User preferences for privacy features in digital assistants
Frank Ebbers (),
Jan Zibuschka (),
Christian Zimmermann () and
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Frank Ebbers: Fraunhofer Institute for Systems and Innovation Research ISI
Jan Zibuschka: Robert Bosch GmbH
Christian Zimmermann: Robert Bosch GmbH
Electronic Markets, 2021, vol. 31, issue 2, No 11, 426 pages
Abstract Digital assistants (DA) perform routine tasks for users by interacting with the Internet of Things (IoT) devices and digital services. To do so, such assistants rely heavily on personal data, e.g. to provide personalized responses. This leads to privacy concerns for users and makes privacy features an important component of digital assistants. This study examines user preferences for three attributes of the design of privacy features in digital assistants, namely (1) the amount of information on personal data that is shown to the user, (2) explainability of the DA’s decision, and (3) the degree of gamification of the user interface (UI). In addition, it estimates users’ willingness to pay (WTP) for different versions of privacy features. The results for the full sample show that users prefer to understand the rationale behind the DA’s decisions based on the personal information involved, while being given information about the potential impacts of disclosing specific data. Further, the results indicate that users prefer to interact with the DA’s privacy features in a serious game. For this product, users are willing to pay €21.39 per month. In general, a playful design of privacy features is strongly preferred, as users are willing to pay 23.8% more compared to an option without any gamified elements. A detailed analysis identifies two customer clusters “Best Agers” and “DA Advocates”, which differ mainly in their average age and willingness to pay. Further, “DA Advocates” are mainly male and more privacy sensitive, whereas “Best Agers” show a higher affinity for a playful design of privacy features.
Keywords: Information privacy; Digital assistant; Intelligent personal assistant; Choice-based conjoint analysis; Privacy preferences; Internet of things (search for similar items in EconPapers)
JEL-codes: O33 (search for similar items in EconPapers)
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