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Data sets were compiled from the MHIDAS data bank for incidents where there had been five or more fatalities, ten or more injuries, 50 evacuations, or US$1 million damage. The data were converted to magnitudes on the Bradford Disaster Scale and analysed using maximum likelihood. Parameters determined from the estimation procedures were compared for compatibility between themselves and the results of analyses using other data.

Examines attitudes to disasters in Arab countries and argues that they are frequently not reported and therefore not analysed in sufficient detail. Using data from the US Office of Foreign Disaster Assistance describes the types and frequency of natural disasters throughout the Arab world. Concentrates on drought as this is by far the largest cause of fatalities in the region. Outlines current policies regarding disaster prevention and management and concludes by suggesting ways in which the present situation could be improved.

Presents a method of analysis to obtain risk profiles for major adverse events. The method is based on a previously published method for probabilistically modelling historical data of past major accidents and disasters. Shows that insurable costs arising from such major events can be modelled using the two‐parameter Weibull distribution. Values of parameters obtained using different data sets are seen to be comparable in value. Discusses the relevance of this work to risk analysis and identifies areas of research requiring future development.

This chapter introduces the tourism–disaster–conflict nexus through a comprehensive review of the contemporary social science literature. After reviewing conceptual definitions of tourism, disaster and conflict, the chapter explores various axes that link through this nexus. The linkages between tourism and disaster include tourism as a trigger or amplifier of disasters, the impacts of disasters on the tourism industry, tourism as a driver of disaster recovery and disaster risk reduction strategies in the tourism sector. Linkages between tourism and conflict include the idea that tourism can be a force for peace and stability, the niche status of danger zone or dark heritage tourism, the concept of phoenix tourism in post-conflict destination rebranding, tourism and cultural conflicts, and tourism’s conflicts over land and resources. Linkages between disaster and conflict include disasters as triggers or intensifiers of civil conflict, disaster diplomacy and conflict resolution, disaster capitalism, and gender-based violence and intra-household conflict in the wake of disasters. These are some of the conversations that organise this volume, and this introductory chapter ends with a summary of the chapters that follow.

Proposes an optimal identification algorithm of time‐varying dynamic processes. Says it is based on applying a linear combination of the recursive least‐squares method equations. Posits that this scheme could be applied to identify and predict the ARMAX model of the on‐line desalting processes. Desalination technology is used to produce fresh water from saline sources. States that the results obtained give useful information on the physical considerations and desalting process efficiency.

Disasters are classified as natural and man‐made disasters. Man‐made disaster, which occurs at the major hazard installation, is a technological disaster. For an incident to be classified as technological disaster criteria are required to be met. Several criteria have been proposed by researchers and agencies defining the disasters in terms of casualties, economic loss and environmental impact. Few models have been drawn describing the sequence of development of the technological disaster. This paper reviews in detail the proposed criteria, which define the disaster. The paper also summarizes the models which describe the disaster stages. Finally the paper summarizes a proposed model of the technological disaster precondition phase for major accidents.

A disaster and a crisis are two different, and related events. The two terms are sometimes used interchangeably. Man‐made disaster that occurs at an industrial organization, may develop into an industrial crisis. Crisis can happen to any organization. It has been noted that there were no universally accepted definitions yet developed for disaster and crisis. There is also no universally available criteria, to define the disaster in terms of the consequences, such as the casualties and the cost of damage. This paper reviews the definitions, types, characteristics, criteria and models of disaster and crisis. Also the types of crisis were rearranged and the differences between the disasters and crises have been summarized.

The purpose of this paper is to construct a typology of a disaster that informs humanitarian-relief supply chain (HRSC) design across the stages of disaster relief.

In addition to an interdisciplinary review of pertinent literature, this paper utilises a typology construction method to propose theoretically and methodologically sound dimensions of disasters.

Whilst semantic arguments surrounding the concept of a “disaster” are ongoing, the authors propose three typologies based upon six dimensions that serve as interdependent variables informing resultant HRSC design considerations. These are speed of onset, time horizon, spatial considerations, affected population needs, perceived probability of occurrence and perceived magnitude of consequence. These combinational and independent relationships of the variables offer insight into key HRSC design-making considerations.

The study improves conceptual knowledge of disasters, distilling the concept to only the dimensions applicable to HRSC design, omitting other applications. The typologies provide empirical cell types based on extant literature, but do not apply the models towards new or future phenomena.

This paper provides HRSC practitioners with normative guidance through a more targeted approach to disaster relief, with a focus on the impacted system and resulting interactions’ correspondence to HRSC design.

This paper provides three typological models of disasters uniquely constructed for HRSC design across the various stages of disaster relief.

The paper defines Malta’s disaster risks parameter. Various data are given on Malta’s earthquake‐related hazards. By referring to mean damage ratios and death rates, earthquake losses are equated as a percentage of the gross domestic product, and the number of casualties and homeless estimated. Being a small island, the need for foreign help in the aftermath of a large disaster is analysed. Because of the present large number of vacant premises available, the amount of material foreign help required is minimized, as households could be evacuated to other regions of the Island. The above risks could further be minimized if Malta adopts strategic preparedness and mitigation management. Retrofitting of the present building stock is necessary, as is actively encouraging the purchase of disaster insurance, together with preparation of planning tools and strategic choices.

The purpose of this paper is to introduce a 3R (right time, right place, and right material) principle for characterizing failure in humanitarian/relief supply chains’ response to natural disasters, and describes a Bayesian methodology of the failure odds with regard to external factors that may affect the disaster-relief outcome, and distinctive supply chain proneness to failure.

The suggested 3Rs combine simplicity and completeness, enclosing all aspects of the 7R principle popular within business logistics. A fixed effects logistic regression model is designed, with a Bayesian approach, to relate the supply chains’ odds for success in disaster-relief to potential environmental predictors, while accounting for distinctive supply chains’ proneness to failure.

Analysis of simulated data demonstrate the model’s ability to distinguish relief supply chains with regards to their disaster-relief failure odds, taking into account pertinent external factors and supply chain idiosyncrasies.

Due to the complex nature of natural disasters and the scarcity of subsequent data, the paper employs computer-simulated data to illustrate the implementation of the proposed methodology.

The 3R principle offers a simple and familiar basis for evaluating failure in relief supply chains’ response to natural disasters. Also, it brings the issues of customer orientation within humanitarian relief and supply operations to the fore, which had only been implicit within the humanitarian and relief supply chain literature.