The Effect of Unemployment on Crime Occurrence of Major Crime Types

2021 ◽  
Vol 7 (2) ◽  
pp. 183-193
Author(s):  
Sung-won Cho ◽  
Keyword(s):  
Crime Types

Spatial Effect of Crime on Peer-to-Peer Lodging Performance

2021 ◽  
pp. 004728752110082
Author(s):  
Yu-Hua Xu ◽  
Lori Pennington-Gray ◽  
Jinwon Kim
Keyword(s):  
Peer To Peer ◽  
Spatial Effect ◽  
Econometric Models ◽  
Spatial Econometric ◽  
Community Based ◽  
Negatively Associated ◽  
Business Operations ◽  
Spatial Econometric Models ◽  
Crime Types ◽  
Social Uncertainty

Safety is a major factor impacting consumers’ participation in peer-to-peer (P2P) economies. Using spatial econometric models, this study examined crime effects on the performance (RevPAR) of P2P lodgings at three spatial ranges: property, community, and destination level. The performance of P2P lodgings is negatively associated with crime densities, while the degree of the association varies by crime types and room types. Crime can “spill over” to the neighborhood and have the strongest impact at the community level, followed by the destination level and the property level. The study provides a way to understand tourism risks using criminology theories and the concept of social uncertainty. Empirically, the study provides implications to the governance of community-based lodging business. We suggest that the effect of crime on P2P lodging performance was more conditioned by the safety environment in its neighborhood and the whole destination, rather than individual business operations.

Hate Crime and Place: The Spatial and Temporal Concentration of Bias-Motivated Crime in Washington, D.C.

2021 ◽  
pp. 088626052098781
Author(s):  
Marin R. Wenger ◽  
Brendan Lantz
Keyword(s):  
Hate Crime ◽  
Hate Crimes ◽  
Temporal Perspective ◽  
Spatial Stability ◽  
Units Of Analysis ◽  
Crime Types ◽  
High Degree ◽  
Block Groups ◽  
Street Segments

Prior research suggests that many crime types are spatially concentrated and stable over time. Hate crime, however, is a unique crime type that is etiologically distinct from others. As such, examination of hate crime from a spatial and temporal perspective offers an opportunity to understand hate crime and the spatial concentration of crime more generally. The current study examines the spatial stability of hate crimes reported to the police in Washington, D.C., from 2012 through 2018 using street segments, intersections, and block groups as units of analysis. Findings reveal that hate crime is spatially concentrated, with less than 4% of street segments and intersections experiencing hate crime over the study period. Results reveal a high degree of spatial stability, both year-to-year and over the long term even when restricting the analysis to units that experienced at least one hate crime.

Gender Specific Emotional Responses to Anticipated Crime

2007 ◽  
Vol 14 (3) ◽  
pp. 337-351 ◽  
Author(s):  
Simon C. Moore ◽  
Jonathan Shepherd
Keyword(s):  
Fear Of Crime ◽  
Emotional Responses ◽  
Dimensional Measure ◽  
Property Loss ◽  
Crime Types ◽  
Survey Responses ◽  
And Control ◽  
Specific Fear ◽  
Gender Specific ◽  
Personal Harm

In this paper multivariate analyses are used to test two hypotheses specific to the assumption that women are more fearful of crime than men. First, national crime survey responses to a global fear of crime question were analysed to assess whether responses to global questions were biased towards particular crime types. Results show that non-specific global fear of crime questions elicit responses most associated with fear of physical harm - explaining the persistent finding in previous research that women are more fearful than men. Second, a two-dimensional measure of fear of crime was derived from six crime specific fear of crime responses. Gender and control variables were regressed onto the derived measures of fear to test the hypothesis that dimensions of fear are gender specific. Results show that women are relatively more fearful of personal harm but no gender difference was found for fear of property loss. These data are consistent with a physical vulnerability explanation and, taken together, suggest that the irrationality hypothesis can be rejected.

Criminal Careers and Immigration: An Analysis of Offending Over the Life Course Among Homicide Inmates in Texas

2021 ◽  
pp. 001112872110399
Author(s):  
Erin A. Orrick ◽  
Chris Guerra ◽  
Alex R. Piquero
Keyword(s):  
Life Course ◽  
Growth Curve ◽  
Criminal Careers ◽  
Growth Curve Models ◽  
Administrative Records ◽  
Criminal Histories ◽  
Crime Types ◽  
The Life Course

The purpose of this study is to examine differences in patterns of criminal arrests between US citizens and foreign citizens among a sample of individuals incarcerated for homicide in Texas. Data for this project come from administrative records of inmates incarcerated in Texas for homicide. Drawing from the criminal careers literature, official arrest records are assessed to compare differences in criminal histories with growth curve models for the examination of criminal careers of non-Texas born US citizens and foreign citizens. Notable findings are that the age-crime curves are remarkably similar between the two groups, but the curves differ in degree, with those of US citizens peaking significantly higher across all crime types examined.

