An integrative study of information systems security effectiveness

By Atreyi Kankanhalli, Hock Hai Teo, Bernard C. Y. Tan, Kwok Kee Wei. International Journal of Information Management, 2003

561 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/e1a27bf8cc01117a97704a40a90da273c503b295

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

Studying users' computer security behavior: A health belief perspective (2009, background): “However, the increase in organizational dependence on information systems as well as the ease of mounting attacks has led to a corresponding increase in the number of security incidents and damage caused [26].”
A review and analysis of deterrence theory in the IS security literature: making sense of the disparate findings (2011, background): “This issue comes to light when examining the divergent findings of Kankanhalli et al (2003) and D’Arcy et al (2009) regarding the deterrent effect of formal sanction severity.”
An Enhanced Fear Appeal Rhetorical Framework: Leveraging Threats to the Human Asset Through Sanctioning Rhetoric (2015, background): “Following this research, Kankanhalli et al. (2003) investigated whether the use of sanctions led to enhanced IS security effectiveness and found that deterrents, as measured in man-hours spent in security efforts, led to the improved effectiveness of information security.”
Encouraging information security behaviors in organizations: Role of penalties, pressures and perceived effectiveness (2009, background): “[36] found that deterrent severity in the form of punishments meted out to IS abusers did not seem to affect the security effectiveness.”
User Awareness of Security Countermeasures and Its Impact on Information Systems Misuse: A Deterrence Approach (2009, background): “The rationale for GDT is that security countermeasures can serve as deterrent mechanisms by increasing perceptions of the certainty and severity of punishment for IS misuse, thereby reducing the incidence of such behavior.”
The effects of convenience and speed in m-payment (2015, background): “Since PLS-SEM is a variance or component-based linear model which does not require data normality (Kankanhalli et al., 2003; Ranganathan et al., 2011; Sheng and Teo, 2012), it may not be able to capture non-linear decision-making process (Leong et al.”