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Cited by 945

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Neutralization: New Insights into the Problem of Employee Information Systems Security Policy Violations1

Siponen, Mikko, Vance, Anthony·2010·MIS Quarterly

Abstract

Employees’ failure to comply with information systems security policies is a major concern for information technology security managers. In efforts to understand this problem, IS security researchers have traditionally viewed violations of IS security policies through the lens of deterrence theory. In this article, we show that neutralization theory, a theory prominent in Criminology but not yet applied in the context of IS, provides a compelling explanation for IS security policy violations and offers new insight into how employees rationalize this behavior. In doing so, we propose a theoretical model in which the effects of neutralization techniques are tested alongside those of sanctions described by deterrence theory. Our empirical results highlight neutralization as an important factor to take into account with regard to developing and implementing organizational security policies and practices.

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Metadata

Authors
Siponen, M., & Vance, A.
Venue
MIS Quarterly
Publisher
MIS Quarterly
Published
2010-09-01
Volume
34
Issue
3
Pages
487-502
ISSN
  • 0276-7783 (ISSN-L)
  • 2162-9730
OpenAlex
W1536398137
Cited by
945
References
6
FWCI
112.95
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Neutralization: New Insights into the Problem of Employee Information Systems Security Policy Violations1. https://app.cochat.ai/papers/10.2307/25750688
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Siponen, M., & Vance, A. (2010). Neutralization: New Insights into the Problem of Employee Information Systems Security Policy Violations1. MIS Quarterly. https://doi.org/10.2307/25750688

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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.