Pattern and Explanation of Inter-City Crime Variation in South Korea

Hyunjoong Kim () and Eunyoung Seong
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Hyunjoong Kim: Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
Eunyoung Seong: Architecture & Urban Research Institute, Sejong 30103, Republic of Korea

Sustainability, 2022, vol. 14, issue 22, 1-16

Abstract: The primary purpose of this paper is to test the applicability of environmental criminology in South Korea. Moreover, it explores effective strategies from a spatial planning perspective by taking control of diverse spatial planning factors. The study area is South Korea, and the base year is 2016. A spatial econometric model is built to analyze the relationship between the built environment and three crimes (theft, violence, and sexual assault). As a result, the best spatial regression models for violent crime rate and sexual assault rate are a spatial error model (SEM) and a spatial autoregressive model (SAC), respectively. The most prominent finding is that the regression results in the three crimes are slightly different. The broken windows effect was negligible for significant crimes in South Korea. The influence of regional disorders on the incidence of crimes was marginal. In the three crime types, mixed land use affected rising crime rates, which aligns with some previous studies that mixed land use increases the likelihood of crime incidences. In contrast with a series of relevant works, brighter nighttime light has not effectively decreased crimes in South Korea. In South Korea, closed-circuit television (CCTV) did not play a role in deterring crimes. Lastly, socio-economic characteristics were closely connected with crime rates in South Korea. The theft rate, violent crime rate, and sexual assault rate confirm the reliability of environmental criminology. Although this study has examined the likelihood of applying environmental criminology, further research and discussions are followed for concrete plans.

Keywords: crime; environmental criminology; spatial regression models; spatial planning; South Korea (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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