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Understanding User Preferences of Digital Privacy Nudges – A Best-Worst Scaling Approach

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Title:Understanding User Preferences of Digital Privacy Nudges – A Best-Worst Scaling Approach
Authors:Schöbel, Sofia
Barev, Torben
Janson, Andreas
Hupfeld, Felix
Leimeister, Jan Marco
Keywords:Behavioral Economics in the Digital Economy: Digital Nudging and Interface Design
best-worst scaling
nudging
privacy nudging
user preferences
Date Issued:07 Jan 2020
Abstract:Digital nudging in privacy has become more important to protect users of information systems while working with privacy-related data. Nudging is about altering a user’s behavior without forbidding any options. Several approaches exist to “nudge” users to change their behavior. Regarding the usage of digital privacy nudges, research still has to understand the meaning and relevance of individual nudges better. Therefore, this paper compares the preferences of users for different digital nudges. To achieve this goal, it presents the results of a so-called best-worst scaling. This study contributes to theory by providing a better understanding of user preferences regarding design variations of digital nudges. We support practitioners by giving implications on how to design digital nudges in terms of user preferences.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/64221
ISBN:978-0-9981331-3-3
DOI:10.24251/HICSS.2020.479
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Behavioral Economics in the Digital Economy: Digital Nudging and Interface Design


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