Tourists and artificial intelligence-LLM interaction: The power of forgiveness

Abstract

Artificial intelligence large language models (AI-LLMs) can become valuable travel advisors but often suffer from hallucinations that can diminish consumers’ confidence in their results. This study explores the relationship between tourists and AI large language model interactions by analyzing how (i) attachment-aversion affects the motivational strength for using AI large language models as travel advisors and (ii) the moderation role of forgiveness in the relationship between the symbolic benefits consumers get from using those AI advisors and the attachment-aversion relationship. A sample of 451 participants in a Qualtrics survey was used to test the conceptual proposed framework. Findings reveal the important role of enriching the self and enticing the self in shaping attachment-aversion relationships. Forgiveness strengthens the relationship between enriching the self (symbolic benefits) and attachment-aversion. This research can guide managers in using its findings to develop customised AI-LLMs that foster engaging dialogues with travellers, enhance feelings of attachment, and forgive any potential missteps throughout the relationship.