Research consistently demonstrates that past victimisation is among the best
predictors of future risk. Using recorded domestic burglary crime data from
Victoria, Australia, analyses were conducted to examine temporal patterns of
repeat burglary victimisation. The analyses focus on both time elapsed between
incidents at the same location and the time of day that events occur, the latter
previously unexamined in the literature. The time-course of revictimisation is
as found hitherto: revictimisation occurs swiftly and the risk of repetition
decays over time. Considering the time of day, in line with routine activities
theory, the majority of incidents (first or follow-up events) occurred during
the day. More interestingly, the results suggest that, relative to repeat
burglaries that occur months after the first offence, those that occur within 7
days are more likely to occur at the same time of the day as the antecedent
event. Moreover, the time course of revictimisation appears to vary for
burglaries that occur at different times of the day. The results are discussed
in relation to routine activities theory and with respect to their implications
for crime reduction.
Get full access to this article
View all access options for this article.
References
1.
AgrestiA. (1996). An introduction to categorical data
analysis. New York:
Wiley
2.
AndersonD.CheneryS.PeaseK. (1995a). Biting back: Tackling
repeat burglary and car crime (Police Research Group: Crime
Detection and Prevention Series, Paper 58).
London: Home
Office.
3.
AndersonD.CheneryS.PeaseK. (1995b). Preventing repeat
victimisation: A report on progress in Huddersfield (Home
Office Police Research Group Briefing Note 4/95).
London: Home
Office.
4.
AnselinL.SyabriI.KhoY. (2004). GeoDa: An introduction to spatial
data analysis. Available online athttps://geoda.uiuc.edu/
5.
AshtonJ.BrownI.SeniorB.PeaseK. (1998). Repeat victimisation:
Offender accounts. International Journal of Risk,
Security and Crime Prevention,
3(4),
269–279.
6.
Australian Bureau of Statistics. (2002). 2015.2 2001 census of population
and housing: Selected social and housing characteristics for statistical
local areas, Victoria. Retrieved July 14, 2005, from http://www.abs.gov.au/ausstats
7.
BennettT. (1995). Identifying, explaining and
targeting burglary hotspots. European Journal of
Criminal Policy and Research, 31,
113–123.
8.
BlockC. (1984). Is crime seasonal?Chicago: Illinois Criminal
Justice Information Authority.
9.
BowersK.J.HirschfieldA.JohnsonS.D. (1998). Victimisation revisited: A
case study of non-residential repeat burglary on Merseyside.
British Journal of Criminology,
38(3),
429–452
10.
BowersK.J.JohnsonS.PeaseK. (2004). Prospective hot-spotting:
The future of crime mapping?British Journal of Criminology,
44(5),
55–65.
11.
BowersK.J.JohnsonS.D. (2004). Who commits near repeats? A
test of the boost explanation. Western Criminology
Review, 5(3),
12–24.
12.
BowersK.JohnsonS.D. (2005). Domestic burglary repeats
and space-time clusters. European Journal of
Criminology, 2(1),
67–92.
13.
BradyT.V. (1996). Measuring what matters Part
1: Measures of crime, fear and disorder (National Institute of
Justice: Research in Action Series).
Washington: US Department of
Justice.
14.
BuddT. (1999). Burglary of domestic
dwellings: Findings from the British Crime Survey (Home Office
Statistical Bulletin 4/99). London:
Home Office.
15.
BurquestR.FarrellG.PeaseK. (1992). Lessons from
schools. Policing, 8,
148–155.
16.
CheneryS.EllingworthD.TseloniA.PeaseK. (1996). Crimes which repeat:
Undigested evidence from the British Crime Survey.
International Journal of Risk, Security and Crime
Prevention, 1,
207–216.
17.
CheneryS.HoltJ.PeaseK. (1997). Biting back II: Reducing
repeat victimisation in Huddersfield (Crime Detection and
Prevention Series, Paper 82).
London: Home
Office.
18.
CohenL.FelsonM. (1979). Social change and crime
rates: A routine activity approach. American
Sociological Review, 44,
588–608.
19.
ColemanC.MoynihanJ. (1996). Understanding crime data: Haunted
by the dark figure. Maidenhead:
Open University Press.
20.
CornishD.ClarkeR. (1986). The reasoning criminal.
New York:
Springer-Verlag.
21.
CoupeT.BlakeL. (2006). Daylight and darkness
targeting strategies and the risks of being seen at residential
burglaries. Criminology,
44(2),
431–464.
