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A Stab in the Dark? Analysing Temporal Trends of Street Robbery

Bowers, KJ; Tompson, L; (2013) A Stab in the Dark? Analysing Temporal Trends of Street Robbery. Journal of Research in Crime and Delinquency , 50 (4) pp. 616-631. 10.1177/0022427812469114. Green open access


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Objectives: Test the influence of darkness in the street robbery crime event alongside temperature. Methods: Negative binomial regression models tested darkness and temperature as predictors of street robbery. Units of analysis were four 6-hr time intervals in two U.K. study areas that have different levels of darkness and variations of temperature throughout the year. Results: Darkness is a key factor related to robbery events in both study areas. Traversing from full daylight to full darkness increased the predicted volume of robbery by a multiple of 2.6 in London and 1.2 in Glasgow. Temperature was significant only in the London study area. Interaction terms did not enhance the predictive power of the models. Conclusion: Darkness is an important driving factor in seasonal variation of street robbery. A further implication of the research is that time of the day patterns are crucial to understanding seasonal trends in crime data.

Type: Article
Title: A Stab in the Dark? Analysing Temporal Trends of Street Robbery
Open access status: An open access version is available from UCL Discovery
DOI: 10.1177/0022427812469114
Publisher version: http://dx.doi.org/10.1177/0022427812469114
Language: English
Additional information: © The Author(s) 2012. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(http://www.uk.sagepub.com/aboutus/openaccess.htm).
Keywords: causes/correlates crime trends crime; routine activity theory; criminological theory; statistical methods; quantitative research; research methods;
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Security and Crime Science
URI: http://discovery.ucl.ac.uk/id/eprint/1359524
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