Place-based correlates of Motor Vehicle Theft and Recovery: Measuring spatial influence across neighbourhood context

Eric Piza, Shun Feng, Leslie Kennedy and Joel Caplan
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Eric Piza: John Jay College of Criminal Justice, USA
Shun Feng: John Jay College of Criminal Justice, USA
Leslie Kennedy: Rutgers University, USA
Joel Caplan: Rutgers University, USA

Urban Studies, 2017, vol. 54, issue 13, 2998-3021

Abstract: Social scientists have long shown great interest in the spatial correlates of crime patterns. A subset of the literature has focused on how micro-level spatial factors influence the formation of crime hot spots. At the same time, tangential research has highlighted how neighbourhood disadvantage influences crime occurrence. The current study focuses on the intersection of these perspectives through a spatial analysis of Motor Vehicle Theft (MVT) and Motor Vehicle Recovery (MVR) in Colorado Springs, CO. We begin by conducting a Risk Terrain Modelling analysis to identify spatial risk factors significantly related to MVT and MVR occurrence. We then test whether the spatial influences of the criminogenic risk factors differ across traditional measures of neighbourhood disadvantage. Findings suggest that while a citywide effect is evident for multiple risk factors, their spatial influence on crime significantly varies across neighbourhood contexts.

Keywords: environmental criminology; Motor Vehicle Recovery; Motor Vehicle Theft; Risk Terrain Modelling; social disorganisation; 环境犯罪学; 机动车找回; 机动车盗窃; 风险地形建模; ç¤¾ä¼šæ— åº (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:urbstu:v:54:y:2017:i:13:p:2998-3021

DOI: 10.1177/0042098016664299

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