinds of tests were either moderately useful or very useful--fully supporting the recommendations of the experts. An interesting diagram called a "tornado diagram" is used to portray the results of the sensitivity testing.
The tourism industry is considered a very important factor that contributes to the economic development Egypt. The industry has shown growth in the recent years in the number of tourist arrivals to reach a maximum of 6 million in 2003. It could not be denied that government efforts contributed to the growth but nevertheless the devaluation of the pound had a significant influence on the number of visitors. The performance of the industry might look fine in general. But, this is if compared to previous performance only. However, if an in-depth look is taken it is realized that the Egyptian tourism is performing far below capacity. This paper aims at explaining the way to improve the performance of the Egyptian tourism industry using a system dynamics methodology. This will be done by defining the main factors affecting the industry, then explaining how the whole system works and finally proposing a new modified model and required course of action.
The researchers attempt to visualize the complexity and dynamic behaviour of SME clusters in Egypt throughout the process of transferring a clusters state from static (idle) to dynamic (productive). This research constitutes the second of two complementary phases of a more comprehensive research that tries to quantify the qualitative measures of dynamic clusters through extending the application of the business dynamics tool to simulate the effect of different cluster-based economic development policy scenarios. After developing the mental model and during the conceptualization phase, the researchers highlighted the key-leverage causal loops showing feedback effects and uncovering the hidden cause effect relationships existing between the most important elements such as trust level inside the cluster, competition and the number of supporting industries. After validating the model, the researchers designed the policy analysis runs and undertook different scenario analysis over a time span of 50 years. Scenario analysis included studying the effect of elements such as institutions for collaboration (IFCs) on cooperation; effect of broker efficiency and success stories on trust building; and effect of trust on learning.