Building better crime simulations: systematic replication and the introduction of incremental complexity

Computer simulation models have changed the ways in which researchers are able to observe and study social phenomena such as crime. The ability of researchers to replicate the work of others is fundamental to a cumulative science, yet this rarely occurs in computer simulations. In this paper, we argue that, for computer simulations to be seen as a legitimate methodology in social science, and for new knowledge to be generated, serious consideration needs to be given to how simulations could or should be replicated. We develop the concept of systematic replication, a method for developing simulation experiments that move towards a generalisable inference that is directed, explicit, and incorporates complexity incrementally. Finally, we outline how the discrete parts of this process might be carried out in practice, using a simple simulation model.

Daniel J. BirksEmail:

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Michael Townsley   is a lecturer in the School of Criminology and Criminal Justice, Griffith University. Before this he was a Senior Research Fellow at the University College London (UCL) Jill Dando Institute of Crime Science, University College London. He trained as a statistician, and his research has focused on crime analysis, problem-orientated policing and quantitative methods in a criminal justice setting, all with a view to preventing crime. His current research projects include the spatial and temporal modelling of crime and the analysis of large novel data sets. Daniel Birks   is a Research Fellow at the UCL Jill Dando Institute of Crime Science. He has worked on a number of crime prevention research projects in conjunction with the Home Office and several police forces in the UK. His research interests include the development of innovative crime analysis and decision support techniques and tools, prospective models of crime, the application of simulation techniques within criminology, the study of offender predation patterns, and the use of data mining in crime analysis.