Breakthroughs in Decision Science and Risk Analysis

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Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis

Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science.

Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes:

  • An emphasis on new approaches rather than only classical and traditional ideas
  • Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions
  • Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management
  • Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified
  • Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence

Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

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About the author

Louis Anthony (Tony) Cox, Jr. PhD, is Chief Sciences Officer of NextHealth Technologies, a Denver-based health care advanced analytics software company and President of Cox Associates, Inc., a Denver-based applied research company specializing in quantitative health risk assessment, risk analysis, causal modeling, and operations research.  Dr. Cox is also Clinical Professor of Biostatistics and Informatics at the University of Colorado at Denver, a member of the National Academy of Engineering, and Editor-in-Chief of Risk Analysis: An International Journal

 

 

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Additional Information

Publisher
John Wiley & Sons
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Published on
Feb 23, 2015
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Pages
328
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ISBN
9781118938898
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Language
English
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Genres
Business & Economics / Decision-Making & Problem Solving
Business & Economics / General
Business & Economics / Operations Research
Technology & Engineering / Operations Research
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Content Protection
This content is DRM protected.
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Available on Android devices
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THE PRACTICAL, EASY INTRODUCTION TO MODERN SUPPLY CHAIN/LOGISTICS MANAGEMENT FOR EVERY PROFESSIONAL AND STUDENT!

COVERS CORE CONCEPTS, PLANNING, OPERATIONS, INTEGRATION, COLLABORATION, NETWORK DESIGN, AND MORE SHOWS HOW TO MEASURE, CONTROL, AND IMPROVE ANY SUPPLY CHAIN INCLUDES PRACTICAL ADVICE FOR JUMPSTARTING YOUR OWN SUPPLY CHAIN CAREER

This easy guide introduces the modern field of supply chain and logistics management, explains why it is central to business success, shows how its pieces fit together, and presents best practices you can use wherever you work.

Myerson explains key concepts, tools, and applications in clear, simple language, with intuitive examples that make sense to any student or professional. He covers the entire field: from planning through operations, integration and collaboration through measurement, control, and improvement.

You’ll find practical insights on hot-button issues ranging from sustainability to the lean-agile supply chain. Myerson concludes by helping you anticipate key emerging trends—so you can advance more quickly in your own career.

Trillions of dollars are spent every year on supply chains and logistics. Supply chain management is one of the fastest growing areas of business, and salaries are rising alongside demand. Now, there’s an easy, practical introduction to the entire field: a source of reliable knowledge and best practices for students and professionals alike.

Paul A. Myerson teaches you all you’ll need to start or move forward in your own supply chain career. Writing in plain English, he covers all the planning and management tasks needed to transform resources into finished products and services, and deliver them efficiently to customers.

Using practical examples, Myerson reviews the integration, collaboration, and technology issues that are essential to success in today’s complex supply chains. You’ll learn how to measure your supply chain’s performance, make it more agile and sustainable, and focus it on what matters most: adding customer value.

MASTER NUTS-AND-BOLTS OPERATIONAL BEST PRACTICES
Improve procurement, transportation, warehousing, ordering, reverse logistics, and more BUILD A BETTER GLOBAL SUPPLY CHAIN
Manage new risks as you improve sustainability STRENGTHEN KEY LINKAGES WITH YOUR PARTNERS AND CUSTOMERS
Get supply chains right by getting collaboration right PREVIEW THE FUTURE OF SUPPLY CHAINS—AND YOUR SUPPLY CHAIN CAREER
Discover “where the puck is headed”—so you can get there first

Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.

But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.

Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. 

Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. 

But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.

 Each chapter will cover a different technique in a spreadsheet so you can follow along:

Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language

You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

Improving Risk Analysis shows how to better assess and manage uncertain risks when the consequences of alternative actions are in doubt. The constructive methods of causal analysis and risk modeling presented in this monograph will enable to better understand uncertain risks and decide how to manage them.

The book is divided into three parts. Parts 1 shows how high-quality risk analysis can improve the clarity and effectiveness of individual, community, and enterprise decisions when the consequences of different choices are uncertain. Part 2 discusses social decisions. Part 3 illustrates these methods and models, showing how to apply them to health effects of particulate air pollution.

"Tony Cox’s new book addresses what risk analysts and policy makers most need to know: How to find out what causes what, and how to quantify the practical differences that changes in risk management practices would make. The constructive methods in Improving Risk Analysis will be invaluable in helping practitioners to deliver more useful insights to inform high-stakes decisions and policy,in areas ranging from disaster planning to counter-terrorism investments to enterprise risk management to air pollution abatement policies. Better risk management is possible and practicable; Improving Risk Analysis explains how."
Elisabeth Pate-Cornell, Stanford University

"Improving Risk Analysis offers crucial advice for moving policy-relevant risk analyses towards more defensible, causally-based methods. Tony Cox draws on his extensive experience to offer sound advice and insights that will be invaluable to both policy makers and analysts in strengthening the foundations for important risk analyses. This much-needed book should be required reading for policy makers and policy analysts confronting uncertain risks and seeking more trustworthy risk analyses."
Seth Guikema, Johns Hopkins University

"Tony Cox has been a trail blazer in quantitative risk analysis, and his new book gives readers the knowledge and tools needed to cut through the complexity and advocacy inherent in risk analysis. Cox’s careful exposition is detailed and thorough, yet accessible to non-technical readers interested in understanding uncertain risks and the outcomes associated with different mitigation actions. Improving Risk Analysis should be required reading for public officials responsible for making policy decisions about how best to protect public health and safety in an uncertain world."
Susan E. Dudley, George Washington University

Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis

Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science.

Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes:

An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence

Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

This book grew out of an effort to salvage a potentially useful idea for greatly simplifying traditional quantitative risk assessments of the human health consequences of using antibiotics in food animals. In 2001, the United States FDA’s Center for Veterinary Medicine (CVM) (FDA-CVM, 2001) published a risk assessment model for potential adverse human health consequences of using a certain class of antibiotics, fluoroquinolones, to treat flocks of chickens with fatal respiratory disease caused by infectious bacteria. CVM’s concern was that fluoroquinolones are also used in human medicine, raising the possibility that fluoroquinolone-resistant strains of bacteria selected by use of fluoroquinolones in chickens might infect humans and then prove resistant to treatment with human medicines in the same class of antibiotics, such as ciprofloxacin. As a foundation for its risk assessment model, CVM proposed a dramatically simple approach that skipped many of the steps in traditional risk assessment. The basic idea was to assume that human health risks were directly proportional to some suitably defined exposure metric. In symbols: Risk = K × Exposure, where “Exposure” would be defined in terms of a metric such as total production of chicken contaminated with fluoroquinolone-resistant bacteria that might cause human illnesses, and “Risk” would describe the expected number of cases per year of human illness due to fluoroquinolone-resistant bacterial infections caused by chicken and treated with fluoroquinolones.
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