Cancer is a problem that has long been wrought over by philosopher and biologist alike. It provides a tremendous insight into the diversity of complex phenomena, into the ontogeny of order, into the deepest deterministic principles of life itself. Here we try to sketch dynamically the emergence of such a metastatic and invasive process, tying together chemical, molecular, and physiological insights to more clearly define the problem. We follow the progression of small-cell lung cancer in a population of brachial lung cells tracing the molecular, cellular, and systems etiology of this complex disease.
Model analysis in system dynamics (SD) entails articulating exactly how the structure of circular, feedback relations among variables in a system determines its performance through time. This article combines disruptive innovation (DI) theory with SD to show the use and benefits of model analysis with the pathway participation metric (PPM), implemented in the Digest® software. The model replicates the hard-disk makers overshoot and collapse dynamics that DI allegedly caused. Multiple insights emerge from the dynamics the model computes. Model analysis shows that, over five distinct time phases, four different feedback loops become most prominent in generating the hard-disk makers population dynamics from 1973 to 1993. And Digest® helps detect exactly how changes in loop polarity and prominence determine system performance.
We investigate irreversible acceptance dynamics, leading to phenomena typical for paradigm change not described by widely used reversible and static behavioral models, e.g., multistability, hysteresis, critical parameter values (tipping points), irreversible state changes. Based on a recycling model, we explain these phenomena and develop a simple, generic mathematical model describing the basic traits of acceptance dynamics. Analytical investigations and numerical experiments with this generic model show reproduction of the above mentioned phenomena. In addition, the generic model shows the interplay between internal and external forces. The relation of their time constants is shown to play a crucial role, leading to reversible elasticity dynamics or irreversible acceptance dynamics. Critical parameter values (tipping points) separating elasticity dynamics from acceptance dynamics can be deduced from the generic model. We show that some simplifications applied to the waste recycling model lead to the generic acceptance model. Further, the acceptance model is shown to comprise also the well-known Bass model to describe market diffusion of new products. Finally, we discuss benefits of the generic model, its possible extensions to include additional phenomena, and its research implications.
In irrigation systems over-abstraction of water and/or neglected maintenance are common problems
faced by their users. For a generalized system with head- and tail-users, which interact through water
abstraction and maintenance, a feedback structure is presented. It builds on causal relationships derived
from theoretical work on collective action and irrigation. The concept of the model can be looked upon as
a general formulation of two mutually but asymmetrically dependent groups of users with regard to a
common resource. Main objective of the study is to provide a systems framework allowing for a deeper
understanding of the social and institutional nature of irrigation problems. It is embedded in
transdisciplinary research in Kyrgyzstan and Kenya aimed at developing strategies for a sustainable future
in semi-arid rural areas.
Virtual teams are fast becoming the norm in organizations and strategies are needed to deal with the new challenges that they create. Software Project Dynamics is a field of research that uses system dynamics simulation to explore software engineering issues. The objective of this research effort was to enhance systematically the understanding of virtual software engineering by using the system dynamics methodology and existing software project dynamic models. To accomplish the research objective, the following tasks were accomplished: First, an extensive literature review was done. Second, a Software Project Dynamics model was reproduced. Third, the model was used as an experimentation vehicle. This paper suggests that system dynamics is a viable tool in the exploration of virtual software engineering challenges. A new field of research is recommended to deal with additional challenges of virtual software project teams by using system dynamics with the proposed name: Virtual Software Project Dynamics.
Decision makers are often faced with insufficient and incomplete information, yet are forced to make decisions on this basis. The result may often be unintended consequences or situations where too few or too many resources have been allocated to solve the problem. Practicing decision making is often realised through live-exercises, which tend to be extremely expensive, or by using table-top games, providing a much lesser amount of realism to the game. MindLab allows for more sophisticated training arenas to a relatively low cost. The idea is to create a simulation model general enough to accommodate different decision making scenarios, accompanied by relatively rich user interfaces and an experiment setting that gives the game a high level of realism. This paper looks into how the MindLab architecture functions, as well as presenting two different simulation models with accompanied user interfaces that are currently being used with MindLab.
This paper focuses on the problem of rural energization in isolated regions in Colombia (Not interconnected zones NIS). Using the Sustainable Livelihood approach we assess the situation of the isolated communities before and after energization. Systems dynamics is used for simulating and evaluating energy policies. We apply our approach to the municipality of Jambaló in the Cauca department, Colombia.
This paper reports the results of a comparison of quantitative and qualitative approaches to systems analysis. The primary goal of the investigation was to test a heuristic for qualitative analysis previously proposed by the author that is intended to improve recognition of potential sources of failure for models used for forecasting. A series of papers published by John Sterman, George Richardson, and Pål Davidsen in the mid- to late-1980s examining resource estimation methods and the petroleum lifecycle were selected for analysis based on their completeness and perceived high quality of the models both quantitative and qualitative. The quantitative results presented in those papers are compared to published data and some potential sources of deviation are identified. The paper then presents an analysis of the qualitative models contained in the papers, highlighting the differences in the nature of insights available from the qualitative and quantitative analyses and illustrating how this expanded logic for qualitative analysis may contribute to the formulation and bounding process for predictive system dynamic models.
This paper describes an interdisciplinary approach to computer modeling of large-scale power systems. System dynamics is used to represent the the feedback relationships which govern the long-term evolution of the system, while engineering methods are used to calculate the short-term prices and power flows in the transmission network. This approach has been implemented in a model of the WECC, the Western Electricity Coordinating Council. The paper uses the WECC model to simulate the impact of the carbon allowances market envsioned by the Climate Stewardship Act of 2003. The simulations indicate that the western electricity system could achieve dramatic reductions in carbon emissions over the next two decades. The preliminary results indicate that the large reduction could be achieved with only half the increase in retail electricity rates that have been predicted for the nation as a whole.
Participatory environmental modeling is an adaptive management tool which natural resource managers, those dependent upon natural resources, property owners, and government agencies may use to help them understand the complexities of ecosystem management. Models have been used for sage-grouse, bear and fishery management, estuary systems and watersheds. These models share adaptive management theory, but differ on many other aspects such as the number of stakeholders and the degree to which they are involved. There can be many levels of involvement that are layered in a representative fashion with the modelers and intensely involved participants at the core. Varying physical, social and economic boundaries and the availability of data affect the time spent on different facets of the process. Finally, the intended use of the model may differ. Some processes are designed around group learning while others create tools which will assist with management decisions.