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Explains multi-level models of enterprise systems and covers modeling methodology This book addresses the essential phenomena underlying the overall behaviors of complex systems and enterprises. Understanding these phenomena can enable improving these systems. These phenomena range from physical, behavioral, and organizational, to economic and social, all of which involve significant human components. Specific phenomena of interest and how they are represented depend on the questions of interest and the relevant domains or contexts. Modeling and Visualization of Complex Systems and Enterprises examines visualization of phenomena and how understanding the relationships among phenomena can provide the basis for understanding where deeper exploration is warranted. The author also reviews mathematical and computational models, defined very broadly across disciplines, which can enable deeper understanding. * Presents a 10 step methodology for addressing questions associated with the design or operation of complex systems and enterprises * Examines six archetypal enterprise problems including two from healthcare, two from urban systems, and one each from financial systems and defense systems * Provides an introduction to the nature of complex systems, historical perspectives on complexity and complex adaptive systems, and the evolution of systems practice Modeling and Visualization of Complex Systems and Enterprises is written for graduate students studying systems science and engineering and professionals involved in systems science and engineering, those involved in complex systems such as healthcare delivery, urban systems, sustainable energy, financial systems, and national security.

Explores the nature of academic enterprises, including why they work the way they do and where such enterprises are headed, with the goal of gaining insights into where change can and will happen This book looks at universities from a whole-enterprise perspective. It explores the steady escalation of the costs of higher education and uses a computational economic model of complex academic enterprises. This model includes component models of research, teaching, administration, and brand value. Understanding the relationships among practices, processes, structure, and ecosystem provides the basis for transforming academia, leveraging its strengths and overcoming its limitations. More specifically, this architecture helps the reader understand how various elements of the enterprise system either enable or hinder other elements of the system, all of which are embedded in a complex behavioral and social ecosystem. Each topic is explored in terms of the levels of the architecture at which it primarily functions. Levers of change within each area are discussed, using many experiences of pursuing such issues in a range of academic enterprises. • Provides a new methodology by taking a more systems-oriented approach to education systems as a whole • Shows how various elements of the enterprise system either enable or hinder other elements of the system • Offers alternative strategies for transformation of academic enterprises Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where the University Enterprise Is Headed is a reference for systems scientists and engineers, economists, social scientists, and decision makers. William B. Rouse is the Alexander Crombie Humphreys Chair within the School of Systems & Enterprises and Director of the Center for Complex Systems and Enterprises at Stevens Institute of Technology, Hoboken, New Jersey. He is also Professor Emeritus, and former Chair, of the School of Industrial and Systems Engineering at the Georgia Institute of Technology, Atlanta, Georgia. Rouse has written hundreds of articles and book chapters, and has authored many books, including most recently Modeling and Visualization of Complex Systems and Enterprises (Wiley, 2015).

Human survival depends on our ability to predict future outcomes so that professionals can make informed decisions. Human cognition and perception are optimized for local, short-term decision-making, such as deciding when to fight or flight, whom to mate, or what to eat. In the 21st century, computational models and visualizations of model results inform much of humans decision-making: near real-time weather forecasts help us decide when to take an umbrella, plant, or harvest; where to ground airplanes; or when to evacuate inhabitants in the path of a hurricane, tornado, or flood. Here, Borner et al look at the tends and development of forecasting innovations in science, technology, and education.

The future of the American academic research enterprise is considered. Data are presented that characterize the resources available for the 160 best-resourced research universities, a small subset of the 2,285 4-year, nonprofit, higher education institutions. A computational model of research universities was extended and used to simulate three strategic scenarios: status quo, steady decline in foreign graduate student enrollments, and downward tuition pressures from high-quality, online professional master’s programs. Four specific universities are modeled: large public and private, and small public and private. The former are at the top of the 160 in terms of resources, while the latter are at the bottom of the 160. The model’s projections suggest how universities might address these competitive forces. In some situations, it would be in the economic interests of these universities to restrict research activities to avoid the inherent subsidies these activities require. The computational projections portend the need for fundamental change of approaches to business for universities without large institutional resources.

Fundamental Economic Principles, Methods, and Tools for Addressing Human Systems Integration Issues and Tradeoffs Human Systems Integration (HSI) is a new and fundamental integrating discipline designed to help move business and engineering cultures toward more human-centered systems. Integrating consideration of human abilities, limitations, and preferences into engineering systems yields important cost and performance benefits that otherwise would not have been accomplished. In order for this new discipline to be effective, however, a cultural change—starting with organizational leadership—is often necessary. The Economics of Human Systems Integration explains the difficulties underlying valuation of investments in people's training and education, safety and health, and work productivity. It provides an overview of how the field of economics addresses these difficulties, focusing on human issues associated with design, development, production, operations, maintenance, and sustainment of complex systems. The set of thought leaders recruited as contributors to this volume collectively provides a compelling set of data and principles for assessing the economic value of investing in people, not just in general but in specific investment situations. The early chapters provide the contexts for HSI and investment analysis, illustrating the enormous difference context makes in how issues are best framed and analyzed. A host of practical methods and tools for investment valuation are then presented. Provided are: * A variety of real-world applications of economic analysis ranging from military acquisition and automotive investment to healthcare and high-tech investments in general, in both the U.S. and abroad * A range of economics-based methods and tools for cost analysis, cost-benefit analysis, and investment analysis, as well as sources of data for performing such analyses * Differing perspectives on economic decision-making, including a range of private sector points of view, as well as government and regulatory perspectives In addition, five real-world case studies illustrate how such valuations have been done and their major impacts on investment decisions. HSI professionals, systems engineers, and finance professionals who address investment analysis will appreciate the wide range of methods and real-life applications; senior undergraduates and masters-level graduate students will find this to be an excellent textbook that provides theory and supports practice.

