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DBLP
Article . 2021
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The Nudge Puzzle

Matching Nudge Interventions to Cybersecurity Decisions
Authors: Verena Zimmermann; Karen Renaud;

The Nudge Puzzle

Abstract

Nudging is a promising approach, in terms of influencing people to make advisable choices in a range of domains, including cybersecurity. However, the processes underlying the concept and the nudge’s effectiveness in different contexts, and in the long term, are still poorly understood. Our research thus first reviewed the nudge concept and differentiated it from other interventions before applying it to the cybersecurity area. We then carried out an empirical study to assess the effectiveness of three different nudge-related interventions on four types of cybersecurity-specific decisions. Our study demonstrated that the combination of a simple nudge and information provision, termed a “hybrid nudge,” was at least as, and in some decision contexts even more effective in encouraging secure choices as the simple nudge on its own. This indicates that the inclusion of information when deploying a nudge, thereby increasing the intervention’s transparency, does not necessarily diminish its effectiveness. A follow-up study explored the educational and long-term impact of our tested nudge interventions to encourage secure choices. The results indicate that the impact of the initial nudges, of all kinds, did not endure. We conclude by discussing our findings and their implications for research and practice.

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Keywords

QA75, 330, Electronic computers. Computer science, 320

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    selected citations
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    76
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
76
Top 1%
Top 10%
Top 1%
Green
bronze