Objective: Examine the distribution and sources of crime across freestanding businesses in San Antonio. We test hypotheses about the main and interactive effects of neighborhood and business characteristics on crime at the business, with a focus on busy contexts and busy businesses. Method: Police crime incident data are spatially joined to study area business parcels. Additional data sources include Infogroup USA Business Data, the American Community Survey, and an Environmental Protection Agency traffic activity indicator. Multilevel negative binomial regression models are estimated to observe the main and interactive effects of census block group and business variables on crime at the parcel. Results: Businesses located in block groups with more commercial property and high levels of vehicular traffic experience more crime. In addition, crime is higher at “busy” businesses, as indicated by employee size, sales volume, and square footage. Busy contexts and busy businesses do not appear to interact to increase crime at the parcel beyond their main effects. Conclusions: Crime is clustered at relatively few businesses, and this variation cannot be explained by business type alone. Both neighborhood and business characteristics are associated with crime at freestanding businesses, with busy businesses and those within busier block groups experiencing more crime.

中文翻译：

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繁忙的企业和繁忙的环境：商业财产中犯罪的分布和来源

目的：检查圣安东尼奥各独立企业的犯罪分布和犯罪来源。我们测试关于社区和企业特征对企业犯罪的主要和互动影响的假设，重点关注繁忙的环境和繁忙的企业。方法：将警察犯罪事件数据在空间上合并到研究区域的业务范围中。其他数据源包括Infogroup USA商业数据，美国社区调查和环境保护局的交通活动指标。估计多级负二项式回归模型可观察人口普查区组和业务变量对包裹犯罪的主要影响和交互作用。结果：位于具有更多商业财产和高水平车辆通行的街区组的企业遭受的犯罪更多。此外，员工人数，销售量和平方英尺数表明，“繁忙”企业的犯罪率更高。繁忙的环境和繁忙的企业似乎并没有相互作用，以增加其主要影响之外的犯罪率。结论：犯罪集中在相对较少的企业中，并且这种变化不能仅通过业务类型来解释。邻里和商业特征都与独立式企业的犯罪活动相关，繁忙的企业和繁忙的街区群体中的企业遭受更多犯罪。这种变化无法仅通过业务类型来解释。邻里和商业特征都与独立式企业的犯罪活动相关，繁忙的企业和繁忙的街区群体中的企业遭受更多犯罪。这种变化无法仅通过业务类型来解释。邻里和商业特征都与独立式企业的犯罪活动相关，繁忙的企业和繁忙的街区群体中的企业遭受更多犯罪。