The Influence of Activity Space and Visiting Frequency on Crime Location Choice: Findings from an Online Self-Report Survey

Menting, Barbara; Lammers, Marloes; Ruiter, Stijn; Bernasco, Wim

doi:10.1093/bjc/azz044

Cited by 22 publications

(59 citation statements)

References 18 publications

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“…they are in their activity or awareness spaces. The studies that were performed using the data on detected residential burglaries unanimously agree that areas that are close to the offender's home are more likely to be targeted (Bernasco and Nieuwbeerta, ; Townsley et al ., ; Menting et al ., ; Clare et al ., ). In the study based on a survey of offenders, Menting et al .…”

Section: Application: London Burglary Crimementioning

confidence: 99%

“…In the study based on a survey of offenders, Menting et al . () argued that other awareness spaces than their residence play a significant role in target selection. These include previous addresses and neighbourhoods of their family and friends, as well as places where they work and go about their recreation and leisure.…”

Section: Application: London Burglary Crimementioning

confidence: 99%

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Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes

Povala

Virtanen

Girolami

2020

Journal of the Royal Statistical Society Series C: Applied Statistics

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To obtain operational insights regarding the crime of burglary in London, we consider the estimation of the effects of covariates on the intensity of spatial point patterns. Inspired by localized properties of criminal behaviour, we propose a spatial extension to mixtures of generalized linear models from the mixture modelling literature. The Bayesian model proposed is a finite mixture of Poisson generalized linear models such that each location is probabilistically assigned to one of the groups. Each group is characterized by the regression coefficients, which we subsequently use to interpret the localized effects of the covariates. By using a blocks structure of the study region, our approach enables specifying spatial dependence between nearby locations. We estimate the proposed model by using Markov chain Monte Carlo methods and we provide a Python implementation.

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Section: Application: London Burglary Crimementioning

confidence: 99%

Section: Application: London Burglary Crimementioning

confidence: 99%

Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes

Povala

Virtanen

Girolami

2020

Journal of the Royal Statistical Society Series C: Applied Statistics

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“…Studies using Discrete Spatial Choice Modelling (DSCM) have even quantified the increase in odds of a location being chosen based on its proximity to offenders' previous addresses, their family members' current or previous addresses, and the locations of their previous crimes, when controlling for proximity to their home [3,9,[23][24][25][26]. Two further DSCM studies, both on young offenders, incorporated additional types of activity nodes to confirm that the odds of crime increase with proximity to any activity node [27,28].…”

Section: Offenders' Activity Spacesmentioning

confidence: 99%

A National Examination of the Spatial Extent and Similarity of Offenders’ Activity Spaces Using Police Data

Curtis‐Ham

Bernasco

Medvedev

et al. 2021

IJGI

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It is well established that offenders’ routine activity locations (nodes) shape their crime locations, but research examining the geography of offenders’ routine activity spaces has to date largely been limited to a few core nodes such as homes and prior offense locations, and to small study areas. This paper explores the utility of police data to provide novel insights into the spatial extent of, and overlap between, individual offenders’ activity spaces. It includes a wider set of activity nodes (including relatives’ homes, schools, and non-crime incidents) and broadens the geographical scale to a national level, by comparison to previous studies. Using a police dataset including n = 60,229 burglary, robbery, and extra-familial sex offenders in New Zealand, a wide range of activity nodes were present for most burglary and robbery offenders, but fewer for sex offenders, reflecting sparser histories of police contact. In a novel test of the criminal profiling assumptions of homology and differentiation in a spatial context, we find that those who offend in nearby locations tend to share more activity space than those who offend further apart. However, in finding many offenders’ activity spaces span wide geographic distances, we highlight challenges for crime location choice research and geographic profiling practice.

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“…A burgeoning body of empirical research has indeed shown that offenders are very consistent in where they commit offenses. Building on crime pattern theory, previous studies have shown that characteristics of offenders' activity spaces, such as their routinely visited places, the distance from their homes to the crime locations, and travel direction from home are all associated with where they commit crime (e.g., Menting et al 2019;Townsley and Sidebottom 2010;Van Daele and Bernasco 2012).…”

Section: Introductionmentioning

confidence: 99%

When Do Offenders Commit Crime? An Analysis of Temporal Consistency in Individual Offending Patterns

2020

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Objectives Building on Hägerstrand's time geography, we expect temporal consistency in individual offending behavior. We hypothesize that repeat offenders commit offenses at similar times of day and week. In addition, we expect stronger temporal consistency for crimes of the same type and for crimes committed within a shorter time span. Method We use police-recorded crime data on 28,274 repeat offenders who committed 152,180 offenses between 1996 and 2009 in the greater The Hague area in the Netherlands. We use a Monte Carlo permutation procedure to compare the overall level of temporal consistency observed in the data to the temporal consistency that is to be expected given the overall temporal distribution of crime. Results Repeat offenders show strong temporal consistency: they commit their crimes at more similar hours of day and week than expected. Moreover, the observed temporal consistency patterns are indeed stronger for offenses of the same type of crime and when less time has elapsed between the offenses, especially for offenses committed within a month after the prior offense. Discussion The results are consistent with offenders having recurring rhythms that shape their temporal crime pattern. These findings might prove valuable for improving predictive policing methods and crime linkage analysis as well as interventions to reduce recidivism.

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The Influence of Activity Space and Visiting Frequency on Crime Location Choice: Findings from an Online Self-Report Survey

Cited by 22 publications

References 18 publications

Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes

Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes

A National Examination of the Spatial Extent and Similarity of Offenders’ Activity Spaces Using Police Data

When Do Offenders Commit Crime? An Analysis of Temporal Consistency in Individual Offending Patterns

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