Applications and Modelling Using Multi-Attribute Decision Making to Rank Terrorist Threats
Journal of Socialomics
Keywords: Terrorist threats; Multi-attribute decision making; Analytical hierarchy process; Technique of order preference by similarity to ideal solution; Sensitivity analysis Data Envelopment Analysis (DEA) Description and uses Data envelopment analysis (DEA) is a relatively new "data inputoutput driven" approach for evaluating the performance of entities called decision making units (DMUs) that convert multiple inputs into multiple outputs  . The definition of a DMU is generic and very
... ible. It has been used to evaluate both the performance or efficiencies of hospitals, schools, departments, US Air Force wings, US armed forces recruiting agencies, universities, cities, courts, businesses, banking facilities, countries, regions, and the list go on. According to Cooper , DEA has been used to gain insights into activities that were not obtained by other quantitative or qualitative methods. Charnes et al.  , described DEA as a mathematical programming model applied to observational data, providing a new way of obtaining empirical estimates of relations. It is formally defined as a methodology directed to frontiers rather than central tendencies. Abstract In this paper we will examine a threat risk assessment process and modelling methodology that could be used by local law enforcement, homeland security, or military units to examine possible terrorist threats. We provide examples from a risk assessment process and a dark network. We apply different multi-attribute schemes to the threats. We also apply sensitivity analysis to the methods. Citation: Fox WP (2016) Applications and Modelling Using Multi-Attribute Decision Making to Rank Terrorist Threats. J Socialomics 5: 162. JSC, an open access journal Each method has its pros and cons. However, sensitivity analysis is critical to see how the ranking changes due to changes in the criteria weights.