Behavioural case linkage (BCL) is a procedure that can be used to identify linked crime series, which contain two or more crimes committed by the same person, thereby helping the police to detect and prosecute repeat offenders who are responsible for a disproportionate amount of crime. However, despite the potential benefits of BCL, there are also damaging consequences if crimes are incorrectly linked. Consequently, research has started to test if and how this procedure can work in the most efficient and reliable way. But, the extant literature has a number of important limitations, particularly in terms of (1) generalisability (i.e., there have been few attempts to replicate findings across geographical locations and time periods), (2) ecological validity (i.e., the methodology used to test BCL is not representative of how the procedure is used in practice), and (3) methodology (i.e., there is a lack of research to systematically compare the various methodological/statistical approaches to BCL). The primary aim of this thesis was to address these three important limitations. In terms of generalisability, this thesis has tested the extent to which previous BCL research on residential burglary, commercial robbery, and car theft can be replicated in new geographical locations and time periods. In terms of ecological validity, a number of new methodologies have been developed and tested that reduce the gap between research and practice in BCL by allowing both non-serial and unsolved offences (as well as solved, serial offences) to be included when testing the principles of BCL, and also for these principles to be tested with crime series that contain several different types of offence. In terms of methodology, novel methodological approaches have been compared with the ‘traditional’, status quo methodology for researching the BCL principles, thereby ensuring that the findings reported in this thesis can be compared with previous work. This thesis, therefore, has important implications for theory, research, and practice and the findings are discussed in the context of these. Future research directions are also outlined.

Law enforcement agencies regularly collect crime scene information. There exists, however, no detailed, systematic procedure for this. The data collected is affected by the experience or current condition of law enforcement officers. Consequently, the data collected might differ vastly between crime scenes. This is especially problematic when investigating volume crimes. Law enforcement officers regularly do manual comparison on crimes based on the collected data. This is a time-consuming process; especially as the collected crime scene information might not always be comparable. The structuring of data and introduction of automatic comparison systems could benefit the investigation process. This thesis investigates descriptive and predictive models for automatic comparison of crime scene data with the purpose of aiding law enforcement investigations. The thesis first investigates predictive and descriptive methods, with a focus on data structuring, comparison, and evaluation of methods. The knowledge is then applied to the domain of crime scene analysis, with a focus on detecting serial residential burglaries. This thesis introduces a procedure for systematic collection of crime scene information. The thesis also investigates impact and relationship between crime scene characteristics and how to evaluate the descriptive model results. The results suggest that the use of descriptive and predictive models can provide feedback for crime scene analysis that allows a more effective use of law enforcement resources. Using descriptive models based on crime characteristics, including Modus Operandi, allows law enforcement agents to filter cases intelligently. Further, by estimating the link probability between cases, law enforcement agents can focus on cases with higher link likelihood. This would allow a more effective use of law enforcement resources, potentially allowing an increase in clear-up rates.

Geographic profiling is a technique used by crime investigators and the police to examine the locations of a connected series of crimes, to determine the most probable area of the offender’s residence. Using both qualitative and quantitative methods, Geographic profiling helps to better interpret the spatial behavior of an offender and focuses the investigation on a specific and smaller area of the community. From the abovementioned and from previous research, we know that Geographic profiling is useful in serial crimes such as in cases of serial murderers, serial rapists etc. Having as a point of reference Malmö, because of the many shooting incidents that have happened through the last years, in this master thesis dissertation, a systematic literature review on Geographic Profiling was conducted while at the same time the usefulness of the method in locating the serial murderers was examined.