LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A multi-attribute approach to assess homeland security risk

Photo from wikipedia

The United States Department of Homeland Security manages a wide spectrum of risks involving crime, terrorism, accidents, and natural disasters. This paper supports disaster management by identifying which attributes should… Click to show full abstract

The United States Department of Homeland Security manages a wide spectrum of risks involving crime, terrorism, accidents, and natural disasters. This paper supports disaster management by identifying which attributes should be used to describe risks comprehensively and assessing the need to incorporate such multiattribute information into risk management processes. Attributes for describing homeland security risks were selected through a literature review. These attributes were then used in a risk assessment of homeland security hazards that informed risk ranking sessions conducted with members of the general public. The results taken together support the use of a range of attributes and perspectives. While aspects of life/health and economic damage were considered most important by both experts and the lay public, other attributes were of widespread importance, including attributes related to dread and uncertainty. These results demonstrate how to present risks in a deliberative risk management process and the importance of doing so using a complete set of attributes to describe the risks.

Keywords: attribute approach; risk; homeland security; approach assess; multi attribute

Journal Title: Journal of Risk Research
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.