Predicting serial killers' home base using a decision support system

The effectiveness of a geographical decision support tool (Dragnet) for locating the base of serial offenders was compared across 570 models comprised of 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 it was found that the specially developed normalization parameter (QRange) produced the optimal search costs. The optimal search cost was also found to be for a function that did not include any buffer zone. The optimal, average search cost across the whole sample was 11% of the defined search area. Fifty-one percent of the offenders resided in the first 5% of the search area, with 87% in the first 25%. All resided in the total defined search area. These results support the potential for operational tools using such procedures as well as contributing to our understanding of criminal's geographical behavior. The applicability to other forms of serial crime is considered.