Artificial intelligence-generated or user-generated content: the influence of episodic future thinking on age-related pre-travel information preference
Hao Zhang et al.
Abstract
Purpose This study aims to explore the preference differences for two mainstream types of tourism digital information, artificial intelligence-generated content (AIGC) and user-generated content (UGC), between tourists of different age groups and highlights the key role of episodic future thinking in shaping tourists’ preferences. Design/methodology/approach A sequential explanatory mixed-methods design was used. It included a scenario-based experiment, a large-scale survey and adapted autobiographical interviews. Findings Older tourists show a stronger preference for AIGC, while young tourists prefer UGC. Age-related differences in episodic future thinking (contextual clarity and self-engagement level) lead to varying information demands in terms of characteristics and requirements. These demands, in turn, shape tourists’ overall information preferences. Additionally, travel experience further moderates these information preference effect. Originality/value This study offers new insights into information preference mechanisms and enriches age-based tourist information behavior theory. The findings also provide practical guidance for the development of age-appropriate tourism information products and services.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.