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New insights on relationships between street crimes and ambient population: Use of hourly population data estimated from mobile phone users’ locations

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  • Kazumasa Hanaoka

Abstract

The purpose of this research is to examine relationships between occurrences of snatch-and-run offences and hourly population estimated from mobile phone users’ locations, with particular focus on differences between daytime and nighttime. Using an hourly population dataset allows us to count the so-called ‘ambient population’ by hour of day to accurately quantify the influence of such population as capable guardians and suitable targets in a framework of routine activity theory. Our major findings based on logistic regression models are that (1) the effects of ambient population and (2) its temporal change are large, and the effects differ between daytime and nighttime. During the daytime, snatch-and-run offences are less likely to occur in areas where hourly population density is expect to increase, possibly because offenders are highly sensitive to the risk of being detected by other people. On the other hand, offences at night occur even in relatively crowded areas, and they are only weakly related to population change. In addition, our study found that (3) snatch-and-run offences are more likely to occur in or near local town centres and (4) socially vulnerable neighbourhoods are only targeted at night. We attempted to explain this in terms of offenders’ characteristics and motivations depending on time of day.

Suggested Citation

  • Kazumasa Hanaoka, 2018. "New insights on relationships between street crimes and ambient population: Use of hourly population data estimated from mobile phone users’ locations," Environment and Planning B, , vol. 45(2), pages 295-311, March.
  • Handle: RePEc:sae:envirb:v:45:y:2018:i:2:p:295-311
    DOI: 10.1177/0265813516672454
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    References listed on IDEAS

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    1. Wim Bernasco & Richard Block & Stijn Ruiter, 2013. "Go where the money is: modeling street robbers' location choices," Journal of Economic Geography, Oxford University Press, vol. 13(1), pages 119-143, January.
    2. Baasch, David M. & Tyre, Andrew J. & Millspaugh, Joshua J. & Hygnstrom, Scott E. & Vercauteren, Kurt C., 2010. "An evaluation of three statistical methods used to model resource selection," Ecological Modelling, Elsevier, vol. 221(4), pages 565-574.
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