The strongest does not attract all but it does attract the most – evaluating the criminal attractiveness of shopping malls using fuzzy logic

Authors

  • Vijay K. Mago,

    1. The Modelling of Complex Social Systems (MoCSSy) Program, The IRMACS Centre, Burnaby, Canada
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  • Richard Frank,

    1. The Modelling of Complex Social Systems (MoCSSy) Program, The IRMACS Centre, Burnaby, Canada
    2. Institute for Canadian Urban Research Studies (ICURS), School of Criminology, Simon Fraser University, Burnaby, Canada
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  • Andrew Reid,

    1. The Modelling of Complex Social Systems (MoCSSy) Program, The IRMACS Centre, Burnaby, Canada
    2. Institute for Canadian Urban Research Studies (ICURS), School of Criminology, Simon Fraser University, Burnaby, Canada
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  • Vahid Dabbaghian

    1. The Modelling of Complex Social Systems (MoCSSy) Program, The IRMACS Centre, Burnaby, Canada
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Abstract

Crime attractors are locations (e.g. shopping malls) that attract criminally motivated offenders because of the presence of known criminal opportunities. Although there have been many studies that explore the patterns of crime in and around these locations, there are still many questions that linger. In recent years, there has been a growing interest to develop mathematical models in attempts to help answer questions about various criminological phenomena. In this paper, we are interested in applying a formal methodology to model the relative attractiveness of crime attractor locations based on characteristics of offenders and the crime they committed. To accomplish this task, we adopt fuzzy logic techniques to calculate the attractiveness of crime attractors in three suburban cities in the Metro Vancouver region of British Columbia, Canada. The fuzzy logic techniques provide results comparable with our real-life expectations that offenders do not necessarily commit significant crimes in the immediate neighbourhood of the attractors, but travel towards it, and commit crimes on the way. The results of this study could lead to a variety of crime prevention benefits and urban planning strategies.

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