사용자 경험 기반 중국 음악 애플리케이션 이용 연구 = A Study on the User Experience-Based Music Applications Usage in China

다국어 초록 (Multilingual Abstract)

With the advancement of digital content platforms, music applications have established themselves as key mediums for emotional content consumption. Particularly from the user experience design perspective, personalized content delivery and emotion-centered music platforms are gaining attention as major factors determining the competitiveness of music applications. Accordingly, this study aims to empirically analyze how attributes such as content quality, interface design, interactivity, and recommendation systems of music platforms structurally affect users' psychological responses toward music applications and the formation of their continuance usage intention. For this purpose, the Stimulus-Organism-Response (SOR) theory was adopted as the analytical framework, and the Expectation-Confirmation Theory (ECT) was complementarily applied to explain continuance usage intention.
To examine users' experiences with music applications, this study conducted a survey targeting users of the music platforms NetEase Cloud Music and QQ Music. A total of 368 questionnaires were collected, and the gathered data were statistically analyzed using quantitative research methods. Specifically, exploratory factor analysis and confirmatory factor analysis were performed to verify the reliability and validity of the measurement tools. Structural equation modeling was employed to examine the relationships between variables. Furthermore, a multi-group analysis was conducted to analyze structural differences according to platform type.
As a result, attributes of music platforms such as content quality, interactivity, and recommendation systems were found to have a significant impact on users' app dependence and satisfaction. However, in terms of continuous usage intention, while user satisfaction was identified as the most critical antecedent explaining continuous usage intention, app dependence was found to have no direct effect. This suggests that music platform users' habitual use of the app does not necessarily translate into long-term usage intention. In other words, continuous usage intention is formed through users' cognitive evaluation and satisfaction with the service experiences of the music platform.
Meanwhile, in the multi-group analysis, differences in influence between the two platforms were observed. On NetEase Cloud Music, interactivity played a significant role in forming app dependence and continued use intention, whereas on QQ Music, content quality and recommendation system features were found to influence continued use intention and satisfaction. This suggests that the mechanisms of user behavior in music applications are formed differently depending on the service strategies and experience design directions of the music platforms.
This study focused on users' experiences with music platforms in order to encourage the continued use of music applications, and its significance lies in empirically demonstrating the importance of quality management for platforms. Based on this study, future research is expected to explore the usage behavior of digital content platforms in greater depth.

목차 (Table of Contents)

• <목 차>
• ABSTRACT
• 제1장 서론 1
• 1.1 연구의 배경 및 목적 1
• 1.2 연구의 구성 3
• 제2장 이론적 배경 4
• 2.1 디지털 플랫폼(Digital Platforms) 4
• 2.2 음악 애플리케이션 및 선행연구 5
• 2.3 사용의도에 관한연구 6
• 2.4 SOR 모델 8
• 2.5 변수의 정의 9
• 제3장 연구 가설 및 연구 모형 16
• 3.1 연구모형 16
• 3.2 연구가설 17
• 제4장 실증분석 23
• 4.1 변수의 조작적 정의 및 설문지 구성 23
• 4.2 조사대상 및 자료수집 26
• 4.3 분석방법 27
• 4.4 인구통계학적 분석 결과 28
• 4.5 신뢰도 검증 결과(Internal Consistency Reliability Analysis) 30
• 4.6 탐색적 요인분석 결과(Exploratory Factor Analysis, EFA) 30
• 4.7 확인적 요인분석 결과 34
• 4.8 상관관계 및 판별타당성 검증 결과 36
• 4.9 가설 검증 결과 38
• 4.10 플랫폼 유형의 조절효과 분석 결과 39
• 제5장 결론 44
• 5.1 결과 요약 44
• 5.2 연구의 시사점 45
• 5.3 연구의 한계점 및 향후 연구 방향 46
• 참고문헌 47
• <부록> 설문조사 70
• <표 차례>
• <표 1> 플랫폼 관련 선행연구 6
• <표 2> 사용의도에 관한 선행연구 7
• <표 3> 조사대상 및 자료 수집 절차 26
• <표 4> 표본 대상의 인구 통계적 분석 29
• <표 5> 신뢰도 검증 결과 30
• <표 6> 탐색적 요인분석 결과 31
• <표 7> 설명된 총 분산 32
• <표 8> 동일방법편의 검증 결과 33
• <표 9> 확인적 요인분석 결과 35
• <표 10> 모형의 적합도 지수 36
• <표 11> 상관관계 분석 결과 37
• <표 12> HTMT(Heterotrait-Monotrait Ratio of Correlations)분석 결과 37
• <표 13> 연구 가설 검증 결과 39
• <표 14> 구조모형의 적합도 39
• <표 15> 다집단 분석 결과 42
• <표 16> 구조모형의 적합도 43
• <그림 차례>
• <그림 1> 연구모형 16