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作者

Xin Gu;Lin Liu;Minxuan Lan;Hanlin Zhou

来源

CITIES,Vol.135,Issue1,Article 104188

语言

英文

关键字

作者单位

Department of Geography and GIS, University of Cincinnati, Cincinnati, OH 45221, USA;Department of Geography and Planning, University of Toledo, Toledo, OH 43606, USA;Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada;Department of Geography, Geomatics, and Environment, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada;Department of Geography and GIS, University of Cincinnati, Cincinnati, OH 45221, USA;Department of Geography and Planning, University of Toledo, Toledo, OH 43606, USA;Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada;Department of Geography, Geomatics, and Environment, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada;University of Alicante, Spain;Xi'an Jiaotong-Liverpool University, China;Department of Geography, Lab for Landscape Ecology, Humboldt Universität zu Berlin, Berlin, Germany;Department of Urban and Environmental Sociology, Helmholtz Centre for Environmental Research UFZ, Leipzig, Germany;St. Peter's College, University of Oxford, New Inn Hall Street, Oxford OX1 2DL, United Kingdom;Department for Continuing Education, University of Oxford, Rewley House, 1 Wellington Square, OX1 2JA, Oxford, United Kingdom;College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China;Department of Civil, Structural & Environmental Engineering, University of Dublin, Trinity College, Dublin 2, Ireland;Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China;Key Labs of Law Evaluation of Ministry of Land and Resources of China, 388 Lumo Road, Hongshan District, Wuhan 430074, China;Collaborative Innovation Center for Emissions Trading system Co-constructed by the Province and Ministry, Hubei University of Economics, Wuhan 430205, China,;School of Low Carbon Economics, Hubei University of Economics, Wuhan 430205, China;School of Design, Shanghai Jiao Tong University, Shanghai 200240, China;School of Geographic Sciences, East China Normal University, Shanghai 200241, China;School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China;Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China

摘要

Social disorganization theory has significantly contributed to understanding the relationship between community characteristics and crime. It is based on the assumption that the residents of a community define the characteristics of the community. In particular, Shaw and McKay discover that racial heterogeneity could disrupt the local community's social organization and account for crime and delinquency. While residents play the most important role in defining the characteristics of a community, non-residents who frequent a community could also affect the community. The perceived racial composition is likely to be different from the makeup of the residential population. Drawing from the recent big data which could capture residents and non-residents, this paper proposes an innovative racial heterogeneity index based on the ambient population. The effectiveness of the new index is illustrated by using negative binomial models, to explain street crime. The findings show that the ambient population-based racial heterogeneity index outperforms the traditional one in explaining street robbery. Further, the new index positively impacts street robbery in a statistically significant fashion. Conversely, the traditional index shows no statistically significant influence. The study also reveals that the racial heterogeneity of ambient population in an area is mostly contributed by the visitors from the neighboring areas. Overall, the proposed ambient population-based racial heterogeneity is theoretically sound and effective in explaining street crimes such as street robbery. The novel approach and findings add new contributions to social disorganization and routine activity theories.