We present the story of our involvement in the formulation of the USâs policy for mitigating pandemic influenza. At the heart of this formulation was modeling but in its actualization was interaction, drive, serendipity, hard work and advocacy for the use of models to select robust policy in the face of great uncertainty. Reflecting on this entire process and others where high impact influence has been achieved has led us to a recognition that nearly all the systems that we wish to influence can be categorized as Complex Adaptive Systems of Systems or CASoS and that our field of endeavor is CASoS Engineering.
Iranian National Petrochemical Company (NPC) has recently started a fast development. Because of the imbalance in development of NPC, despite of its reputation and history, is not able to recruit qualified workforce. Managers concern the future of the industry as this flow of low qualified human resources accedes to the top of the organizational pyramid. In this paper, a system dynamics model has been used to consider the impact of structural development on human resources of NPC. The results of simulation show that if managers of NPC desire the industry to grow faster than a particular rate, it will finally collapse. It is a quite counter intuitive result. A number of insights have been obtained through the simulations and some practical policies have been suggested and simulated.
Informed by a theory of symbolic interactionism, this research explores the dynamics of dyadic communications within which understanding is socially constructed. Based upon an earlier analysis of a case-study investigation in a large multi-disciplinary governmental project with multiple contractors and subcontractors, we modify, simulate, and analyze a dynamic model of dyadic communications. Our simulation results support the previous findings and, in addition, underscore the role of path dependency in creating shared understanding; that is, first interpretations affected by random and imprecise messages can influence subsequent shared understanding and meaning construction significantly. Finally, our sensitivity analysis sheds light on the effects of decision and action delay and observation and orientation delay. Delays, which in part represent how responsive a partner is, can have counter-intuitive effects on players convergence or divergence in a dyadic communication. Our study shows that reducing observation and orientation delay can be considered as a leverage point for communication convergence, while increasing decision and action delay may facilitate convergence.
Public policies often fail to achieve their intended result due to the complexity of both the environment and the policy making process. In this article, we review the benefits of using small system dynamics models to address public policy questions. First we discuss the main difficulties inherent in the public policymaking process. Then, we discuss how small system dynamics models can address policymaking difficulties by examining two promising examples: the first in the domain of urban planning and the second in the domain of social welfare. These examples show how we can get insightful and important lessons for policy making that are exclusive to the endogenous and aggregate perspective in modeling and simulation.
This paper explores the use of causal loop modeling to depict the structure of forces that influence ethical behavior. Our goal is to demonstrate that this kind of modeling can capture and show the complexity inherent in ethics situations. The desire to increase ethical performance is part of a system which includes the desire to increase other aspects of performance, such as competitiveness, profitability, job securoty, wealth, etc. Three examples are used to demonstrate the approach. The first model depicts the generic framework of forces that shape personal ethics behavior. The second model depicts some of the forces that led to the current sub-prime mortgage crisis. The third model focuses on factors and causal loops that can combine to shape the ethical behavior of a business executive. Insights into ethics influences can be gained from the modeling process itself, and from examining the resulting model structures. These insights can provide guidance for policy makers and managers focused on raising ethics behavior. Although our models focus on business ethics in developed free-market economies, the approach is readily applicable to other contexts, such as analysis of the forces impacting on ethics in the professions or in government.
One of the most important concerns for food industry is safety. Predictive Microbiology is the application of mathematical models to describe microbial behavior in order to prevent food spoilage as well as food-borne illness. Because of complexity of microbial behavior and food systems, Predictive Microbiology presents some limitations. System Dynamics could be a useful alternative and complementary tool to model and predict microbiological behavior in foods while providing a graphical interface and structures linked with a series of equations, to clarify and improve quantitative Predictive Microbiology descriptions.