Does the Association Between Flows of People and Crime Differ Across Crime Types in Sweden?

Places with persistently high levels of crime, hot spots, are an important object of study. To some extent, the high levels of crime at such hot spots are likely to be related to flows of people. City center locations with large flows of people are quite often also hot spots, e.g., hot spots for pick pocketing at a central train station, or hot spots for assault in the nightlife district. This can be related to crime pattern theory, or to the routine activity perspective, which both suggest that flows of people can affect crime. The present study attempts to explore and quantify whether there are differences in the association between flows of people and crime for different crime types. The analysis considers locations with high crime counts for six crime types in the city of Malmö, Sweden. For each crime type, hot spots are identified and mapped, and in order to explore whether, or how, these are related to flows of people, the crime levels are then analyzed in relation to the number of people who boarded a local bus (N = 33,134,198) nearby. The paper shows that all six crime types are associated with flows of people, although less so for arson and vandalism. This is hypothesized to be due to the relatively constant target availability for these crimes as opposed to the other crime types studied.

Right place, right time? Making crime pattern theory time-specific

Objectives Crime pattern theory and the related empirical research have remained rather a-temporal, as if the timing of routine activities and crime plays no role. Building on previous geography of crime research, we extend crime pattern theory and propose that an offender’s spatial knowledge acquired during daily routine activities is not equally applicable to all times of day. Methods We put this extended theory to a first empirical test by applying a discrete spatial choice model to detailed information from the Netherlands on 71 offences committed by 30 offenders collected through a unique online survey instrument. The offenders reported on their most important activity nodes and offence locations over the past year, as well as the specific times they regularly visited these locations. Results The results show that almost 40% of the offences are committed within the neighbourhoods of offenders’ activity nodes, increasing to 85% when including first-, second- and third-order neighbourhoods. Though not statistically significant in our small sample, the results further suggest that offenders are more likely to commit crime in neighbourhoods they have regularly visited at the same time of day than in neighbourhoods they have regularly visited at different times of day. Conclusion Our extension of crime pattern theory is only tentatively supported. We argue for replication research with larger samples before any firm conclusions are warranted.

Crime Pattern Theory

A broad understanding of crime requires explanations for both the origins of individual and group criminal propensity and when and where criminal events occur. Crime pattern theory provides explanations for the variation in the distribution of criminal events in space and time given a range of different propensities. In the organization of their everyday lives, both occasional and persistent criminals spend most of their time engaged in the same legitimate everyday activities as everyone else. The location of criminal events in space–time are shaped by these everyday activities and the specific criminal’s activity. Occasional and persistent offenders develop activity spaces and awareness spaces. The shape and dynamics of these spaces is influenced by the structures of human settlements that channel and limit movement patterns in time and space. These structures include the built environments and the socioeconomic and cultural environments in which people live, work, or go to school, and in which they spend their social, entertainment, and shopping time. Crime pattern theory utilizes the major components of the built and social environment—activity nodes, paths between nodes, neighborhoods and neighborhood edges, and the socioeconomic backcloth—in conjunction with the routine movements of the population in general to understand crime generator and crime attractor locations and the formation of repeat areas of offending for individuals and groups of offenders as well as more aggregate crime hot spots and cold spots. This information is translated into a geometry of crime that describes the journeys to crime by individual criminal offenders and groups of offenders and their victims or targets. Crime pattern theory explains the process of criminal target search, suggests strategies for crime reduction, and describes potential displacements of criminal events in space and time following changes in the suitability of targets or target locations at particular places and specific times.

A framework for estimating crime location choice based on awareness space

This paper extends Crime Pattern Theory, proposing a theoretical framework which aims to explain how offenders’ previous routine activity locations influence their future offence locations. The framework draws on studies of individual level crime location choice and location choice in non-criminal contexts, to identify attributes of prior activities associated with the selection of the location for future crime. We group these attributes into two proposed mechanisms: reliability and relevance. Offenders are more likely to commit crime where they have reliable knowledge that is relevant to the particular crime. The perceived reliability of offenders’ knowledge about a potential crime location is affected by the frequency, recency and duration of their prior activities in that location. Relevance reflects knowledge of a potential crime location’s crime opportunities and is affected by the type of behaviour, type of location and timing of prior activities in that location. We apply the framework to generate testable hypotheses to guide future studies of crime location choice and suggest directions for further theoretical and empirical work. Understanding crime location choice using this framework could also help inform policing investigations and crime prevention strategies.

Does the association between flows of people and crime differ across crime types in Sweden?

