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Cited by 513

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The Novelty of ‘Cybercrime’: An Assessment in Light of Routine Activity Theory

Yar, Majid·2005·European Journal of Criminology

Abstract

Recent discussions of ‘cybercrime’ focus upon the apparent novelty or otherwise of the phenomenon. Some authors claim that such crime is not qualitatively different from ‘terrestrial crime’, and can be analysed and explained using established theories of crime causation. One such approach, oft cited, is the ‘routine activity theory’ developed by Marcus Felson and others. This article explores the extent to which the theory’s concepts and aetiological schema can be transposed to crimes committed in a ‘virtual’ environment. Substantively, the examination concludes that, although some of the theory’s core concepts can indeed be applied to cybercrime, there remain important differences between ‘virtual’ and ‘terrestrial’ worlds that limit the theory’s usefulness. These differences, it is claimed, give qualified support to the suggestion that ‘cybercrime’ does indeed represent the emergence of a new and distinctive form of crime.

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Metadata

Authors
Yar, M.
Venue
European Journal of Criminology
Published
2005-10
Volume
2
Issue
4
Pages
407-427
ISSN
  • 1477-3708 (ISSN-L)
  • 1741-2609
OpenAlex
W2121377134
Cited by
513
References
1
FWCI
10.64
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Novelty of ‘Cybercrime’: An Assessment in Light of Routine Activity Theory. https://app.cochat.ai/papers/10.1177/147737080556056
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Yar, M. (2005). The Novelty of ‘Cybercrime’: An Assessment in Light of Routine Activity Theory. European Journal of Criminology. https://doi.org/10.1177/147737080556056

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.