Predicting serial killers' home base using a decision support system

The effectiveness of a geographical decision support tool (Dragnet) for loc ating 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 loca tions within each series for 70 U.S. serial killers. Two normalization para meters were compared for all functions. The test of effectiveness was a spe cifically defined measure of search cost. When applied to the Dragnet predi ctions it was found that the specially developed normalization parameter (Q Range) 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 optima l, average search cost across the whole sample was 11% of the defined searc h area. Fifty-one percent of the offenders resided in the first 5% of the s earch area, with 87% in the first 25%. All resided in the total defined sea rch area. These results support the potential for operational tools using s uch procedures as well as contributing to our understanding of criminal's g eographical behavior. The applicability to other forms of serial crime is c onsidered.