Relevant bibliographies by topics / Near repeat burglary

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  1. Journal articles
  2. Dissertations / Theses

Academic literature on the topic 'Near repeat burglary'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Near repeat burglary"

1

Chen, Peng, and Justin Kurland. "The Impact of “Strike Hard” on Repeat and Near-Repeat Residential Burglary in Beijing." ISPRS International Journal of Geo-Information 9, no. 3 (March 6, 2020): 150. http://dx.doi.org/10.3390/ijgi9030150.

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“Strike Hard” is an enhanced law-enforcement strategy in China that aims to suppress crime, but measurement of the crime-reducing effect and potential changes in the spatiotemporal concentration of crime associated with “Strike Hard” remain unknown. This paper seeks to examine the impact, if any, of “Strike Hard” on the spatiotemporal clustering of burglary incidents. Two and half years of residential burglary incidents from Chaoyang, Beijing are used to examine repeat and near-repeat burglary incidents before, during, and after the “Strike Hard” intervention and a new technique that enables the comparison of repeat and near repeat patterns across different temporal periods is introduced to achieve this. The results demonstrate the intervention disrupted the repeat pattern during the “Strike Hard” period reducing the observed ratio of single-day repeat burglaries by 155%; however, these same single-day repeat burglary events increased by 41% after the cessation of the intervention. Findings with respect to near repeats are less remarkable with nominal evidence to support that the intervention produced a significant decrease, but coupled with other results, suggest that spatiotemporal displacement may have been an undesired by-product of “Strike Hard”. This study from a non-Western setting provides further evidence of the generalizability of findings related to repeat and near repeat patterns of burglary and further highlights the limited preventative effect that the “Strike Hard” enhanced law enforcement campaign had on burglary.
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Chainey, Spencer P., Sophie J. Curtis-Ham, R. Mark Evans, and Gordon J. Burns. "Examining the extent to which repeat and near repeat patterns can prevent crime." Policing: An International Journal 41, no. 5 (October 1, 2018): 608–22. http://dx.doi.org/10.1108/pijpsm-12-2016-0172.

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Purpose The purpose of this paper is to examine the extent and variation in the estimates to which crime can be prevented using patterns of repeats and near repeats, and whether hotspot analysis complements these patterns. Design/methodology/approach Crime data for four study areas in New Zealand are used to examine differences in the extent of burglary repeat and near repeat victimisation. Hotspots of burglary are also created to determine the extent to which burglary repeats and near repeats spatially intersect hotspots. Findings The extent of repeats and near repeats varies, meaning there is variation in the estimated prevention benefits that repeat and near repeat patterns offer. In addition, at least half of the burglaries repeats and near repeats were not located within hotspots. Research limitations/implications The use of other techniques for examining crime concentration could be used to improve the research observations. Practical implications By showing that levels of repeats and near repeats vary, the extent to which these observations coincide in hotspots offers practitioners a better means of determining whether repeat and near repeat patterns are reliable for informing crime prediction and crime prevention activities. Originality/value The paper is the first known research study that explicitly measures the variation in the extent of repeats and near repeats and the spatial intersection of these patterns within crime hotspots. The results suggest that rather than considering the use of repeat and near repeat patterns as a superior method for predicting and preventing crime, value remains in using hotspot analysis for determining where crime is likely to occur, particularly when hotspot analysis emphasises other locations for resource targeting.
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Hoppe, Laura, and Manne Gerell. "Near-repeat burglary patterns in Malmö: Stability and change over time." European Journal of Criminology 16, no. 1 (January 9, 2018): 3–17. http://dx.doi.org/10.1177/1477370817751382.

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It is well established that previous crime events are valuable indicators for the prediction of future crime. Near-repeat burglaries are incidents that occur in close proximity in space and time to an initial burglary. The current study analyses near-repeat victimization patterns in Malmö, Sweden’s third-largest city. The data, provided by the local police, cover a six-year time frame from 2009 to 2014. The complete dataset, as well as each year’s individual dataset, was analysed using Ratcliffe’s Near Repeat Calculator version 1.3. Results reveal significant near-repeat victimization patterns. For the full dataset, an observed/expected ratio of 2.83 was identified for the first week after an initial incident and an area of 100 metres surrounding the original burglary. Separate analyses of each individual year reveal both similarities and differences between years. Some years manifest near-repeat patterns at longer spatial and temporal distances, indicating a need for further studies on the variability of near repeats. Preventive strategies that include both private and public actors need to be intensified and focused on the first two weeks after a burglary.
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Short, M. B., M. R. D’Orsogna, P. J. Brantingham, and G. E. Tita. "Measuring and Modeling Repeat and Near-Repeat Burglary Effects." Journal of Quantitative Criminology 25, no. 3 (May 20, 2009): 325–39. http://dx.doi.org/10.1007/s10940-009-9068-8.

