Most attacker-defender games consider players as risk neutral, whereas in reality attackers and defenders may be risk seeking or risk averse. This article studies the impact of players' risk preferences on their equilibrium behavior and its effect on the notion of deterrence. In particular, we study the effects of risk preferences in a single-period, sequential game where a defender has a continuous range of investment levels that could be strategically chosen to potentially deter an attack. This article presents analytic results related to the effect of attacker and defender risk preferences on the optimal defense effort level and their impact on the deterrence level. Numerical illustrations and some discussion of the effect of risk preferences on deterrence and the utility of using such a model are provided, as well as sensitivity analysis of continuous attack investment levels and uncertainty in the defender's beliefs about the attacker's risk preference. A key contribution of this article is the identification of specific scenarios in which the defender using a model that takes into account risk preferences would be better off than a defender using a traditional risk-neutral model. This study provides insights that could be used by policy analysts and decisionmakers involved in investment decisions in security and safety.

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This paper applies game theory and expected utility theory models to study the optimal public–private partnerships (PPPs) in disaster preparedness considering the uncertain consequences of the disasters, the investment costs, and the private sector’s potential risk attitudes, including risk-seeking behavior, risk aversion, and risk neutrality. We study the private sector’s best response and the subgame perfect Nash equilibrium solutions. Our results show that the public sector provides the least amount of subsidy to the risk-averse private sector and the highest amount of subsidy to the risk-seeking private sector. On the contrary, the risk-averse private sector invests the most, and the risk-seeking private sector invests the least. Finally, we validate the model results using a two-stage experiment with 91 participants. This paper provides insights into how to construct win–win PPPs in disaster preparedness with considerations of the private sector’s risk behavior.

The estimated cost of fire in the United States is about $329 billion a year, yet there are gaps in the literature to measure the effectiveness of investment and to allocate resources optimally in fire protection. This article fills these gaps by creating data‐driven empirical and theoretical models to study the effectiveness of nationwide fire protection investment in reducing economic and human losses. The regression between investment and loss vulnerability shows high R2 values (≈0.93). This article also contributes to the literature by modeling strategic (national‐level or state‐level) resource allocation (RA) for fire protection with equity‐efficiency trade‐off considerations, while existing literature focuses on operational‐level RA. This model and its numerical analyses provide techniques and insights to aid the strategic decision‐making process. The results from this model are used to calculate fire risk scores for various geographic regions, which can be used as an indicator of fire risk. A case study of federal fire grant allocation is used to validate and show the utility of the optimal RA model. The results also identify potential underinvestment and overinvestment in fire protection in certain regions. This article presents scenarios in which the model presented outperforms the existing RA scheme, when compared in terms of the correlation of resources allocated with actual number of fire incidents. This article provides some novel insights to policymakers and analysts in fire protection and safety that would help in mitigating economic costs and saving lives.