A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Information Technology is key to today's modern world. Scientific theories introduced in the last five decades can now be realized with the latest computational infrastructure. Modeling and simulation, along with Big Data technologies are at the forefront of such exploration and investigation. The text offers a number of simulation-based methods, technologies, and approaches that are designed to encourage the reader to incorporate simulation technologies to further their understanding of emergent behavior in complex systems. The authors present a resource for those designing, developing, managing, operating, and maintaining systems, including system of systems. The guide is designed to help better detect, analyse, understand, and manage the emergent behaviour inherent in complex systems engineering in order to reap the benefits of innovations and avoid the dangers of unforeseen consequences. This vital resource: * Presents coverage of a wide range of simulation technologies * Explores the subject of emergence through the lens of Modeling and Simulation (M&S) * Offers contributions from authors at the forefront of various related disciplines such as philosophy, science, engineering, sociology, and economics * Contains information on the next generation of complex systems engineering Written for researchers, lecturers, and students, Emergent Behavior in Complex Systems Engineering provides an overview of the current discussions on complexity and emergence, and shows how systems engineering methods in general and simulation methods in particular can help in gaining new insights in complex systems engineering.

Entities involved in population health often share a common mission while acting independently of one another and perhaps redundantly. Population health is in everybody’s interest, but nobody is really in charge of promoting it. Across governments, corporations, and frontline operations, lack of coordination, lack of resources, and lack of reliable, current information have often impeded the development of situation-awareness models and thus a broad operational integration for population health. These deficiencies may also affect the technical, organizational, policy, and legal arrangements for information sharing, a desired practice of high potential value in population health. In this article, we articulate a vision for a next-generation modeling effort to create a systems architecture for broadly integrating and visualizing strategies for advancing population health. This multipurpose systems architecture would enable different views, alerts, and scenarios to better prepare for and respond to potential degradations in population health. We draw inspiration from systems engineering and visualization tools currently in other uses, including monitoring the state of the economy (market performance), security (classified intelligence), energy (power generation), transportation (global air traffic control), environment (weather monitoring), jobs (labor market dynamics), manufacturing and supply chain (tracking of components, parts, subassemblies, and products), and democratic processes (election analytics). We envision the basic ingredients for a population health systems architecture and its visualization dashboards to eventually support proactive planning and joint action among constituents. We intend our ambitious vision to encourage the work needed for progress that the population deserves.

Examines current and prospective challenges surrounding global challenges of education, energy, healthcare, security, and resilience This book discusses issues in large-scale systems in the United States and around the world. The authors examine the challenges of education, energy, healthcare, national security, and urban resilience. The book covers challenges in education including America's use of educational funds, standardized testing, and the use of classroom technology. On the topic of energy, this book examines debates on climate, the current and future developments of the nuclear power industry, the benefits and cost decline of natural gases, and the promise of renewable energy. The authors also discuss national security, focusing on the issues of nuclear weapons, terrorism and cyber security. Urban resilience is addressed in the context of natural threats such as hurricanes and floods. * Studies the usage of a globalized benchmark for both student and pedagogical performance * Covers topics such as surveillance, operational capabilities, movement of resources, and the pros and cons of globalization * Examines big data, evolving medical methodologies and effects on the medical educational curriculum, and the positive effects of electronic records in healthcare data Perspectives on Complex Global Challenges: Education, Energy Healthcare, Security, and Resilience serves as a reference for government officials, personnel in security, business executives and system engineers.

In this study, the authors used simulation to explore factors that might influence hospitals' decisions to adopt evidence-based interventions. Specifically, they developed a simulation model to examine the extent to which hospitals would benefit economically from the transitional care model (TCM). The TCM is designed to transition high-risk older adults from hospitals back to communities using interventions focused on preventing readmissions.The authors used qualitative methods to identify and validate simulation facets. Four simulation experiments explored the economic impact of the TCM on more than 3,000 U.S. hospitals: (1) magnitude of readmission penalty, (2) application to specific diagnosis-related groups, (3) level of cost sharing between payer and provider, and (4) capitated versus fee-for-service payments. The simulator projected hospital-specific economic effects. The authors used Monte Carlo methods for the simulations, which were parameterized with public data sets from the Centers for Medicare & Medicaid Services (CMS) and TCM data from randomized controlled trials and comparative effectiveness studies.Under current conditions, the simulation indicated that only 10 of more than 3,000 Medicare-certified hospitals would benefit financially from the TCM. If current readmission penalties were doubled, the number of hospitals projected to benefit would increase to 300. Targeting selected diagnosis cohorts would also increase the number of hospitals to 300. If payers reimbursed providers for 100% of the TCM costs, 2,000 hospitals would benefit financially. Under a capitated payment model, 1,500 hospitals would benefit from the TCM.Current CMS penalties-or reasonable increases-have little economic effect on the TCM. In the current environment, two strategies are likely to facilitate adoption: (1) persuading payers to reimburse TCM costs and (2) focusing on hospitals with higher bed occupancies and higher revenue patients.