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5

Groff, Elizabeth, and Travis Taniguchi. "Quantifying Crime Prevention Potential of Near-Repeat Burglary." Police Quarterly 22, no. 3 (February 14, 2019): 330–59. http://dx.doi.org/10.1177/1098611119828052.

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Groff, Elizabeth, and Travis Taniguchi. "Using citizen notification to interrupt near-repeat residential burglary patterns: the micro-level near-repeat experiment." Journal of Experimental Criminology 15, no. 2 (January 26, 2019): 115–49. http://dx.doi.org/10.1007/s11292-018-09350-1.

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7

Pitcher, Ashley B., and Shane D. Johnson. "Exploring Theories of Victimization Using a Mathematical Model of Burglary." Journal of Research in Crime and Delinquency 48, no. 1 (February 2011): 83–109. http://dx.doi.org/10.1177/0022427810384139.

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Research concerned with burglary indicates that it is clustered not only at places but also in time. Some homes are victimized repeatedly, and the risk to neighbors of victimized homes is temporarily elevated. The latter type of burglary is referred to as a near repeat. Two theories have been proposed to explain observed patterns. The boost hypothesis states that risk is elevated following an event reflecting offender foraging activity. The flag hypothesis, on the other hand, suggests that time-stable variation in risk provides an explanation where data for populations with different risks are analyzed in the aggregate. To examine this, the authors specify a series of discrete mathematical models of urban residential burglary and examine their outcomes using stochastic agent-based simulations. Results suggest that variation in risk alone cannot explain patterns of exact and near repeats, but that models which also include a boost component show good qualitative agreement with published findings.
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8

Townsley, Michael, Ross Homel, and Janet Chaseling. "Repeat Burglary Victimisation: Spatial and Temporal Patterns." Australian & New Zealand Journal of Criminology 33, no. 1 (April 2000): 37–63. http://dx.doi.org/10.1177/000486580003300104.

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To date there has been little Australian research on repeat victimisation. This is a study of repeat burglary in an area of Brisbane using police calls for service data. We demonstrate: (a) the prevalence of residential repeat victim addresses (‘hot dot’) is of a similar magnitude to that found in studies in the United Kingdom; (b) the time distributions of revictimisation are identical with those found in studies in the UK and elsewhere; (c) ‘hot spots’ (small areas with high crime density) can be identified by statistical analyses of spatial concentrations of incidents; (d) unstable hot spots tend to be temporary aggregations of hot dots, whereas stable hot spots seem to reflect more the social and physical characteristics of certain localities; and (e) the overall incidence of burglary could be reduced by at least 25 per cent if all repeat victimisation could be eliminated. There are a number of areas where concepts and techniques for repeat victim research could potentially be strengthened: (a) clarifying the connections between hot dots and hot spots, particularly through exploration of the concept of a ‘near repeat address’; (b) applying survival analysis to the data on the time periods between victimisations; and (c) using moving average techniques to examine changes in the spatial distributions of burglary over time.
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Bediroglu, Gamze, Sevket Bediroglu, H. Ebru Colak, and Tahsin Yomralioglu. "A Crime Prevention System in Spatiotemporal Principles With Repeat, Near-Repeat Analysis and Crime Density Mapping: Case Study Turkey, Trabzon." Crime & Delinquency 64, no. 14 (January 9, 2018): 1820–35. http://dx.doi.org/10.1177/0011128717750391.

