Suchergebnisse

Increasing attention is being paid to reliability, safety, and security issues in social systems. Scott Sagan examined why more security forces (a redundancy solution) may lead to less security.(1) He discussed how such a solution can backfire due to three major issues (i.e., "common‐mode error,""social shirking," and "overcompensation"). In this article, using Sagan's hypotheses, we simulate and analyze a simple and generic security system as more guards are added to the system. Simulation results support two of Sagan's hypotheses. More specifically, the results show that "common‐mode error" causes the system to backfire, and "social shirking" leads to an inefficient system while exacerbating the common‐mode error's effect. Simulation results show that "overcompensation" has no effect of backfiring, but it leads the system to a critical state in which it can easily be affected by the common‐mode error. Furthermore, the simulation results make us question the importance of the initial power of adversaries (e.g., terrorists) as the results show that, for any exogenous level of adversary power, the system endogenously overcompensates to a level that makes the system more susceptible to being attacked.

AbstractUnderstanding the state of the COVID‐19 pandemic relies on infection and mortality data. Yet official data may underestimate the actual cases due to limited symptoms and testing capacity. We offer a simulation‐based approach which combines various sources of data to estimate the magnitude of outbreak. Early in the epidemic we applied the method to Iran's case, an epicenter of the pandemic in winter 2020. Estimates using data up to March 20th, 2020, point to 916,000 (90% UI: 508 K, 1.5 M) cumulative cases and 15,485 (90% UI: 8.4 K, 25.8 K) total deaths, numbers an order of magnitude higher than official statistics. Our projections suggest that absent strong sustaining of contact reductions the epidemic may resurface. We also use data and studies from the succeeding months to reflect on the quality of original estimates. Our proposed approach can be used for similar cases elsewhere to provide a more accurate, early, estimate of outbreak state.© 2020 System Dynamics Society

AbstractWe reflect on our past 7 years of collaboration to develop systems models of U.S. higher education and scientific workforce development. Based on three recent modeling examples, we offer a methodological proposition that many traditional operations research (OR) models can be improved by including feedback processes, as is commonly done in system dynamics (SD) modeling. Such models, even if simple and approximate, can be powerful, insightful, easy to communicate, and effective. While these modeling examples may not follow conventional SD or OR modeling, they benefit from and contribute to both schools of modeling. We argue that to build such synergy modeling teams should be willing to create models building on the strengths of each school of modeling.Copyright © 2018 System Dynamics Society

AbstractPeople have difficulties inferring the behavior of a stock variable from its inflows and outflows. Our goal is to offer low‐cost interventions to help overcome this difficulty. We hypothesize that the failure to understand accumulation relates to the cognitive mode of thinking: if people use their System 2 mode of thinking (analytical thinking), they are more likely to answer stock–flow questions correctly. We conduct an experiment with 400 participants and test effects of two interventions. The study replicates previously observed stock–flow failure and uncovers several variables that can influence subjects' response to the department store task. One particular finding is that having participants answer an analytical question right before the department store task marginally increases their chances of answering stock–flow questions correctly. Copyright © 2015 System Dynamics Society

AbstractEconomic transition management is an important issue in countries that have not completely adjusted to the market economy style, as well in countries that temporarily implement price controls. The common concern is to manage the transition in a way that lessens the socio‐economic side effects of the process. This paper presents policy recommendations for the Iranian cement industry, which will undergo such a transition. Building on the commodity model literature and supported by interviews with different stakeholders in the industry, we develop a cement price model and calibrate it for Iran's economy. In the base run, we predict a large overshoot in price before it reaches its long‐term equilibrium state. Experimenting with the model, we suggest a specific transition policy which starts from drastic rise(s) in price before leaving the price up to the market. In addition, this paper gives some insights into analyzing similar economic policy problems. Copyright © 2010 John Wiley & Sons, Ltd.

