인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
DBpia Top 5%
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
AI-Generated music, which combines artificial intelligence technology with music creation, has garnered significant attention in both academia and industry in recent years. Platforms like Suno AI offer accessible music creation tools for ordinary users and provide fresh creative insights for professional musicians. However, the factors that influence user acceptance of AI-Generated music remain underexplored. This study, based on data from 302 valid questionnaires, utilizes SmartPLS and SPSS for structural equation modeling to investigate the impact of product heterogeneous preference on user acceptance. The study also examines the mediating role of sense of competence and the moderating effects of consumer expertise and AI personification. The findings reveal that product heterogeneous preference significantly reduces user acceptance of AI-Generated music, both directly and through its impact on the sense of competence. However, AI personification can mitigate this negative effect. These insights deepen our understanding of user interaction mechanisms within the creative domain of generative AI and offer practical guidance for enhancing AI-Generated music platforms. By addressing the psychological factors influencing user acceptance, this research provides a theoretical foundation for optimizing AI-Generated music systems to better align with user preferences and improve overall user experience. Additionally, the study offers valuable perspectives on how artificial intelligence is reshaping human aesthetic experiences and creative practices.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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