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Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations

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  • Kim, Jungkeun
  • Kim, Jeong Hyun
  • Kim, Changju
  • Park, Jooyoung

Abstract

This research examines how individuals respond differently to recommendation options generated by ChatGPT, an AI-powered language model, in five studies. In contrast to previous research on choice overload, Studies 1 and 2 demonstrate that people tend to respond positively to a large number of recommendation options (60 options), revealing diverse consumer perceptions of AI-generated recommendations. Studies 3 and 4 further illustrate the moderating effect of recommendation agents and indicate that choice overload elicits distinct patterns of consumer reactions depending on whether the recommendations are from a human or AI agent. Lastly, Study 5 directly measures consumer preferences for recommendation agents, revealing a general preference for ChatGPT, particularly when a large number of options are available. These findings have significant implications for recommendation system design and user preferences regarding AI-powered recommendations.

Suggested Citation

  • Kim, Jungkeun & Kim, Jeong Hyun & Kim, Changju & Park, Jooyoung, 2023. "Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:joreco:v:75:y:2023:i:c:s0969698923002412
    DOI: 10.1016/j.jretconser.2023.103494
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    Cited by:

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    3. Kim Shin Young & Sang-Gun Lee & Ga Youn Hong, 2024. "User satisfaction with the service quality of ChatGPT," Service Business, Springer;Pan-Pacific Business Association, vol. 18(3), pages 417-431, December.
    4. Cui, Yuanyuan (Gina) & van Esch, Patrick & Phelan, Steven, 2024. "How to build a competitive advantage for your brand using generative AI," Business Horizons, Elsevier, vol. 67(5), pages 583-594.
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    6. Benjamin J. McCloskey & Phillip M. LaCasse & Bruce A. Cox, 2024. "Natural language processing analysis of online reviews for small business: extracting insight from small corpora," Annals of Operations Research, Springer, vol. 341(1), pages 295-312, October.
    7. Lee, Garim & Kim, Hye-Young, 2024. "Human vs. AI: The battle for authenticity in fashion design and consumer response," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).

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