Publication | Open Access
Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations
112
Citations
55
References
2023
Year
EngineeringBehavioral Decision MakingConsumer ResearchSocial InfluenceCommunicationRecommendation OptionsPreference LearningManagementDecision TheoryPreference ModelingPredictive AnalyticsUser ExperienceConversational Recommender SystemMarketingChatgpt RecommendationsGroup RecommendersInteractive MarketingUser PreferencesHuman-ai InteractionHuman-computer InteractionChoice OverloadPreference ElicitationDecision SciencePersuasion
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.
| Year | Citations | |
|---|---|---|
Page 1
Page 1