Abstract
To identify and compare the space–time patterns of vehicle thefts and the effects of associated environmental factors, this paper conducts a case study of the Pudong New Area (PNA), a major urban district in Shanghai, China’s largest city. Geographic information system (GIS)-based analysis indicated that there was a stable pattern of vehicle theft over time. Hotspots of vehicle theft across different time periods were identified. These data provide clues for how law enforcement can prioritize the deployment of limited patrol and investigative resources. Vehicle thefts, especially those of non-motor vehicles, tend to be concentrated in the central-western portion of the PNA, which experienced a dramatic rate of urbanization and has a high concentration of people and vehicles. Important factors contributing to vehicle thefts include a highly mobile and transitory population, a large population density, and high traffic volume.
Highlights
IntroductionThe costs of vehicle theft include the direct uninsured financial losses, the opportunity cost of the time taken to deal with the crime, the opportunity cost of the temporary unavailability of a vehicle, and the psychological costs of victimization [3,4,5]
Vehicle theft is a major cause for concern for the public [1,2]
The temporal analysis revealed the dynamics of non-motor vehicle thefts (NMVT) and motor vehicle thefts (MVT) in the Pudong New Area (PNA)
Summary
The costs of vehicle theft include the direct uninsured financial losses, the opportunity cost of the time taken to deal with the crime, the opportunity cost of the temporary unavailability of a vehicle, and the psychological costs of victimization [3,4,5]. Most studies on vehicle theft were conducted in developed countries, though many developing countries suffer from growing rates of such crime. Of particular relevance in China is the fact that little is known about vehicle theft and its spatial and urban contexts, which experience restless landscape restructuring. Shanghai is the largest city in China and experienced accelerated urbanization since the early 1990s [13]. This paper aimed to identify and compare the space–time patterns of vehicle thefts in the Pudong New Area (PNA), the largest urban district in Shanghai, China. Studies on the spatiotemporal distributions of vehicle thefts in China are quite limited
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