AbstractService science theories do not fully explain failure cases in data‐intensive services – high‐technology services that utilize large volumes of data and provide customized information for users. In these service systems, the technological and social elements are highly interconnected: firms cannot maintain databases and analytic capabilities if they lack market penetration, which itself is influenced by performance of analytic capabilities and databases; a positive feedback loop. Informed by a case study, we develop a simulation model, postulate that market adoption is highly sensitive to the launch conditions, specifically with respect to the initial states of the system, and offer a dynamic theory in which highly nonlinear relationships among the initial states of the system drive outcomes of the market adoption of data‐intensive services. We argue that a tipping point exists at which small technological differences in the launch period differentiates between market success and failure. Furthermore, our analysis points to a strong self‐fulfilling mechanism whereby initial positive customer perception can increase the service's likelihood of success by indirectly influencing technological improvement. In contrast to the conventional belief, having a large number of initial adopters may negatively influence market adoption in the long run. A major source of the patterns observed is the high level of interdependencies between social and technological elements of data‐intensive services. © 2022 System Dynamics Society.

The US government has been increasingly supporting postdoctoral training in biomedical sciences to develop the domestic research workforce. However, current trends suggest that mostly international researchers benefit from the funding, many of whom might leave the USA after training. In this paper, we describe a model used to analyse the flow of national versus international researchers into and out of postdoctoral training. We calibrate our model in the case of the USA and successfully replicate the data. We use the model to conduct simulation‐based analyses of effects of different policies on the diversity of postdoctoral researchers. Our model shows that capping the duration of postdoctoral careers, a policy proposed previously, favours international postdoctoral researchers. The analysis suggests that the leverage point to help the growth of domestic research workforce is in the pregraduate education area, and many policies implemented at the postgraduate level have minimal or unintended effects on diversity. Copyright © 2013 John Wiley & Sons, Ltd.

The US government has been increasingly supporting postdoctoral training in biomedical sciences to develop the domestic research workforce. However, current trends suggest that mostly international researchers benefit from the funding, many of whom might leave the USA after training. In this paper, we describe a model used to analyse the flow of national versus international researchers into and out of postdoctoral training. We calibrate our model in the case of the USA and successfully replicate the data. We use the model to conduct simulation-based analyses of effects of different policies on the diversity of postdoctoral researchers. Our model shows that capping the duration of postdoctoral careers, a policy proposed previously, favours international postdoctoral researchers. The analysis suggests that the leverage point to help the growth of domestic research workforce is in the pregraduate education area, and many policies implemented at the postgraduate level have minimal or unintended effects on diversity.

Postdoctoral fellows (postdocs) comprise a large sector of the US scientific workforce. A substantial majority of postdocs are in a holding pattern, seeking tenure‐track assistant professorships. We model the postdoc population as a labour force in waiting—in queue. Postdocs enter the queue as they start their first postdoctoral appointment, and they leave in one of two ways: (i) obtaining the 'queue service' desired by the majority of postdocs, that is, an assistant professorship, or (2) reneging from the queue and seeking other positions. Using recent data from the US Survey of Doctorate Recipients, we show that the postdoc queue is one of those rare queueing systems where most of the queuers eventually renege rather than receive service. We find that only about 17% of postdocs ultimately land tenure‐track positions. The mean time in queue (postdoc career length) is 2.9 years, with significant variations across disciplines. We discuss policy implications. © 2018 John Wiley & Sons, Ltd.

Post-traumatic stress disorder (PTSD) stands out as a major mental illness; however, little is known about effective policies for mitigating the problem. The importance and complexity of PTSD raise critical questions: What are the trends in the population of PTSD patients among military personnel and veterans in the postwar era? What policies can help mitigate PTSD? To address these questions, we developed a system dynamics simulation model of the population of military personnel and veterans affected by PTSD. The model includes both military personnel and veterans in a "system of systems." This is a novel aspect of our model, since many policies implemented at the military level will potentially influence (and may have side effects on) veterans and the Department of Veterans Affairs. The model is first validated by replicating the historical data on PTSD prevalence among military personnel and veterans from 2000 to 2014 (datasets from the Department of Defense, the Institute of Medicine, the Department of Veterans Affairs, and other sources). The model is then used for health policy analysis. Our results show that, in an optimistic scenario based on the status quo of deployment to intense/combat zones, estimated PTSD prevalence among veterans will be at least 10% during the next decade. The model postulates that during wars, resiliency-related policies are the most effective for decreasing PTSD. In a postwar period, current health policy interventions (e.g., screening and treatment) have marginal effects on mitigating the problem of PTSD, that is, the current screening and treatment policies must be revolutionized to have any noticeable effect. Furthermore, the simulation results show that it takes a long time, on the order of 40 years, to mitigate the psychiatric consequences of a war. Policy and financial implications of the findings are discussed.