Before You Are a Victim in Mexico: Police Strategies to Prevent Commercial Burglary Using Public Data

Antonio Petz () and Miguel Alejandro Flores
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Antonio Petz: School of Social Sciences and Government, Tecnologico de Monterrey, Monterrey 64700, Mexico
Miguel Alejandro Flores: School of Social Sciences and Government, Tecnologico de Monterrey, Monterrey 64700, Mexico

Social Sciences, 2025, vol. 14, issue 5, 1-24

Abstract: In a country where the majority of crimes remain unreported, uninvestigated, and unpunished, law enforcement faces considerable challenges in obtaining high-quality data that are consistent, reliable, and timely to effectively plan and deploy their strategies. By leveraging publicly available data, this paper identifies high-vulnerability areas for commercial burglary within the Metropolitan Area of Monterrey, utilizing a variable that incorporates the key dimensions of routine activity theory in criminology. This is accomplished by constructing an index through principal component analysis, followed by spatially grouping the resulting variable using the global indicator of spatial association (LISA). The results allow us to focus strategies to combat commercial burglary on 16.82% of the studied territory and establish an order of priorities to address the most vulnerable areas one by one. Also, the results allow us to implement prevention actions in broader zones by generating clusters around areas that share similar attributes.

Keywords: commercial burglary; hot spots; crime; principal component analysis; police (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2025
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