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Recommendation agents: an analysis of consumers’ risk perceptions toward artificial intelligence

Author

Listed:
  • Simoni F. Rohden

    (IPAM Lisboa – Portuguese Marketing Management Institute)

  • Diully Garcia Zeferino

    (Unisinos Business School – Unisinos University)

Abstract

Tools that use artificial intelligence to improve consumer experiences and automate processes, such as recommendation agents have been widely adopted by companies. However, the use of this type of technology can increase a user’s perception of a risk to data privacy. This article aims to go more in-depth into what is known about the variables that impact this perception of risk related to recommendation agents. By way of an exploratory study with in-depth interviews followed by a survey, it was possible to identify how aspects such as a concern with data and the perceived risk in online shopping increase the sense of a risk to privacy. Consumers are generally unaware of how recommendation agents work, which makes them unsure about their usability and purpose. Consumer trust, however, mediates this relationship by mitigating the negative effects of risk perception.

Suggested Citation

  • Simoni F. Rohden & Diully Garcia Zeferino, 2023. "Recommendation agents: an analysis of consumers’ risk perceptions toward artificial intelligence," Electronic Commerce Research, Springer, vol. 23(4), pages 2035-2050, December.
    • Handle: RePEc:spr:elcore:v:23:y:2023:i:4:d:10.1007_s10660-022-09626-9
    DOI: 10.1007/s10660-022-09626-9
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    References listed on IDEAS

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    4. Rahim Rashidi & Keyhan Khamforoosh & Amir Sheikhahmadi, 2022. "Proposing improved meta-heuristic algorithms for clustering and separating users in the recommender systems," Electronic Commerce Research, Springer, vol. 22(2), pages 623-648, June.
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    Full references (including those not matched with items on IDEAS)

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