建议(编程)
类型学
旅游
抗性(生态学)
广告
业务
营销
计算机科学
社会学
地理
生态学
人类学
生物
考古
程序设计语言
作者
Siamak Seyfi,Abolfazl Siyamiyan Gorji,Tan Vo‐Thanh,Mustafeed Zaman
摘要
ABSTRACT Many travelers remain hesitant to rely on generative AI for travel planning, despite its growing presence in tourism services. While most existing studies emphasize adoption, this study shifts attention to the relatively underexplored issue of resistance. Drawing on Innovation Resistance Theory (IRT) and qualitative data from a developing country, we identify five core barriers to AI‐generated travel advice: usage, value, risk, image, and tradition. We propose a typology of traveler resistance comprising rejecters, postponers, and opinion leaders, each defined by distinct motivations, levels of engagement, and patterns of skepticism. Our findings show that resistance is not fixed but shaped by cultural norms, social context, and personal identity. In rethinking resistance as a situated practice rather than a static outcome, the study extends IRT within tourism research and offers practical guidance for designing AI‐based travel services that are culturally attuned, trust‐oriented, and responsive to the social meanings embedded in travel planning.
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