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Risky places: An analysis of carjackings in Detroit

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  • Lersch, Kim Michelle

Abstract

The purpose of this research is to apply Risk Terrain Modeling (RTM) to identify spatial indicators that may place citizens at higher risk for carjackings in the City of Detroit, Michigan, USA. While a number of risk factors were tested, the RTM Diagnostic utility identified six that were influential in the best fitting model: proximity to service stations; convenience/grocery/liquor stores; bus stops; residential and commercial demolitions; and areas with high concentrations of drug arrests and restaurants. These factors resulted in relative risk scores that ranged from 1 for the lowest risk areas to 278 for the highest risk areas. This implied that certain locations had an expected rate of carjacking that was 278 times higher than other locations.

Suggested Citation

  • Lersch, Kim Michelle, 2017. "Risky places: An analysis of carjackings in Detroit," Journal of Criminal Justice, Elsevier, vol. 52(C), pages 34-40.
    • Handle: RePEc:eee:jcjust:v:52:y:2017:i:c:p:34-40
    DOI: 10.1016/j.jcrimjus.2017.07.011
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    Citations

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    Cited by:

    1. Connealy, Nathan T. & Piza, Eric L., 2019. "Risk factor and high-risk place variations across different robbery targets in Denver, Colorado," Journal of Criminal Justice, Elsevier, vol. 60(C), pages 47-56.
    2. Valasik, Matthew, 2018. "Gang violence predictability: Using risk terrain modeling to study gang homicides and gang assaults in East Los Angeles," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 10-21.
    3. Thomas, Shaun A. & Drawve, Grant, 2018. "Examining interactive effects of characteristics of the social and physical environment on aggravated assault," Journal of Criminal Justice, Elsevier, vol. 57(C), pages 89-98.
    4. Jacobs, Bruce A. & Cherbonneau, Michael, 2019. "Carjacking and the management of natural surveillance," Journal of Criminal Justice, Elsevier, vol. 61(C), pages 40-47.
    5. Yunmi Park & Minju Kim & Kijin Seong, 2021. "Happy neighborhoods: Investigating neighborhood conditions and sentiments of a shrinking city with Twitter data," Growth and Change, Wiley Blackwell, vol. 52(1), pages 539-566, March.
    6. Piza, Eric L. & Gilchrist, Andrew M., 2018. "Measuring the effect heterogeneity of police enforcement actions across spatial contexts," Journal of Criminal Justice, Elsevier, vol. 54(C), pages 76-87.

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