Engineering Decision Making and Risk Management
An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics. Jeffrey W. Herrmann, PhD, is Associate Professor at the University of Maryland, where he holds a joint appointment with the Department of Mechanical Engineering and the Institute for Systems Research. A member of the Institute of Industrial Engineers, the Institute for Operations Research and the Management Sciences, the American Society of Mechanical Engineers, and the American Society for Engineering Education, Dr. Herrmann's research interests include production scheduling, decision making in product development, and public health preparedness planning.
Engineering Decision Making and Risk Management
This textbook covers important topics on decision making, presents tools for helping engineers make better decisions, and provides examples to illustrate the concepts and techniques. Students and engineers who study this material and apply these concepts and techniques should become better decision-makers.
Like the products and systems that engineers design, this textbook began as an idea for meeting a need and went through many iterations and revisions over time. In this case, the initial discussions about engineering decision making involved my colleague Linda Schmidt, an expert on design methodologies and design education. She and I discussed how engineers in product development organizations shared information and made decisions, and we decided to begin studying this activity as a system. Then, with our colleague Peter Sandborn, we were awarded a grant from the National Science Foundation to study how firms used information about environmental impacts in product development decision making. After studying multiple firms and publishing our results, the next step was to develop a course in which we could share our insights about decision making with others. We jointly developed a course outline, and in the Spring, 2004, semester I taught the course for the first time. Although a traditional decision analysis textbook was used, the course included topics beyond its scope, so I created course notes and expanded them every time I taught the course.
In the meantime, our research continued, and I developed three perspectives on decision making. This led me to reorganize the course (and the course notes) around these three perspectives, which provide a new way to consider engineering decision making. In addition, I included various topics on risk management, a type of decision-making process. These changes also emphasized the challenges of using a traditional decision analysis textbook that was organized in a completely different way. The organization of this course was not increasing mathematical difficulty but increasing conceptual complexity, and existing texts on decision analysis were inappropriate. The first draft of this textbook was my reorganized set of course notes, which I then divided and rearranged again to form distinct chapters.
This text discusses three perspectives on decision making: (1) the problem-solving perspective, (2) the decision-making process perspective, and (3) the decision-making system perspective. The text introduces these perspectives in Chapter 1 and covers them in sequence as the following paragraphs describe. Techniques for modeling and managing risk are included throughout the text where appropriate within this framework.
Chapters 2-6 consider the components and structure of decisions, which is the problem-solving perspective. Chapter 2 reviews some fundamental topics, including the context of a decision situation, fundamental objectives and means objectives, influence diagrams, rationality, choice strategies, dominance, "framing" a decision situation, risk acceptance criteria, and types of measurement scales. Understanding these important fundamental concepts can help one improve decision making.
After Chapter 2 are two chapters about decisions without uncertainty (Chapters 3 and 4) and then two chapters about decisions with uncertainty (Chapters 5 and 6).
Chapter 3 covers multicriteria decision making, which is a traditional topic in decision analysis and an important skill that is the foundation of decision making. This chapter covers multiple techniques: the Pugh matrix, a version of the analytic hierarchy process (AHP), multiattribute utility theory (MAUT), and conjoint analysis. It also discusses the usefulness of the "Value of a Statistical Life" and the differences between compensating and non-compensating solutions.
Chapter 4 reviews techniques for group decision making. This material fo