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Simulation research has made some notable contributions in political science. This article describes a variety of simulation projects and points out the strengths and weaknesses of simulation in contrast with other methods of research. The strength of simulation research is that it is naturally suited to modeling projects that include a large number of autonomous, interacting agents. Statistical and formal methods of analysis have made contributions in these areas, but there is good reason to believe that simulation can go further. This point is explored in several contexts, including social choice theory, individual-level simulation models, international relations, the prisoner's dilemma game, and more general agent-based models of multiperson interaction.

Identifying high-leverage intervention points to increase cyber resiliency—the ability to provide and maintain acceptable service levels in the face of challenges— requires identifying, integrating, and framing a diverse set of strategies that cut across boundaries of governments, corporation, non-profits, and individuals. Drawing on a preliminary framework developed by Jonathan Zittrain, we identify several sources of corporate interventions and suggest possible trajectories for intervention effectiveness over time by utilizing simulation modeling. The overall goal of this research is to develop innovative management and operational approaches using experts, emerging data sets, policy analysis, and relevant theory, along with simulation-modeling, to enable real-world implementation of high-leverage opportunities to promote corporate resiliency to cyber threats. ; This material is based on work supported by the U.S. Office of Naval Research, Grant No. N00014-09-1-0597. Any opinions, findings, conclusions or recommendations therein are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.

This article describes and assesses the development of a major evaluation and policy research tool-microdata simulation modeling-over the past two decades. The method of microdata simulation modeling is described and its reliance on the development of large, nationally weighted household surveys is noted. After a brief tracing of the history of this evaluation method from the first-generation static models to dynamic models, to models with economic behavior imbedded in them, and to applied general equilibrium models, the problems and prospects of the technique are assessed. The analytic gains in richness and reliability are cited, as are the offsetting problems of cost, complexity, and the reliability of the underlying microdata and behavioral response junctions. The discussion concludes with an examination of the effect of this War on Poverty-stimulated research method on the development of the social sciences.

Intro -- Preface -- Contents -- Contributors -- 1 Simulation Modeling of Forest Landscape Disturbances: An Overview -- 1.1 Background -- 1.2 The Topic -- 1.2.1 Forest Landscapes -- 1.2.2 Disturbances -- 1.2.3 Simulation Modeling -- 1.3 The Contents of the Book -- References -- 2 Modeling Windthrow at Stand and Landscape Scales -- 2.1 Introduction -- 2.2 Overview of Factors that Contribute to Windthrow -- 2.3 Empirical Modeling -- 2.3.1 Approaches to Empirical Modeling -- 2.3.2 Advantages and Disadvantages of Empirical Models -- 2.4 Hybrid-Mechanistic-Empirical Models -- 2.4.1 Windthrow Mechanics as Represented in Hybrid-Mechanistic Models -- 2.4.2 Overview of Hybrid-Mechanistic Models -- 2.4.3 Integration of Hybrid-Mechanistic Models into Spatial Decision Support Models -- 2.4.4 Advantages and Disadvantages of Hybrid-Mechanistic Modeling -- 2.5 Discussion of Modeling Gaps and Potential Approaches -- 2.5.1 Representation of Spatial Variability in Factors Contributing to Windthrow -- 2.5.2 Representation of Temporal Variability in Factors Contributing to Windthrow -- 2.5.3 Improving Windthrow Modeling at the Landscape-Scale -- 2.5.3.1 Integrating Model Predictions with Consequences and Responses -- 2.6 Conclusions -- References -- 3 Approaches to Modeling Landscape-Scale Drought-Induced Forest Mortality -- 3.1 Introduction -- 3.2 Effects of Drought on Forest Landscapes -- 3.2.1 Drought Dynamics -- 3.3 Approaches to Modeling Drought -- 3.3.1 Past and Developing Approaches -- 3.3.2 Empirical Approach -- 3.3.2.1 Case Study 1-Oconto County, Wisconsin -- 3.3.2.2 Critique of the Empirical Approach -- 3.3.3 Deterministic Approach -- 3.3.3.1 Case Study 2-Voyageurs National Park -- 3.3.3.2 Critique of the Deterministic Approach -- 3.3.4 Process-Based (Mechanistic) Approach -- 3.3.4.1 Critique of the Mechanistic Approach -- 3.4 Future Prospects.

The development of the global economy affects the environment in which we are living, often in negative ways, including pollutions, exhaust emissions, depletion of natural resources, and other concerns. Therefore, it is so important to use resources in a reasonable, sustainable manner and to be aware of the impact of our activities on the environment, which in the next stage translates into trying to limit negative impacts to the environment. Aspects of sustainable supply chain (SSC) have become more and more popular in the last years. Entrepreneurs pay more attention to the aspect of sustainable development in their activities, especially to exhaust emissions. The rational use of resources is also a very important topic. Not only economic aspects but also environmental and social topics are taken into account in company politics, which is characteristic of sustainable development. The main purpose of this article is to show the benefits of SSC. For this purpose, the simulation models showing the supply chain and the sustainable supply chain will be built. The benefits of SSC in economic and environmental aspects will be presented using a computer simulation tool. Using a simulation tool fits in with sustainability; thanks to modeling supply chains in their virtuality and analysis, many resources can be saved in reality (for example, thanks to the consolidation of freight).