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In this study, we investigated crime events with repeat and near-repeat analysis for Turkey’s Trabzon city’s crime data after standardization process on raw crime data. First, a new crime geodatabase model was created. All types of recorded crime data for events between the years 2010 and 2014 were standardized, generalized, and Geo-referenced. We gave certain locations to crime events with geocoding techniques. Then, we created density maps of crime events with Kernel method in Geographic Information Systems (GIS). Repeat and near-repeat methods were tested on Burglary crime type in this geodatabase. Studies focused to applying prediction analysis besides showing current situation. These predictive analyses may be applied for all the security, intelligence, or defense departments at local, national, or international levels.
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Wang, Zengli, and Xuejun Liu. "Analysis of Burglary Hot Spots and Near-Repeat Victimization in a Large Chinese City." ISPRS International Journal of Geo-Information 6, no. 5 (May 10, 2017): 148. http://dx.doi.org/10.3390/ijgi6050148.

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Dissertations / Theses on the topic "Near repeat burglary"

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Drawve, Grant. "GEOSPATIAL ANALYSIS OF REPEAT & NEAR REPEAT RESIDENTIAL BURGLARIES." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/652.

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This analysis explores the formation of stable hot spots and the overall shifts of repeat and near repeat residential burglary over time. Data were obtained from a small college town police department. There were 1,513 repeat residential burglaries between January 2003 and December 2009 that occurred at a total of 356 addresses. Based upon past research it is thought that repeat residential burglaries will cluster in time and space creating stable hot spots and that the centrographic measures of the burglaries will remain relatively constant from year to year. The results found support for the formation of stable hot spots but found that the area in which the repeat residential burglaries were occurring increased over time.
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Clark, James Andrew George Roy. "The near repeat risk calculation of residential burglaries in Hillcrest, KwaZulu-Natal, South Africa : a criminological analysis." Diss., 2018. http://uir.unisa.ac.za/handle/10500/25683.

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Text in English with abstracts in English, isiZulu and Xhosa
This research applies the Near Repeat Calculator (NRC) to identify near repeat residential burglary patterns in the Hillcrest (KZN) policing area for the first time. A total of 490 residential burglaries, over a 12-month period, reported to Hillcrest police station were mapped (geocoded) and the near repeat calculations were visualised using the Geographic Information Systems (GIS). The month-to-month near repeat calculations are analysed and suggest that the NRC is a valuable tool that can predict the space-time locations of near repeat residential burglaries in the Hillcrest policing area.
Lolu cwaningo lusebenzisa i-Near Repeat Calculator (NRC) ukuhlonza amaphethini okuphindaphindeka kwezigameko zokugqekezwa kwamakhaya endaweni eyenganyelwe yisiteshi samaphoyisa sase-Hillcrest (KZN). Izigameko zokugqekezwa kwamakhaya ezingama-490 ezabikwa esiteshini samaphoyisa sase- Hillcrest esikhathini esiyizinyanga eziyi-12 zaboniswa emfanekisweni webalazwe lendawo (geocoded) futhi izilinganiso zamathuba okuthi ziphinde zenzeke izigameko zokugqekezwa kwamakhaya zaboniswa ngokuthi kusetshenziswe umfanekiso owenziwe nge-Geographic Information Systems (GIS). Kwahlaziywa amathuba enyanga nenyanga okuphindaphindeka kwezigameko, futhi imiphumela eyatholakala kulokhu iyabonisa ukuthi i-NRC iyithuluzi eliwusizo impela elingabikezela izindawo nesikhathi lapho kungaphinda futhi kwenzeke khona izigameko zokugqekezwa kwamakhaya endaweni eyenganyelwe yisiteshi samaphoyisa sase-Hillcrest.
Olu phando lusebenzisa uhlobo lokubala olwaziwa ngokuba yiNear Repeat Calculator (NRC) ngenjongo yokubona isimbo sokuqhekezwa kwezindlu zabantu kummandla ophantsi kwamapolisa aseHillcrest (eKZN). Kuqwalaselwe ama-490 eziganeko zoqhekezo lwemizi ezaxelwa emapoliseni aseHillcrest kwisithuba seenyanga ezili-12, kwaye uhlobo lokubala oluqikelela ukuphindwa kweziganeko zoqhekezo luboniswe ngokusebenzisa inkqubo ekuthiwa yiGeographic Information Systems (GIS). Ubalo oluqikelela ukuphindwa kweziganeko luphononongiwe kwinyanga nenyanga, kwaye iziphumo zibonisa ukuba iNRC sisixhobo esinexabiso, esinokukwazi ukuqikelela indawo nexesha apho kunokuphinda kuqhekezwe khona kummandla ophantsi kwamapolisa aseHillcrest.
Criminology and Security Science
M.A. (Criminology)
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