22.
EllingworthD.FarrellG.PeaseK. (1995). A victim is a victim is a
victim?British Journal of Criminology,
35(3),
360–65.
23.
EricssonU. (1995). Straight from the horse's
mouth. Forensic Update,
43, 23–25.
24.
EversonS. (2003). Repeat victimisation and
prolific offending: Chance or choice?International Journal of Police Science and Management,
5(3),
180–194.
25.
EwartB.W.OatleyG.C. (2003). Applying the concept of
revictimization: using burglars' behaviour to predict houses at risk of
future victimization. International Journal of
Police Science and Management,
5(2),
69–84.
26.
EwartB.WOatleyG.C.BurnK. (2005). Matching crimes using
burglars' modus operandi: A test of three models.
International Journal of Police Science and Management,
7(3),
160–174.
27.
FarrellG.PeaseK. (1993). Once bitten, twice bitten:
Repeat victimisation and its implications for crime prevention
(Crime Prevention, Paper 46).
London: Home
Office.
28.
FarrellG.PeaseK. (1997). Repeat victim
support. British Journal of Social Work,
27,
103–113.
29.
FarrellG.PhillipsC.PeaseK. (1995). Like taking candy: Why does
repeat victimisation occur?British Journal of Criminology, 35,
384–399.
30.
FelsonM. (2002). Crime and everyday life(3rd ed.). California:
Sage Publications.
31.
FelsonM.PoulsonE. (2003). Simple indicators of crime
by time of day. International Journal of
Forecasting, 19,
595–601.
32.
ForresterD.ChattertonM.PeaseK. (1988) The Kirkholt Burglary
Prevention Project, Rochdale (Crime Prevention Unit, Paper
13). London: Home
Office.
33.
ForresterD.FrenzS.O'ConnellM.PeaseK. (1990). The Kirkholt Burglary
Prevention Project: Phase II (Crime Prevention Unit, Paper
23). London: Home
Office.
34.
GillM.PeaseK. (1998). Repeat robbers: How are they
different? In GillM.(Ed.), Crime at work: Studies in security and crime
prevention. Leicester:
Perpetuity Press.
35.
HawleyA. (1950). Human ecology: A theory of
community structure. New York:
Ronald Press.
36.
HindelangM.GottfredsonM.GarofaloJ. (1978). Victims of personal crime: An
empirical foundation for a theory of personal victimisation.
Cambridge, MA:
Ballinger.
37.
JacobsJ. (1961). The death and life of great
American cities. New York:
Random House.
38.
JohnsonJ. (1973). The recidivist victim: A
descriptive study. Criminal Justice
Monograph, 4(1).
39.
JohnsonS.D.BowersK.J.HirschfieldA. (1997). New insights into the
spatial and temporal distribution of repeat victimisation.
British Journal of Criminology,
37(2),
224–241.
40.
JohnsonS.D.BowersK.J. (2004a). The stability of space-time
clusters of burglary. British Journal of
Criminology, 44,
55–65.
41.
JohnsonS.D.BowersK.J. (2004b). The burglary as clue to the
future: The beginnings of prospective hot-spotting.
European Journal of Criminology.
1(2),
237–255.
42.
KrebsJ.R.DaviesN.B. (1987). An introduction to behavioural
ecology. Oxford:
Blackwell.
43.
LeBeauJ.L. (2002). The impact of a hurricane on
routine activities and on calls for police service: Charlotte, North
Carolina, and Hurricane Hugo. Crime Prevention and
Community Safety: An International Journal,
4(1),
53–64.
44.
MatthewsR.PeaseC.PeaseK. (2000). Repeated bank robbery: Theme
and variations. In FarrellG.PeaseK. (Eds.), Repeat victimisation (Crime
Prevention Studies, Vol. 12). New
York: Criminal Justice
Press.
45.
MorganF. (2000). Repeat burglary in a Perth
suburb: Indicator of short-term or long-term risk? In
FarrellG.PeaseK. (Eds.), Repeat victimisation (Crime
Prevention Studies, Vol. 12). New
York: Criminal Justice
Press.
46.
MooreD. (1997). Statistics: Concepts and
controversies. New York:
W.H. Freeman and Co.
47.
MukherjeeS.CarcachC. (1998). Repeat victimisation in
Australia: Extent, correlates and implications for crime
prevention (Australian Institute of Criminology Research and Public
Policy Series, No. 15). Canberra:
Australian Institute of
Criminology.
48.
