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User preferences for privacy features in digital assistants

Author

Listed:
  • Frank Ebbers

    (Fraunhofer Institute for Systems and Innovation Research ISI)

  • Jan Zibuschka

    (Robert Bosch GmbH)

  • Christian Zimmermann

    (Robert Bosch GmbH)

  • Oliver Hinz

    (Goethe University Frankfurt)

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.

Suggested Citation

  • Frank Ebbers & Jan Zibuschka & Christian Zimmermann & Oliver Hinz, 2021. "User preferences for privacy features in digital assistants," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 411-426, June.
  • Handle: RePEc:spr:elmark:v:31:y:2021:i:2:d:10.1007_s12525-020-00447-y
    DOI: 10.1007/s12525-020-00447-y
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    Cited by:

    1. Annette Wenninger & Daniel Rau & Maximilian Röglinger, 2022. "Improving customer satisfaction in proactive service design," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1399-1418, September.
    2. Valerie Graf-Drasch & Maximilian Röglinger & Annette Wenninger & Sabiölla Hosseini, 2022. "A Contextualized Acceptance Model for Proactive Smart Services," Schmalenbach Journal of Business Research, Springer, vol. 74(3), pages 345-387, September.
    3. Katharina Baum & Olga Abramova & Stefan Meißner & Hanna Krasnova, 2023. "The effects of targeted political advertising on user privacy concerns and digital product acceptance: A preference-based approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    4. Rainer Alt, 2021. "Electronic Markets on digital platforms and AI," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 233-241, June.
    5. Kim, Doha & Song, Yeosol & Kim, Songyie & Lee, Sewang & Wu, Yanqin & Shin, Jungwoo & Lee, Daeho, 2023. "How should the results of artificial intelligence be explained to users? - Research on consumer preferences in user-centered explainable artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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    More about this item

    Keywords

    Information privacy; Digital assistant; Intelligent personal assistant; Choice-based conjoint analysis; Privacy preferences; Internet of things;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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