Risk - A Multidisciplinary Introduction

1. Front Matter

   Pages I-X

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2. Risk in History, Society and Science

   1. Front Matter

      Pages 1-1

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   2. Risk in Historical Perspective: Concepts, Contexts, and Conjunctions

      • Karin Zachmann

      Pages 3-35

   3. Risk Management and Business Ethics: Integrating the Human Factor

      • Christoph Luetge, Eberhard Schnebel, Nadine Westphal

      Pages 37-61

   4. Decision-Making Under Risk: A Normative and Behavioral Perspective

      • Daniel Straub, Isabell Welpe

      Pages 63-93

   5. The New Role of Mathematical Risk Modeling and Its Importance for Society

      • Klaus Mainzer

      Pages 95-129

3. Quantitative Risk Methodology

   1. Front Matter

      Pages 131-131

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   2. The Mathematical Concept of Measuring Risk

      • Francesca Biagini, Thilo Meyer-Brandis, Gregor Svindland

      Pages 133-150

   3. Quantifying Extreme Risks

      • Vicky Fasen, Claudia Klüppelberg, Annette Menzel

      Pages 151-181

   4. Statistical Models for the Prediction of Genetic Values

      • Chris-Carolin Schön, Valentin Wimmer

      Pages 183-205

   5. Bayesian Risk Analysis

      • Claudia Czado, Eike Christian Brechmann

      Pages 207-240

   6. Dealing with Dependent Risks

      • Claudia Klüppelberg, Robert Stelzer

      Pages 241-277

   7. Model Risk and Uncertainty—Illustrated with Examples from Mathematical Finance

      • Karl F. Bannör, Matthias Scherer

      Pages 279-306

4. Risk Treatment in Various Applications

   1. Front Matter

      Pages 307-307

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   2. Cost-Benefit Analysis

      • Jutta Roosen

      Pages 309-331

   3. Engineering Risk Assessment

      • Daniel Straub

      Pages 333-362

   4. Integrated Modeling of Complex Production Automation Systems to Increase Dependability

      • Birgit Vogel-Heuser, Susanne Rösch

      Pages 363-385

   5. Information Technology Risks: An Interdisciplinary Challenge

      • Michael Schermann, Manuel Wiesche, Stefan Hoermann, Helmut Krcmar

      Pages 387-405

   6. Risk Issues in Developing Novel User Interfaces for Human-Computer Interaction

      • Gudrun Klinker, Manuel Huber, Marcus Tönnis

      Pages 407-439

   7. Translational Risk Models

      • Donna Pauler Ankerst, Vanadin Seifert-Klauss, Marion Kiechle

      Pages 441-458

This is a unique book addressing the integration of risk methodology from various fields. It will stimulate intellectual debate and communication across disciplines, promote better risk management practices and contribute to the development of risk management methodologies. Individual chapters explain fundamental risk models and measurement, and address risk and security issues from diverse areas such as finance and insurance, the health sciences, life sciences, engineering and information science. Integrated Risk Sciences is an emerging discipline that considers risks in different fields, aiming at a common language, and at sharing and improving methods developed in different fields. Readers should have a Bachelor degree and have taken at least one basic university course in statistics and probability. The main goal of the book is to provide basic knowledge on risk and security in a common language; the authors have taken particular care to ensure that all content can readily be understood by doctoral students and researchers across disciplines. Each chapter provides simple case studies and examples, open research questions and discussion points, and a selected bibliography inviting readers to further study.

• decision-making under risk
• extreme event risk
• integrated risk modeling
• probabilistic modeling for dependent risks
• reliability analysis
• risk reduction
• statistical risk analysis
• quality control, reliability, safety and risk
• climate change

• Department of Mathematics, Munich University of Technology, Munich, Germany

  Claudia Klüppelberg

• Faculty of Civil, Geo and Environmental Engineering, Munich University of Technology, Munich, Germany

  Daniel Straub

• TUM School of Management, Munich University of Technology, Munich, Germany

  Isabell M. Welpe

The research interests of Claudia Klüppelberg combine various disciplines of applied probability theory and statistics with applications to risk measurement in the areas of economic, technical and climate risks. Her fundamental research concentrates on advancing the modeling and the methodology for risk analysis and risk measurement with applications to real-world problems. Before being appointed Full Professor of Mathematical Statistics at the Technische Universität München (TUM), she spent several years at ETH Zurich and at Mainz University. From 2008 to 2011 she chaired the focus group Risk Analysis and Stochastic Modeling at the TUM’s Institute for Advanced Study. Daniel Straub develops and teaches reliability analysis, risk assessment and probabilistic decision making for infrastructure, environmental and general engineering systems. He received his doctorate in 2004 at ETH Zurich. Prior to joining the TUM as a Professor of Engineering Risk Analysis in 2008, he was a postdoctoralresearcher and adjunct professor at the University of California, Berkeley (2006 to 2008). Beyond his academic work, he is active as a consultant to various industries, including the offshore, maritime, energy, infrastructure and transportation sectors. Isabell M. Welpe conducts research in the area of strategy and organization from a behavioral science perspective, with a focus on performance management, strategic leadership, organizational design, behavior in organizations and the role of digital technology and social media for and in organizations. She has held the Chair of Strategy and Organization at the TUM since 2009.

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