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Predicting Serial Killers' Home Base Using a Decision Support System

NCJ Number
186958
Journal
Journal of Quantitative Criminology Volume: 16 Issue: 4 Dated: December 2000 Pages: 457-478
Author(s)
David Canter; Toby Coffey; Malcolm Huntley; Christopher Missen
Date Published
December 2000
Length
22 pages
Annotation
This study describes predicting serial killers' home bases using a decision support system.
Abstract
The study compared the effectiveness of a geographical decision support tool (Dragnet) for locating the base of serial offenders. The study included 570 models displaying a range of negative exponential functions, buffer zone components, and normalization parameters. The models were applied to the body disposal locations within each series for 70 U.S. serial killers. Two normalization parameters were compared for all functions. The test of effectiveness was a specifically defined measure of search cost. When applied to the Dragnet predictions, the specially developed normalization parameter (QRange) produced the optimal search costs. The optimal, average search cost across the whole sample was 11 percent of the defined search area. Fifty-one percent of the offenders resided in the first 5 percent of the search area, with 87 percent in the first 25 percent. All resided in the total defined search area. Study results support the potential for operational tools using such procedures as well as contributing to an understanding of criminals' geographical behavior. Note, figures, references