Push–Pull–Mooring Effects on Travelers’ Switching Behavior from Online Travel Communities to Generative Artificial Intelligence Services: An Integrated Theoretical Framework
本研究整合推-拉-锚定理论、压力-应变-结果模型和信息系统成功模型，基于445名旅行者调查数据，发现信息过载和沟通过载促使旅行者转向生成式人工智能服务，而惯性是主要障碍，并识别出三种高转换意愿的路径。
The rise of generative artificial intelligence (GenAI) is transforming how travelers seek tourism information and challenging traditional online travel communities (OTCs). Integrating push–pull–mooring theory with the stressor–strain–outcome and information systems success models, we investigate why travelers intend to switch from OTCs to GenAI services. Using survey data from 445 travelers, we apply structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA). Results reveal that information overload and communication overload in OTCs drive fatigue and prompt travelers to adopt GenAI services, which offer superior system quality and information quality and thus increase travelers’ satisfaction. Inertia remains a significant barrier, whereas switching cost has minimal impact. Complementing the net effects, the fsQCA identifies three distinct configurational pathways to high switching intention. The findings suggest integrating human-generated content and GenAI into tourism information systems to reduce cognitive strain, improve relevance, and elevate satisfaction.