The proliferation of generative AI (GenAI) has led to a growing number of users relying on it for travel planning; however, users' evaluation of AI-generated content (AIGC) quality in travel planning remain unclear. From the perspective of users' subjective perception, this study first draws upon information quality theory, the technology acceptance model and user experience theory to construct an AIGC quality evaluation framework comprising 10 indicators across 3 dimensions: content quality, user experience and itinerary planning. A scenario-based experiment was then employed, in which 4 mainstream Chinese GenAI platforms were selected to complete the same travel planning task, with user-generated content (UGC) from social media serving as a control condition. A questionnaire survey was further conducted to collect users' evaluation of AIGC quality, yielding 211 valid responses. The results show that: first, users' evaluation of AIGC quality exhibit significant group heterogeneity. Specifically, males give significantly lower ratings for personalization, whereas females give significantly lower ratings for comprehensibility and itinerary rationality; users aged 20-30 have higher expectations regarding personalization, whilst those under 20 have higher expectations regarding itinerary rationality, and sensitivity to timeliness increases with age; frequent users rate usefulness higher but assign lower scores to personalization. Second, users' overall evaluation of AIGC quality is significantly better than their evaluation of UGC quality, yet they perceive the timeliness of AIGC as inferior to that of UGC. Third, regression analysis indicates that usage frequency exerts a significant positive influence on users' overall quality evaluation of AIGC, while education level exerts a significant negative influence. This study enriches user-centred research on AIGC quality evaluation and provides user-side empirical evidence for the technological optimisation of AIGC and the intelligent upgrading of tourism information services.

Fukang Fang, Xue Wang, Guifang Zhou. A Study on Users' Evaluation of AIGC Quality in Travel Planning. Academic Journal of Computing & Information Science (2026), Vol. 9, Issue 9: 1-7. https://doi.org/10.25236/AJCIS.2026.090901.

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