NelsonJ. (1980). Multiple victimisation in
American cities: A statistical analysis of rare events.
American Journal of Sociology, 85,
870–891.
49.
PeaseK.LaycockG. (1996). Reducing the heat on hot
victims. Washington:
Bureau of Justice Statistics.
50.
PeaseK. (1998). Repeat victimisation:
Taking stock (Crime Prevention and Detection Series, Paper
90). London: Home
Office.
51.
PolviN.LoomanT.HumphriesC.PeaseK. (1991). The time course of repeat
burglary victimisation. British Journal of
Criminology, 31(4),
411–414.
52.
RatcliffeJ.McCullaghM. (1998). Identifying repeat
victimisation with GIS. British Journal of
Criminology, 38(4),
651–662.
53.
RatcliffeJ.McCullaghM. (1999). Burglary, victimisation and
social deprivation. Crime Prevention and Community
Safety, 1(2),
37-46.
54.
RatcliffeJ.McCullaghM. (2001). Crime, repeat victimisation
and GIS. In HirschfieldA.F.G.BowersK. (Eds.), Mapping and analysing crime data: Lessons from
research and practice. London:
Taylor & Francis.
55.
RatcliffeJ. (2000). Aoristic analysis: The
spatial interpretation of unspecific temporal events.
International Journal of Geographical Information Science,
14(7),
669–679.
56.
RatcliffeJ. (2006). A temporal constraint theory
to explain opportunity-based spatial offending patterns.
Journal of Research in Crime and Delinquency,
43(3),
261–291.
57.
RatcliffeJ. (2002). Aoristic signatures and the
spatio-temporal analysis of high volume crime patterns.
Journal of Quantitative Criminology,
18(1),
23–43.
58.
RatcliffeJ. (2004). The hotspot matrix: A
framework for the spatio-temporal targeting of crime
reduction. Police Practice and Research,
5(1),
5–23.
59.
ReadT.OldfieldD. (1995). Local crime analysis'
police research group (Crime Detection and Prevention Series,
Paper 65). London:
Home Office.
60.
RengertG. (1997). Auto theft in
Philadelphia. In HomelR.(Ed.), Policing for prevention: Reducing crime,
public intoxication and injury. New
York: Criminal Justice
Press.
61.
RengertG.WasilchickJ. (2000). Suburban burglary: A tale of two
suburbs. Springfield:
Charles C. Thomas.
62.
SampsonA.PhillipsC. (1995). Reducing repeat racial
victimisation on an East London estate (Police
Research Group: Crime Detection and Prevention Series, Paper 67).
London: Home
Office.
63.
SchneiderJ.L. (2005). The link between shoplifting
and burglary: The booster burglar. British Journal
of Criminology, 45(3),
395-401.
64.
ShermanL. (1992). Policing domestic violence:
Experiments and dilemmas. New York:
Macmillan.
65.
SimpsonE. H. (1951). The interpretation of interaction
in contingency tables, Journal of the Royal Statistical Society,
Series B, 13,
238–241.
SparksR. (1981). Multiple victimisation:
Evidence, theory and future research. Journal of
Criminal Law and Criminology, 72,
762–778.
68.
SpelmanW. (1995). Once bitten, then what?British Journal of Criminology,
35(3),
366–383.
69.
TilleyN. (1993). After Kirkholt —
Theory, method and results of replication evaluations (Police
Research Group: Crime Prevention Unit Series, Paper 47).
London: Home
Office.
70.
TilleyN. (1995) Thinking about crime
prevention performance indicators (Crime Detection and
Prevention Series, Paper 57).
London: Home
Office.
71.
TownsleyM.HomelR.ChaselingJ. (2000). Repeat burglary
victimisation: Spatial and temporal patterns.
Australian and New Zealand Journal of Criminology,
33(1),
37–63.
72.
TownsleyM.HomelR.ChaselingJ. (2003). Infectious burglaries: A
test of the near repeat hypothesis. British Journal
of Criminology, 43(3):
615–633.
73.
TrickettA.OsbornD.SeymourJ.PeaseK. (1992). What is different about high
crime areas?British Journal of Criminology,
32(1),
81–89.
74.
TseloniA.PeaseK. (1998). Nuisance phone calls to
women in England and Wales. European Journal
on Criminal Policy and Research, 6,
91–111.
75.
VaupelJ.W.YashinA.I. (1985). Heterogeneity's ruses: Some
surprising effects of selection on population dynamics.
The American Statistician,
39(3),
176–185.
