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AI recommendation vs. crowdsourced recommendation vs. travel expert recommendation: The moderating role of consumption goal on travel destination decision

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  • Young Eun Park
  • Hyunsang Son

Abstract

This research investigates the effects of recommender type (AI versus crowdsourcing versus travel expert) and consumption goal (utilitarian versus hedonic) on consumer responses to travel destination recommendation email advertisements. Across two experiments, findings reveal that consumers held the most favorable attitude toward email advertisements featuring travel expert recommendations compared to crowdsourced or AI-generated suggestions. Notably, this study highlights the moderating role of consumption goal type (utilitarian vs. hedonic) in shaping attitudes toward the recommendation source. Specifically, consumers preferred ads featuring AI-generated recommendations for utilitarian travel goals (e.g., business trips), while for hedonic travel goals (e.g., romantic getaways), they favored ads with crowdsourced suggestions. Through serial mediation (Study 1) and moderated serial mediation (Study 2), this research further elucidates the underlying psychological mechanisms driving these effects.

Suggested Citation

  • Young Eun Park & Hyunsang Son, 2025. "AI recommendation vs. crowdsourced recommendation vs. travel expert recommendation: The moderating role of consumption goal on travel destination decision," PLOS ONE, Public Library of Science, vol. 20(3), pages 1-25, March.
  • Handle: RePEc:plo:pone00:0318719
    DOI: 10.1371/journal.pone.0318719
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    1. Noel Scott & Christine Green & Sheranne Fairley, 2016. "Investigation of the use of eye tracking to examine tourism advertising effectiveness," Current Issues in Tourism, Taylor & Francis Journals, vol. 19(7), pages 634-642, June.
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