The statistical analysis of the logistic regression model for street crime victimization, a hotspot analysis model of a contour map, and a spatial autocorrelation map identified vulnerable locations in the residential and business neighborhood areas where people are frequently victimized by street crime. More street crime hotspots were found in the residential than in the business neighborhood. It was found that male, married, landlord, and middle-income groups of people are more likely to be victimized than the female, unmarried, renters, rich, and no-income groups. Primary and secondary data sources were used, but primary data played a primary role in this study. This study analyzes USC hotspots and identifies the associated risk factors of becoming a USC hotspot in the residential and business neighborhood areas of Chittagong city. Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center.
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