Marcus Wiens

A new focus on risk reduction: an ad hoc decision support system for humanitarian relief logistics

Abstract Particularly in the early phases of a disaster, logistical decisions are needed to be made quickly and under high pressure for the decision‐makers, knowing that their decisions may have direct consequences on the affected society and all future decisions. Proactive risk reduction may be helpful in providing decision‐makers with optimal strategies in advance. However, disasters are characterized by severe uncertainty and complexity, limited knowledge about the causes of the disaster, and continuous change of the situation in unpredicted ways. Following these assumptions, we believe that adequate proactive risk reduction measures are not practical. We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted. Therefore, we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options. By combining these aspects in a dynamic manner and integrating new information continuously, it can be ensured that a decision is always based on the best currently available and processed information. And finally, to identify a robust decision option that is provided as a decision recommendation to the decision‐makers, methods of multi‐attribute decision making (MADM) are applied. Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.

A game-theoretic approach to assess adversarial risks

In our complex world today almost all critical infrastructures are interdependent and thus vulnerable to many different external and internal risks. To protect them against the greatest risks, a well-functioning risk management process is required to develop appropriate safety and security strategies. There are many wellestablished risk analysis methods existing. They predominantly apply empirical models and statistical data to quantify the risks. Within the realms of natural or aleatory risks this approach is considered suitable and functional. However, it could be a fatal flaw to apply such conventional, history-orientated models in order to assess risks that arise from intelligent adversaries such as terrorists, criminals or competitors. Approaches of classic risk analysis generally describe adversaries’ choices as random variables, thus excluding the adversaries’ behaviour and ability to adapt to security strategies. One possibility for considering human behaviour when analysing risks is the recourse to game theory. Game theory is the paradigmatic framework for strategic decision-making when two or more rational decision-makers (intelligent adversaries) are involved in cooperative or conflictive decision situations. In our study we propose an approach for combining a classic risk analysis method with a game-theoretic approach. Using a defenderoffender game as a basis, we simulate, exemplary for a terrorist attack against public transport, the behaviour and reactions (to applied security strategies of the defender) of a rational player acting as an adversary. Although risk analysis and game theory are very different methodologies, we show that linking them can significantly improve the quality of forecasts and risk assessments. If the behaviour and reactions of intelligent adversaries need to be considered, our approach contributes to enhance security through improving the allocation of scarce financial resources.

Collaborative Emergency Supply Chains for Essential Goods and Services

Focal actors in disaster relief logistics are predominantly public authorities, emergency organizations, and NGOs, whereas private firms rather play a subordinate role—at least in the context of direct crisis intervention. Although it is entirely clear that engaging in public crisis management is not among the original tasks of commercial firms there is a substantial—and so far still unexploited—potential for public–private cooperation in a disaster situation. In this contribution, we outline the scope of a Public–Private Emergency Collaboration (PPEC) with a focus on the provision of essential goods and services. We discuss the different objectives and strategies of the partners and evaluate the potential for a PPEC for each phase of a disaster from an economic perspective with a primary focus on logistics operations. Based on a simple model, we identify the chance to improve crisis management operations by information sharing and coordinated allocation of resources and capacities for both the escalating and de-escalating phase of a disaster. Interestingly, a PPEC can also help to overcome public acceptance problems which could be occasionally observed in historic disasters. As key requirements of a PPEC, we identify a clear allocation of responsibilities between the public and the private partners together with sufficient incentives for commercial firms to engage in a PPEC on a sustainable basis.

Strategic Deterrence of Terrorist Attacks

Protection against terrorist threats has become an integral part of organisational and national security strategies. But research on adversarial risks is still dominated by approaches which focus too much on historical frequencies and which do not sufficiently account for the terrorists motives and the strategic component of the interaction. In this paper we model the classical risk analysis approach using a specific variant of adaptive play and compare it with a direct implementation approach. We find that the latter allows for a more purposeful use of security measures as defenders avoid to get caught in a “hare-tortoise-trap”. We specify the conditions under which the direct implementation outperforms adaptive play in the sense that it lowers the cost of defence at a given rate of deterrence. We analyse the robustness of our results and discuss the implications and requirements for practical application.

Understanding Resilience: A Spatio-temporal Vulnerability Assessment of a Population Affected by a Sudden Lack of Food

Natural disasters such as massive floods and severe storms can lead to disorganizations of the food supply chain. A cutoff of the food supply chain is a worst case scenario in which the population is not able to buy food in stores for a couple of days. In this situation, the private food stock in households is the key self-helping capacity to cope with the effects of a sudden lack of food. In this paper a spatio-temporal vulnerability model is introduced to facilitate disaster preparedness and to enhance the understanding of resilience of the population in Germany. The model is indicator-based and uses the empirical data about the stock piling behavior of the population, statistical data about the population structure of different city districts, and the results of an expert survey to estimate the time-dependent vulnerability of a population derived from the continuous consumption of their private food stock. The paper includes a review about studies recently published about the empirical quantifications of food stocks in households in Germany and an evaluation of the expert survey. The model was applied to two cases of German cities to demonstrate and discuss its benefits.