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Behavioural Public Policy
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Research Collection
Article . 2025
License: CC BY
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Dark patterns and consumer vulnerability

Authors: Amit Zac; Yu-Chun Huang; Amédée von Moltke; Christopher Decker; Ariel Ezrachi;

Dark patterns and consumer vulnerability

Abstract

Abstract Dark patterns that manipulate consumer behaviour are now a pervasive feature of digital markets. Depending on the choice architecture utilised, they can affect the perception, behaviour and purchasing patterns of online consumers. Using a novel empirical design, we find strong evidence that individuals across all groups are susceptible to dark patterns, and only weak evidence that user susceptibility is materially affected by commonly used general proxies for consumer vulnerability (such as income, educational attainment or age). Our conclusions provide empirical support for broad restrictions on the use of dark patterns, such as those contained in the EU’s Digital Services Act, that protect all consumer groups. Our study also finds that added friction, in the form of required payment action following successful deployment of dark patterns, reduces their effectiveness. This insight highlights the instances in which dark patterns would be most effective – when no further action is required by the user. Consumer vulnerability is therefore more pronounced when dealing with online providers who store users’ payment details and can rely on a ‘single click’ to complete the purchase.

Countries
Switzerland, United Kingdom
Related Organizations
Keywords

competition law, online behavioural manipulation, online platforms, competition law; dark patterns; online behavioural manipulation; online platforms, dark patterns

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
9
Top 10%
Average
Top 10%
Green
hybrid
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