Examining user migration intention from social Q&A communities to generative AI

被引:0
作者
Zhou, Tao [1 ]
Wu, Xiaoying [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Management, Hangzhou 310018, Peoples R China
来源
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS | 2024年 / 11卷 / 01期
基金
中国国家自然科学基金;
关键词
CONTINUANCE INTENTION; INFORMATION QUALITY; SWITCHING BEHAVIOR; ONLINE; PULL; FLOW; PUSH; ACCEPTANCE; OVERLOAD;
D O I
10.1057/s41599-024-03540-1
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
As an emerging application, generative AI has attracted many users to conduct question and answer (Q&A), which may lead to their defection from social Q&A communities. Based on the push-pull-mooring (PPM) model, this research examined user migration intention from social Q&A communities to generative AI. Data were analyzed using a mixed method of SEM and fsQCA. The results revealed that migration intention is influenced by a combination of push factors (information overload and community fatigue), pull factors (perceived anthropomorphism, perceived accuracy, perceived trustworthiness, and flow experience), and mooring factor (social influence). The fsQCA results identified three main paths leading to migration intention. These results imply that Q&A communities need to reduce information overload and mitigate users' fatigue in order to retain them and achieve a sustainable development.
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页数:10
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