A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems

Barker, Kash; Santos, Joost R.

doi:10.1111/j.1539-6924.2010.01373.x

Cited by 55 publications

(23 citation statements)

References 23 publications

(43 reference statements)

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“…Conversely, the agriculture, mining, food, and textiles industries only lost $2.6 billion, of which $1.6 billion were direct production losses. As Barker and Santos (2010b) discuss, the breakdown of industry production losses can help policymakers determine the key sectors that are impacted by a disruption. The disruption in the Japanese automotive sector led to tens of billions of dollars of production losses in the service and manufacturing sectors.…”

Section: Data Representing Both Direct and Indirect Impactsmentioning

confidence: 99%

Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami

MacKenzie

Santos

Barker

2012

International Journal of Production Economics

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133

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Section: Data Representing Both Direct and Indirect Impactsmentioning

confidence: 99%

Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami

MacKenzie

Santos

Barker

2012

International Journal of Production Economics

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133

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“…Total production losses due to the disruption is given by x D c * . The IIM has been used to study a number of disruptions that concern policy makers including terrorist attacks (Haimes et al 2005), cyber security (Dynes et al 2007), workforce disruptions (Barker and Santos 2010), and waterway port closures (MacKenzie et al 2012a). …”

Section: Inoperability Input-output Modelmentioning

confidence: 99%

Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill

2014

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Determining where and when to invest resources during and after a disruption can challenge policy makers and homeland security officials. Two decision models, one static and one dynamic, are proposed to determine the optimal resource allocation to facilitate the recovery of impacted industries after a disruption where the objective is to minimize the production losses due to the disruption. This paper presents conditions for optimality for each model as a function of model parameters as well as an algorithm to solve for the optimal conditions in both models. Both models are applied to the Deepwater Horizon oil spill, which adversely impacted several industries in the Gulf region, such as fishing, tourism, real estate, and oil and gas. Results demonstrate the importance of allocating enough resources to stop the oil spill and clean up the oil, which reduces the economic loss across all industries. These models can be applied to different homeland security and disaster response situations to help governments and organizations decide among different resource allocation strategies during and after a disruption.

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“…and Rose . Other measures to strengthen resilience include the key sector analysis and inventory management . Geographic proximity to other economies may also reinforce an economy's resilience toward disasters .…”

Section: Risk Analysis Of Simultaneous Disruptions To Workforce and Imentioning

confidence: 99%

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

Santos

Herrera

et al. 2014

Risk Analysis

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The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.

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A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems

Cited by 55 publications

References 23 publications

Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami

Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami

Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

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