Publications

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Cigarette smoking presented the most significant public health challenge in the United States in the 20th Century and remains the single most preventable cause of morbidity and mortality in this country. A number of System Dynamics models exist that inform tobacco control policies. We reviewed them and discuss their contributions. We developed a theory of the societal lifecycle of smoking, using a parsimonious set of feedback loops to capture historical trends and explore future scenarios. Previous work did not explain the long-term historical patterns of smoking behaviors. Much of it used stock-and-flow to represent the decline in prevalence in the recent past. With noted exceptions, information feedbacks were not embedded in these models. We present and discuss our feedback-rich conceptual model and illustrate the results of a series of simulations. A formal analysis shows phenomena composed of different phases of behavior with specific dominant feedbacks associated with each phase. We discuss the implications of our society's current phase, and conclude with simulations of what-if scenarios. Because System Dynamics models must contain information feedback to be able to anticipate tipping points and to help identify policies that exploit leverage in a complex system, we expanded this body of work to provide an endogenous representation of the century-long societal lifecycle of smoking.

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A system dynamics model was developed in response to the apparent decline in STEM candidates in the United States and a pending shortage. The model explores the attractiveness of STEM and STEM careers focusing on employers and the workforce. Policies such as boosting STEM literacy, lifting the H-1B visa cap, limiting the offshoring of jobs, and maintaining training are explored as possible solutions. The system is complex, with many feedbacks and long time delays, so solutions that focus on a single point of the system are not effective and cannot solve the problem. A deeper understanding of parts of the system that have not been explored to date is necessary to find a workable solution.

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Based upon participant observation in group model building and content analysis of the system dynamics literature, we postulate that modeling efforts have a dual nature. On one hand, the modeling process aims to create a useful representation of a real-world system. This must be done, however, while aligning the clients’ mental models around a shared view of the system. There is significant overlap and confusion between these two goals and how they play out on a practical level. This research clarifies these distinctions by establishing an ideal-type dichotomy. To highlight the differences, we created two straw men: “micro world” characterizes a model that represents reality and “boundary object” represents a socially negotiated model. Using this framework, the literature was examined, revealing evidence for several competing views on problem definition and model conceptualization. The results are summarized in the text of this article, substantiated with strikingly polarized citations, often from the same authors. We also introduce hypotheses for the duality across the remaining phases of the modeling process. Finally, understanding and appreciation of the differences between these ideal types can promote constructive debate on their balance in system dynamics theory and practice.

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