TY - JOUR
T1 - Crime Feeds on Legal Activities
T2 - Daily Mobility Flows Help to Explain Thieves’ Target Location Choices
AU - Song, Guangwen
AU - Bernasco, Wim
AU - Liu, Lin
AU - Xiao, Luzi
AU - Zhou, Suhong
AU - Liao, Weiwei
PY - 2019/12
Y1 - 2019/12
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.
KW - China
KW - Crime location choice
KW - Mobility
KW - Routine activities
KW - Theft from the person
UR - http://www.scopus.com/inward/record.url?scp=85061498104&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061498104&partnerID=8YFLogxK
U2 - 10.1007/s10940-019-09406-z
DO - 10.1007/s10940-019-09406-z
M3 - Article
AN - SCOPUS:85061498104
SN - 0748-4518
VL - 35
SP - 831
EP - 854
JO - Journal of Quantitative Criminology
JF - Journal of Quantitative Criminology
IS - 4
ER -