Learning where to offend: Effects of past on future burglary locations

Informed by a growing literature on space-time patterns of repeat and near repeat burglary victimization, a crime location choice model was used to test whether burglars are attracted to areas they previously targeted. Using data in 3337 detected burglaries from one UK police force, and accounting for the distance to the offender's residence, and for other factors that make target areas attractive to burglars, it was demonstrated that burglars were more likely to commit a burglary in an area they had targeted before. This was particularly the case if the prior burglary was (very) recent. Areas near to those in which burglaries had been committed were also more likely to be selected.

[1]  Ken Pease,et al.  Repeat Victimisation: Taking Stock , 1998 .

[2]  Jay Lee,et al.  Space–time interaction of residential burglaries in Wuhan, China , 2015 .

[3]  Ray Bull,et al.  The psychology of linking crimes: A review of the evidence , 2007 .

[4]  W. Bernasco,et al.  Crime Location Choice , 2014 .

[5]  Elizabeth A. Mack,et al.  Spatio-Temporal Interaction of Urban Crime , 2008 .

[6]  Shane D. Johnson,et al.  TARGET CHOICE DURING EXTREME EVENTS: A DISCRETE SPATIAL CHOICE MODEL OF THE 2011 LONDON RIOTS , 2013 .

[7]  Shane D. Johnson,et al.  Space–Time Patterns of Risk: A Cross National Assessment of Residential Burglary Victimization , 2007 .

[8]  Shane D. Johnson How do offenders choose where to offend? Perspectives from animal foraging , 2014 .

[9]  J. Clare,et al.  Formal Evaluation of the Impact of Barriers and Connectors on Residential Burglars' Macro-Level Offending Location Choices , 2009 .

[10]  M. Townsley,et al.  Infectious Burglaries. A Test of the Near Repeat Hypothesis , 2003 .

[11]  D. McFadden Quantitative Methods for Analyzing Travel Behaviour of Individuals: Some Recent Developments , 1977 .

[12]  Ronald V. Clarke,et al.  The Reasoning Criminal: Rational Choice Perspectives on Offending , 2017 .

[13]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[14]  Shane D. Johnson,et al.  The Use of Maps in Offender Interviews , 2010 .

[15]  Shane D. Johnson,et al.  Domestic Burglary Repeats and Space-Time Clusters , 2005 .

[16]  Shane D. Johnson,et al.  The use of maps in offender interviewing , 2013 .

[17]  Wim Bernasco,et al.  Co‐offending and the choice of target areas in burglary , 2006 .

[18]  W. Bernasco,et al.  Go where the money is: modeling street robbers’ location choices , 2013 .

[19]  Derek Johnson The space/time behaviour of dwelling burglars: Finding near repeat patterns in serial offender data , 2013 .

[20]  A. Tseloni,et al.  Repeat Personal Victimization. ‘Boosts’ or ‘Flags’? , 2003 .

[21]  W. Bernasco,et al.  How Do Residential Burglars Select Target Areas?: A New Approach to the Analysis of Criminal Location Choice , 2005 .

[22]  Shane D. Johnson,et al.  Consistency and specificity in burglars who commit prolific residential burglary: Testing the core assumptions underpinning behavioural crime linkage , 2016 .

[23]  Richard Block,et al.  WHERE OFFENDERS CHOOSE TO ATTACK: A DISCRETE CHOICE MODEL OF ROBBERIES IN CHICAGO* , 2009 .

[24]  Mandeep K. Dhami,et al.  Take-the-best in expert – novice decision strategies for residential burglary , 2022 .

[25]  Robert Haining,et al.  Ecological Analysis of Urban Offence and Offender Data , 2011 .

[26]  Jessica Woodhams,et al.  Linking serial residential burglary: comparing the utility of modus operandi behaviours, geographical proximity, and temporal proximity , 2010 .

[27]  Shane D. Johnson,et al.  Who commits near repeats? A test of the boost explanation , 2004 .

[28]  C. Nee,et al.  Expert Decision Making in Burglars , 2006 .

[29]  Michael J. McCullagh,et al.  IDENTIFYING REPEAT VICTIMIZATION WITH GIS , 1998 .

[30]  Jay Lee,et al.  Permeability, space syntax, and the patterning of residential burglaries in urban China , 2015 .

