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.

Original languageEnglish
Pages (from-to)831-854
Number of pages24
JournalJournal of Quantitative Criminology
Volume35
Issue number4
DOIs
Publication statusPublished - Dec 2019

Keywords

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

Fingerprint Dive into the research topics of 'Crime Feeds on Legal Activities: Daily Mobility Flows Help to Explain Thieves’ Target Location Choices'. Together they form a unique fingerprint.

Cite this