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Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh
Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center. 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. Primary and secondary data sources were used, but primary data played a primary role in this study. 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. More street crime hotspots were found in the residential than in the business neighborhood. 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. Qualitative and statistical analysis results show social, economic, geographical, governance, and planning and urban design factors play a vital role in developing USC hotspots in Chittagong city. The study outcomes need to be considered for an integrated approach to monitor and reduce street crime hotspots by policymakers, urban local government, and community leaders in Chittagong city.
Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh
Urban street crime (USC) hotspots severely affect the residential and business neighborhood (RBN) areas of any urban center. 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. Primary and secondary data sources were used, but primary data played a primary role in this study. 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. More street crime hotspots were found in the residential than in the business neighborhood. 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. Qualitative and statistical analysis results show social, economic, geographical, governance, and planning and urban design factors play a vital role in developing USC hotspots in Chittagong city. The study outcomes need to be considered for an integrated approach to monitor and reduce street crime hotspots by policymakers, urban local government, and community leaders in Chittagong city.
Analyzing Street Crime Hotspots and Their Associated Factors in Chittagong City, Bangladesh
Mohammad Ali Haider (author) / Pawinee Iamtrakul (author)
2022
Article (Journal)
Electronic Resource
Unknown
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