[31]  W. Bernasco,et al.  Effects of residential history on commercial robbers’ crime location choices , 2010 .

[32]  George E. Tita,et al.  Self-Exciting Point Process Modeling of Crime , 2011 .

[33]  Ray Bull,et al.  Linking Different Types of Crime Using Geographical and Temporal Proximity , 2011 .

[34]  K. Bowers,et al.  NEW INSIGHTS INTO THE SPATIAL AND TEMPORAL DISTRIBUTION OF REPEAT VICTIMIZATION , 1997 .

[35]  G. Breetzke The effect of altitude and slope on the spatial patterning of burglary , 2012 .

[36]  G. Farrell,et al.  LIKE TAKING CANDY Why does Repeat Victimization Occur , 1995 .

[37]  D. McFadden Disaggregate Behavioral Travel Demand's RUM Side A 30-Year Retrospective , 2000 .

[38]  Shane D. Johnson Repeat burglary victimisation: a tale of two theories , 2008 .

[39]  Ken Pease,et al.  Prospective hot-spotting - The future of crime mapping? , 2004 .

[40]  Ken Pease,et al.  THE TIME COURSE OF REPEAT BURGLARY VICTIMIZATION , 1991 .

[41]  Population turnover and churn: enhancing understanding of internal migration in Britain through measures of stability. , 2008, Population trends.

[42]  Allen R. Wilcox,et al.  Indices of Qualitative Variation and Political Measurement , 1973 .

[43]  P. Brantingham,et al.  Crime Pattern Theory , 2013, Oxford Research Encyclopedia of Criminology and Criminal Justice.

[44]  Shane D. Johnson,et al.  The Burglary as Clue to the Future , 2002 .

[45]  W. Bernasco A SENTIMENTAL JOURNEY TO CRIME: EFFECTS OF RESIDENTIAL HISTORY ON CRIME LOCATION CHOICE* , 2010 .

[46]  Shane D. Johnson,et al.  Examining the Relationship Between Road Structure and Burglary Risk Via Quantitative Network Analysis , 2015 .

[47]  Shane D. Johnson,et al.  Permeability and Burglary Risk: Are Cul-de-Sacs Safer? , 2010 .

[48]  Albert-László Barabási,et al.  Limits of Predictability in Human Mobility , 2010, Science.

[49]  Scott H. Decker,et al.  Burglars On The Job: Streetlife and Residential Break-ins , 1994 .

[50]  Wim Bernasco,et al.  Same-Offender Involvement in Repeat and Near Repeat Burglaries , 2008 .

[51]  W. Bernasco,et al.  Biting Once, Twice: The Influence of Prior on Subsequent Crime Location Choice: Biting Once, Twice , 2015 .

[52]  Shane D. Johnson,et al.  Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model , 2015, Crime and delinquency.

[53]  Ray Bull,et al.  The linking of burglary crimes using offender behaviour: Testing research cross-nationally and exploring methodology , 2012 .

[54]  Henk Elffers,et al.  Statistical Analysis of Spatial Crime Data , 2010 .

[55]  Fiona Brookman,et al.  THE FOREGROUND DYNAMICS OF STREET ROBBERY IN BRITAIN , 2006 .

[56]  Ken Pease,et al.  CRIME AGAINST THE SAME PERSON AND PLACE: DETECTION OPPORTUNITY AND OFFENDER TARGETING , 2006 .

[57]  Shane D. Johnson,et al.  The Stability of Space-Time Clusters of Burglary , 2004 .

[58]  Wim Bernasco,et al.  Modeling Micro-Level Crime Location Choice: Application of the Discrete Choice Framework to Crime at Places , 2010 .

[59]  Jessica Woodhams,et al.  Linking Crimes Using Behavioural Clues: Current Levels of Linking Accuracy and Strategies for Moving Forward , 2014 .

[60]  R. Golledge,et al.  Spatial Behavior: A Geographic Perspective , 1996 .

[61]  Shane D. Johnson,et al.  Exploring Theories of Victimization Using a Mathematical Model of Burglary , 2011 .

[62]  Ken Pease,et al.  Offender as Forager? A Direct Test of the Boost Account of Victimization , 2009 .