Block-Level Analysis of the Attractors of Robbery in a Downtown Area

Abstract

This article examines the predictions of crime pattern theory in a unique neighborhood type. It tested potential crime attracting facilities against street robbery data from 2009 to 2013 in the Police Districts I & II in Downtown Houston. The analysis modeled the four daily human routine periods described in the American Time Use Survey (ATUS). Generalized linear simultaneous negative binomial regression model was used to determine the size of the influence of the variables (beta coefficients) and their significance for each model outcome. The findings show some distinct patterns of street robbery due to the immediate and lagged effects of the variables relatable to the study environment’s unique setting. Two variables, geographic mobility, and barbershops were particularly significant across three of the outcome models. The results suggest that the physical and social structure of neighborhoods determined by land-use regulations would enhance understanding of the time-based influence on robbery patterns due to crime-attracting facilities.