Disasters are the result of complex interactions between social and natural forces, acting at multiple scales from the individual and community to the organisational, national and international level. Effective disaster planning, response and recovery require an understanding of these interacting forces, and the role of power, knowledge and organizations. This book sheds new light on these dynamics, and gives disaster scholars and practitioners new and valuable lessons for management and planning in practice. The authors draw on methods across the social sciences to examine disaster response and recovery as viewed by those in positions of authority and the 'recipients' of operations. These first two sections examine cases from Hurricane Katrina, while the third part compares this to other international disasters to draw out general lessons and practical applications for disaster planning in any context. The authors also offer guidance for shaping institutional structures to better meet the needs of communities and residents.

Systemic Risk opens new ground in the study of financial crises. It treats the financial system as a complex adaptive system and shows how lessons from network disciplines - such as ecology, epidemiology, and statistical mechanics - shed light on our understanding of financial stability. Using tools from network theory and economics, it suggests that financial systems are robust-yet-fragile, with knife-edge properties that are greatly exacerbated by the hoarding of funds and the fire sale of assets by banks. This book studies the damaging network consequences of the failure of large inter-connected institutions, explains how key funding markets can seize up across the entire financial system, and shows how the pursuit of secured finance by banks in the wake of the global financial crisis can generate systemic risks. The insights are then used to model banking systems calibrated to data to illustrate how financial sector regulators are beginning to quantify financial system stress.

"This book presents a new System Dynamics model (the ERRE model), a novel stock and flow consistent global impact assessment model designed by the authors to address the financial risks emerging from the interaction between economic growth and environmental limits under the presence of shocks. Building on the World3-03 Limits to Growth model, the ERRE links the financial system with the energy, agriculture and climate systems through the real economy, by means of feedback loops, time lags and non-linear rationally bounded decision making. Prices and their interaction with growth, inflation and interest rates are assumed to be the main driver of economic failure while reaching planetary limits. The model allows for the stress-testing of fat tail extreme risk scenarios, such as climate shocks, energy transition, monetary policies and carbon taxes. Risks are addressed via scenario analyses, compared to real available data, and assessed in terms of the economic theory that lies behind. The book outlines the case for a government led system change within this decade, where the market alone cannot lead to sustainable prosperity. This book will be of great interest to scholars of climate change, behavioural, ecological and evolutionary economics, green finance, and sustainable development"--

This book offers an introduction to structural dynamics, ripple effect and resilience in supply chain disruption risk management for larger audiences. In the management section, without relying heavily on mathematical derivations, the book offers state-of-the-art concepts and methods to tackle supply chain disruption risks and designing resilient supply chains in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering background. In the technical section, the book constitutes structural dynamics control methods for supply chain management. Real-life problems are modelled and solved with the help of mathematical programming, discrete-event simulation, optimal control theory, and fuzzy logic. The book derives practical recommendations for management decision-making with disruption risk in the following areas: How to estimate the impact of possible disruptions on performance in the pro-active stage? How to generate efficient and effective stabilization and recovery policies? When does one failure trigger an adjacent set of failures? Which supply chain structures are particular sensitive to ripple effect? How to measure the disruption risks in the supply chain?

There are two types of tenn structure models in the literature: the equilibrium models and the no-arbitrage models. And there are, correspondingly, two types of interest rate derivatives pricing fonnulas based on each type of model of the tenn structure. The no-arbitrage models are characterized by the work of Ho and Lee (1986), Heath, Jarrow, and Morton (1992), Hull and White (1990 and 1993), and Black, Dennan and Toy (1990). Ho and Lee (1986) invent the no-arbitrage approach to the tenn structure modeling in the sense that the model tenn structure can fit the initial (observed) tenn structure of interest rates. There are a number of disadvantages with their model. First, the model describes the whole volatility structure by a sin gle parameter, implying a number of unrealistic features. Furthennore, the model does not incorporate mean reversion. Black-Dennan-Toy (1990) develop a model along tbe lines of Ho and Lee. They eliminate some of the problems of Ho and Lee (1986) but create a new one: for a certain specification of the volatility function, the short rate can be mean-fteeting rather than mean-reverting. Heath, Jarrow and Morton (1992) (HJM) construct a family of continuous models of the term struc ture consistent with the initial tenn structure data.

Based on the “Fourth International Conference on Dynamics of Disasters” (Kalamata, Greece, July 2019), this volume includes contributions from experts who share their latest discoveries on natural and unnatural disasters. Authors provide overviews of the tactical points involved in disaster relief, outlines of hurdles from mitigation and preparedness to response and recovery, and uses for mathematical models to describe natural and man-made disasters. Topics covered include economics, optimization, machine learning, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.