Places with persistently high levels of crime, hot spots, are an important object of study. To some extent the high levels of crime at such hot spots are likely to be related to flows of people. City center locations with large flows of people are quite often also hot spots, e.g. hot spots for pick pocketing at a central train station, or hot spots for assault in the nightlife district. This can be related to crime pattern theory, or to the routine activity perspective, which both suggest that flows of people can affect crime. The present study attempts to explore and quantify whether there are differences in the association between flows of people and crime for different crime types. The analysis considers locations with high crime counts for six crime types in the city of Malmö, Sweden. For each crime type, hot spots are identified and mapped, and in order to explore whether, or how, these are related to flows of people, the crime levels are then analyzed in relation to the number of people who boarded a local bus (N=33,134,198) nearby. The paper shows that all six crime types are associated with flows of people, although less so for arson and vandalism. This is hypothesized to be due to the relatively constant target availability for these crimes as opposed to the other crime types studied.

Block-Level Analysis of the Attractors of Robbery in a Downtown Area

This article examines the predictions of crime pattern theory in a unique neighborhood type. It tested potential crime attracting facilities against street robbery data from 2009 to 2013 in the Police Districts I & II in Downtown Houston. The analysis modeled the four daily human routine periods described in the American Time Use Survey (ATUS). Generalized linear simultaneous negative binomial regression model was used to determine the size of the influence of the variables (beta coefficients) and their significance for each model outcome. The findings show some distinct patterns of street robbery due to the immediate and lagged effects of the variables relatable to the study environment’s unique setting. Two variables, geographic mobility, and barbershops were particularly significant across three of the outcome models. The results suggest that the physical and social structure of neighborhoods determined by land-use regulations would enhance understanding of the time-based influence on robbery patterns due to crime-attracting facilities.

A Socioeconomic Edge Effect: Rational Crime in Small Areas of Sharp Socioeconomic Contrast

Objectives: To determine whether criminogenic “edges,” as defined by crime pattern theory, exist at points of sharp contrast of socioeconomic status (SES). Methods: The study uses a quasi-experimental design with pattern matching logic. A series of negative binomial regression models separately examine five different crimes with an economic incentive as dependent variables, and five crimes without an economic incentive as nonequivalent dependent variables, to determine whether census block groups of predominantly and comparatively higher SES than the wider surrounding area experience greater reported rational crime than would otherwise be expected. Results: The census block groups of comparatively higher SES located within and/or near areas of predominantly lower SES experienced one of the five crimes with an economic incentive, robberies by firearm, 40 percent more frequently than would otherwise be expected. Conclusions: The study’s findings are partially consistent with its hypothesis, which is grounded in crime pattern, rational choice, routine activities, and social disorganization theories. The findings encourage future research that may extend the definition of an “edge” under crime pattern theory as well as research at the intersection of criminological theories.

Applying Crime Pattern Theory and Risk Terrain Modeling to Examine Environmental Crime in Cambodia

The spatial-temporal analysis of crime has significantly evolved. One innovative technique recently developed is risk terrain modeling (RTM). RTM, however, has yet to be used for environmental crime. This research applies RTM and draws from crime pattern theory to examine illegal activities in two protected areas in Cambodia. Findings suggest that pathways, edges, areas with suitable targets, conservation posts, landcover, and prior incidents are related to fauna- and flora-related illegal activities, though this relationship varies by season, units of analysis, and study area (i.e., patrol-based compared with official designation). Implications for theory and policy are outlined.

A Time for a Crime

Objectives: This article examines to what extent repeat offenders’ crime location choices are conditional on the timing of the offenses within the week and within the day. Extending crime pattern theory, we argue that offenders acquire time-specific rather than general knowledge of their environment. We hypothesize that offenders are more likely to offend in previously targeted areas at similar than at different days and times. Methods: Data on 12,639 offenses committed by 3,666 repeat offenders in the Netherlands are analyzed using discrete spatial choice models. Results: Offenders are most likely to offend in areas they already targeted before at similar parts of the week and similar times of the day, especially when the previous offense was committed on exactly the same weekend day or weekday and at the same hour of day. Offenders are less likely to return to previously targeted areas at different times of the week and day, and least likely to offend in areas they never targeted before. The effects were stronger for the same than for different types of crime. Conclusions: Assessing cyclic time patterns in crime location choice not only enhances our understanding of spatial criminal decision-making, but could also improve predictive policing methods.

Geoprofiling Terrorism

A number of recent research projects have explored applications of geographic profiling to counterterrorism and counterinsurgency. These efforts analyzed geospatial patterns of terrorist cells (e.g., the spatial relationship between safe houses and weapon storage sites), tested the ability of these techniques to locate terrorist bases from minor crimes and seditious graffiti, and examined the utility of geoprofiling for locating preparation sites used by insurgents for improvised explosive devices and rocket attacks. In appropriate cases, geoprofiling models have utility for prioritizing geo-intelligence and identifying logistic bases of terrorist operations. This chapter first discusses environmental criminology and the geography of crime. It then covers the basics of geographic profiling, its various applications, and the role of geospatial intelligence and crime pattern theory in counterterrorism. Finally, it examines the geospatial and temporal patterns of terrorism to show how geoprofiling can be used to analyze seditious graffiti, insurgency attacks, cyberterrorism, and bioterrorism.