{"title":"香港公共交通系统的罪案:热点与危害轨迹分析","authors":"Yiu Ming Ng, Barak Ariel, Vincent Harinam","doi":"10.1108/pijpsm-05-2023-0067","DOIUrl":null,"url":null,"abstract":"Purpose A growing body of literature focuses on crime hotspots; however, less is known about the spatial distribution of crime at mass transit systems, and even less is known about trajectory patterns of hotspots in non-English-speaking countries. Design/methodology/approach The spatiotemporal behaviour of 1,494 crimes reported to the Hong Kong’s Railway Police District across a two-year period was examined in this study. Crime harm weights were then applied to offences to estimate the distribution of crime severity across the transit system. Descriptive statistics are used to understand the temporal and spatial trends, and k-means longitudinal clustering are used to examine the developmental trajectories of crime in train stations over time. Findings Analyses suggest that 15.2% and 8.8% of stations accounted for 50% of all counted crime and crime harm scores, respectively, indicating the predictability of crime and harm to occur at certain stations but not others. Offending persists consistently, with low, moderate and high counts and harm stations remaining the same over time. Research limitations/implications These findings suggest that more localised crime control initiatives are required to target crime effectively. Originality/value This is one of the only studies focusing on hotspots and harmspots in the mass transit system.","PeriodicalId":47881,"journal":{"name":"Policing-An International Journal of Police Strategies & Management","volume":"4 2","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Crime on the mass transit system in Hong Kong: a hotspots and harmspots trajectory approach\",\"authors\":\"Yiu Ming Ng, Barak Ariel, Vincent Harinam\",\"doi\":\"10.1108/pijpsm-05-2023-0067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose A growing body of literature focuses on crime hotspots; however, less is known about the spatial distribution of crime at mass transit systems, and even less is known about trajectory patterns of hotspots in non-English-speaking countries. Design/methodology/approach The spatiotemporal behaviour of 1,494 crimes reported to the Hong Kong’s Railway Police District across a two-year period was examined in this study. Crime harm weights were then applied to offences to estimate the distribution of crime severity across the transit system. Descriptive statistics are used to understand the temporal and spatial trends, and k-means longitudinal clustering are used to examine the developmental trajectories of crime in train stations over time. Findings Analyses suggest that 15.2% and 8.8% of stations accounted for 50% of all counted crime and crime harm scores, respectively, indicating the predictability of crime and harm to occur at certain stations but not others. Offending persists consistently, with low, moderate and high counts and harm stations remaining the same over time. Research limitations/implications These findings suggest that more localised crime control initiatives are required to target crime effectively. Originality/value This is one of the only studies focusing on hotspots and harmspots in the mass transit system.\",\"PeriodicalId\":47881,\"journal\":{\"name\":\"Policing-An International Journal of Police Strategies & Management\",\"volume\":\"4 2\",\"pages\":\"0\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2023-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Policing-An International Journal of Police Strategies & Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/pijpsm-05-2023-0067\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CRIMINOLOGY & PENOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Policing-An International Journal of Police Strategies & Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/pijpsm-05-2023-0067","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
Crime on the mass transit system in Hong Kong: a hotspots and harmspots trajectory approach
Purpose A growing body of literature focuses on crime hotspots; however, less is known about the spatial distribution of crime at mass transit systems, and even less is known about trajectory patterns of hotspots in non-English-speaking countries. Design/methodology/approach The spatiotemporal behaviour of 1,494 crimes reported to the Hong Kong’s Railway Police District across a two-year period was examined in this study. Crime harm weights were then applied to offences to estimate the distribution of crime severity across the transit system. Descriptive statistics are used to understand the temporal and spatial trends, and k-means longitudinal clustering are used to examine the developmental trajectories of crime in train stations over time. Findings Analyses suggest that 15.2% and 8.8% of stations accounted for 50% of all counted crime and crime harm scores, respectively, indicating the predictability of crime and harm to occur at certain stations but not others. Offending persists consistently, with low, moderate and high counts and harm stations remaining the same over time. Research limitations/implications These findings suggest that more localised crime control initiatives are required to target crime effectively. Originality/value This is one of the only studies focusing on hotspots and harmspots in the mass transit system.