Crime Feeds on Legal Activities: Daily Mobility Flows Help to Explain Thieves’ Target Location Choices

Guangwen Song, Wim Bernasco, Lin Liu, Luzi Xiao, Suhong Zhou, Weiwei Liao

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Objective: According to routine activity theory and crime pattern theory, crime feeds on the legal routine activities of offenders and unguarded victims. Based on this assumption, the present study investigates whether daily mobility flows of the urban population help predict where individual thieves commit crimes. Methods: Geocoded tracks of mobile phones are used to estimate the intensity of population mobility between pairs of 1616 communities in a large city in China. Using data on 3436 police-recorded thefts from the person, we apply discrete choice models to assess whether mobility flows help explain where offenders go to perpetrate crime. Results: Accounting for the presence of crime generators and distance to the offender’s home location, we find that the stronger a community is connected by population flows to where the offender lives, the larger its probability of being targeted. Conclusions: The mobility flow measure is a useful addition to the estimated effects of distance and crime generators. It predicts the locations of thefts much better than the presence of crime generators does. However, it does not replace the role of distance, suggesting that offenders are more spatially restricted than others, or that even within their activity spaces they prefer to offend near their homes.

LanguageEnglish
JournalJournal of Quantitative Criminology
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint

Crime
offense
offender
Theft
larceny
Geographic Mapping
population migration
Cell Phones
Urban Population
urban population
Police
large city
Population
community
China
police
human being

Keywords

  • China
  • Crime location choice
  • Mobility
  • Routine activities
  • Theft from the person

Cite this

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title = "Crime Feeds on Legal Activities: Daily Mobility Flows Help to Explain Thieves’ Target Location Choices",
abstract = "Objective: According to routine activity theory and crime pattern theory, crime feeds on the legal routine activities of offenders and unguarded victims. Based on this assumption, the present study investigates whether daily mobility flows of the urban population help predict where individual thieves commit crimes. Methods: Geocoded tracks of mobile phones are used to estimate the intensity of population mobility between pairs of 1616 communities in a large city in China. Using data on 3436 police-recorded thefts from the person, we apply discrete choice models to assess whether mobility flows help explain where offenders go to perpetrate crime. Results: Accounting for the presence of crime generators and distance to the offender’s home location, we find that the stronger a community is connected by population flows to where the offender lives, the larger its probability of being targeted. Conclusions: The mobility flow measure is a useful addition to the estimated effects of distance and crime generators. It predicts the locations of thefts much better than the presence of crime generators does. However, it does not replace the role of distance, suggesting that offenders are more spatially restricted than others, or that even within their activity spaces they prefer to offend near their homes.",
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author = "Guangwen Song and Wim Bernasco and Lin Liu and Luzi Xiao and Suhong Zhou and Weiwei Liao",
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Crime Feeds on Legal Activities : Daily Mobility Flows Help to Explain Thieves’ Target Location Choices. / Song, Guangwen; Bernasco, Wim; Liu, Lin; Xiao, Luzi; Zhou, Suhong; Liao, Weiwei.

In: Journal of Quantitative Criminology, 01.01.2019.

Research output: Contribution to JournalArticleAcademicpeer-review

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AU - Bernasco, Wim

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AU - Xiao, Luzi

AU - Zhou, Suhong

AU - Liao, Weiwei

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Objective: According to routine activity theory and crime pattern theory, crime feeds on the legal routine activities of offenders and unguarded victims. Based on this assumption, the present study investigates whether daily mobility flows of the urban population help predict where individual thieves commit crimes. Methods: Geocoded tracks of mobile phones are used to estimate the intensity of population mobility between pairs of 1616 communities in a large city in China. Using data on 3436 police-recorded thefts from the person, we apply discrete choice models to assess whether mobility flows help explain where offenders go to perpetrate crime. Results: Accounting for the presence of crime generators and distance to the offender’s home location, we find that the stronger a community is connected by population flows to where the offender lives, the larger its probability of being targeted. Conclusions: The mobility flow measure is a useful addition to the estimated effects of distance and crime generators. It predicts the locations of thefts much better than the presence of crime generators does. However, it does not replace the role of distance, suggesting that offenders are more spatially restricted than others, or that even within their activity spaces they prefer to offend near their homes.

AB - Objective: According to routine activity theory and crime pattern theory, crime feeds on the legal routine activities of offenders and unguarded victims. Based on this assumption, the present study investigates whether daily mobility flows of the urban population help predict where individual thieves commit crimes. Methods: Geocoded tracks of mobile phones are used to estimate the intensity of population mobility between pairs of 1616 communities in a large city in China. Using data on 3436 police-recorded thefts from the person, we apply discrete choice models to assess whether mobility flows help explain where offenders go to perpetrate crime. Results: Accounting for the presence of crime generators and distance to the offender’s home location, we find that the stronger a community is connected by population flows to where the offender lives, the larger its probability of being targeted. Conclusions: The mobility flow measure is a useful addition to the estimated effects of distance and crime generators. It predicts the locations of thefts much better than the presence of crime generators does. However, it does not replace the role of distance, suggesting that offenders are more spatially restricted than others, or that even within their activity spaces they prefer to offend near their homes.

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