Journal
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Volume 10, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/ijgi10120802
Keywords
cyber fraud; spatiotemporal pattern; driving factors; spatial autocorrelation; generalized additive model
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This study explores the spatiotemporal pattern of cyber fraud crimes in China and finds that cyber fraud has gradually spread from southeastern to middle and northern regions. The distribution of cyber fraud is notably influenced by regional economy and population structure, with factors such as a large nonagricultural population, a high proportion of tertiary industry in GDP, a large number of general college students, a longer cable length, and a large numbers of internet users closely associated with high incidence of cyber fraud crimes.
As a typical cybercrime, cyber fraud poses severe threats to civilians' property safety and social stability. Traditional criminological theories such as routine activity theory focus mainly on the effects of individual characteristics on cybercrime victimization and ignore the impacts of macro-level environmental factors. This study aims at exploring the spatiotemporal pattern of cyber fraud crime in China and investigating the relationships between cyber fraud and environmental factors. The results showed that cyber fraud crimes were initially distributed in southeastern China and gradually spread towards the middle and northern regions; spatial autocorrelation analysis revealed that the spatial concentration trend of cyber fraud became more and more strong, and a strong distinction in cyber fraud clustering between the north and the south was identified. To further explain the formative causes of these spatial patterns, a generalized additive model (GAM) was constructed by incorporating natural and social environmental factors. The results suggested that the distribution of cyber fraud was notably affected by the regional economy and population structure. Also, the high incidence of cyber fraud crime was closely associated with a large nonagricultural population, a high proportion of tertiary industry in GDP, a large number of general college students, a longer cable length, and a large numbers of internet users.
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