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AI trust divide: How recruiter-candidate roles shape tourism personnel decision-making

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  • Hu, Jihao
  • Huang, GuoQiong Ivanka
  • Wong, IpKin Anthony
  • Wan, Lisa C.

Abstract

The artificial intelligence revolution has prompted tourism organizations to consider whether and how to use AI to improve efficiency and create value, particularly in areas such as personnel selection. Through five experimental studies (N = 2199), this paper first reveals that a trust divide exists between job candidates and recruiters in travel agencies. We then investigate how the consideration focus of personnel attributes mediates the impact of roles on trust through thought-listing (Study 1), mediation-by-moderation (Studies 2a & 2b), and self-reported measures (Study 3). To mitigate this misalignment, we examine the AI–human assemblage design and offer an optimal way to bridge the trust divide (Study 4). The current research extends motivated reasoning theory and provides novel insights into practice.

Suggested Citation

  • Hu, Jihao & Huang, GuoQiong Ivanka & Wong, IpKin Anthony & Wan, Lisa C., 2024. "AI trust divide: How recruiter-candidate roles shape tourism personnel decision-making," Annals of Tourism Research, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:anture:v:109:y:2024:i:c:s0160738324001373
    DOI: 10.1016/j.annals.2024.103860
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