A Tale of Two Theories: Whither Social Disorganization Theory and the Routine Activities Approach?

2021 ◽  
pp. e20210013
Author(s):  
Jen-Li Shen ◽  
Martin A. Andresen
Keyword(s):  
Social Disorganization ◽  
Census Data ◽  
Property Crime ◽  
Routine Activities ◽  
Routine Activity ◽  
Social Disorganization Theory ◽  
Theoretical Frameworks ◽  
Social Phenomena ◽  
Crime Types ◽  
Routine Activities Approach

Social disorganization theory and the routine activities approach have been extensively applied separately as theoretical frameworks for the spatial analysis of crime, with general support. As hypothetical explanations for complex social phenomena, criminological theories can impact how studies are framed and how the crime problem is approached. Thus, it is important to evaluate theories continuously in various geographical, as well as contemporary contexts. This study uses both theories in tandem to examine their ability to explain 2016 property crime in Vancouver, Canada, using 2016 census data. Both theories found moderate support. Of particular note is that all of the variables designated as proxies for ethnic heterogeneity in social disorganization theory were either not statistically significant or negative, consistent with the immigration and crime literature. Additionally, almost all variables, when statistically significant, were found to have consistent results across crime types. These results bode well for the continued use of social disorganization theory and the routine activity approach in spatial analyses of crime.

Supervised and Unsupervised Machine Learning Methodologies for Crime Pattern Analysis

2021 ◽  
Vol 12 (1) ◽  
pp. 83-99
Author(s):  
Divya Sardana ◽  
Shruti Marwaha ◽  
Raj Bhatnagar
Keyword(s):  
Machine Learning ◽  
San Francisco ◽  
Pattern Analysis ◽  
Gradient Boosting ◽  
Unsupervised Machine Learning ◽  
Task Forces ◽  
Crime Types ◽  
Grave Problem ◽  
Crime Pattern

Crime is a grave problem that affects all countries in the world. The level of crime in a country has a big impact on its economic growth and quality of life of citizens. In this paper, we provide a survey of trends of supervised and unsupervised machine learning methods used for crime pattern analysis. We use a spatiotemporal dataset of crimes in San Francisco, CA to demonstrate some of these strategies for crime analysis. We use classification models, namely, Logistic Regression, Random Forest, Gradient Boosting and Naive Bayes to predict crime types such as Larceny, Theft, etc. and propose model optimization strategies. Further, we use a graph based unsupervised machine learning technique called core periphery structures to analyze how crime behavior evolves over time. These methods can be generalized to use for different counties and can be greatly helpful in planning police task forces for law enforcement and crime prevention.

scholarly journals Could Crime Risk Be Propagated across Crime Types?

2019 ◽  
Vol 8 (5) ◽  
pp. 203 ◽  
Author(s):  
Zengli Wang ◽  
Hong Zhang
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Theft ◽  
Vehicle Theft ◽  
Crime Type ◽  
Increased Risk ◽  
Short Period ◽  
Public Areas ◽  
Crime Types ◽  
Crime Risk ◽  
Temporal Interaction

It has long been acknowledged that crimes of the same type tend to be committed at the same location or proximity in a short period. However, the investigation of whether this phenomenon exists across crime types remains limited. The spatial-temporal clustered patterns for two types of crimes in public areas (pocket-picking and vehicle/motor vehicle theft) are separately examined. Compared with existing research, this study contributes to current research from three aspects: (1) The repeat and near-repeat phenomenon exists in two types of crimes in a large Chinese city. (2) A significant spatial-temporal interaction between pocket-picking and vehicle/motor vehicle theft exists within a range of 100 m. Some cross-crime type interactions seem to have a stronger ability of prediction than does single-crime type interaction. (3) A risk-avoiding activity is identified after spatial-temporal hotspots of another crime type. The spatial extent with increased risk is limited to a certain distance from the previous hotspots. The experimental results are analyzed and interpreted with current criminology theories.

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