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    AIUGC 환경에서 사용자 경험과 심리적 임파워먼트가 COBRAs에 미치는 영향

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    https://www.riss.kr/link?id=T17568102

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Generative AI is reshaping how user-generated content is produced, edited, and circulated on social media platforms. Content creation is gradually moving from a user-only mode toward a collaborative mode in which users remain the main agents while AI provides supportive assistance. Unlike AI-generated content (AIGC), in which AI functions as the primary content generator, AI-assisted User-Generated Content (AIUGC) refers to a user-led content production condition in which AI supports ideation, expression refinement, information organization, and visual presentation while users retain creative intention and final judgment. Focusing on this context, this study examines how AIUGC influences consumers’ online brand-related activities (COBRAs) through user experience (UX) and psychological empowerment (PE), and whether this pathway differs across stages of the brand life cycle (BLC).
    Taking Xiaohongshu image–text posts as the platform context and Chinese freshly made beverage chain brands as the brand context, this study adopted a 2 × 2 between-subjects scenario experiment. The experimental conditions consisted of content production mode (AIUGC vs. UGC) and brand life cycle stage (growth stage vs. maturity stage). A total of 431 valid responses were collected. The hypotheses were tested using confirmatory factor analysis, structural equation modeling, and Bootstrap analysis.
    The results showed that, under the experimental conditions of this study, AIUGC had a modest but significant positive effect on user experience compared with UGC. This finding does not suggest that AIUGC is inherently superior to UGC or that it can replace user-generated content. Rather, it indicates that when user agency is maintained and the boundary of AI assistance is clearly disclosed, AIUGC can function as a front-end content contact condition that helps users understand, evaluate, and enter the interaction context more smoothly. User experience positively influenced psychological empowerment, and psychological empowerment, in turn, significantly promoted participation tendency in COBRAs. User experience and psychological empowerment also formed a sequential mediating pathway between AIUGC and COBRAs. These findings indicate that AIUGC does not directly or automatically lead to deeper brand-related participation. Instead, its effect is transmitted through a psychological transformation process of experience evaluation, agency perception, and participation deepening.
    The results further showed that brand life cycle moderated the effect of AIUGC on user experience. The effect was stronger in the growth-stage brand condition and relatively weaker in the maturity-stage brand condition. The moderated sequential indirect effect was also supported, suggesting that the pathway from AIUGC to COBRAs through user experience and psychological empowerment differs across brand development stages. This finding indicates that AIUGC should not be understood as a universally effective content strategy, but as a conditional communication and design resource whose effect depends on brand stage, content presentation, creation disclosure, and users’ interpretation of AI assistance.
    This study extends AIUGC research beyond content production efficiency by positioning AIUGC within a sequential relationship among user experience, psychological empowerment, and brand-related participation. From the perspective of visual communication design, this study interprets Xiaohongshu posts as image–text interfaces composed of visual information organization, creation disclosure cues, and interaction entry points. In this sense, AIUGC is not merely a technical tool for producing content, but a content contact condition that shapes how users understand brand information, form brand experience, perceive their own agency, and enter interaction. The findings suggest that the value of AIUGC lies not in replacing user expression, but in supporting clearer understanding, maintaining user agency, and designing differentiated social media brand communication strategies across different stages of the brand life cycle. Future research should further examine credibility, authenticity, and transparency as key variables in AIUGC-based brand communication and visual interaction design.
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    Generative AI is reshaping how user-generated content is produced, edited, and circulated on social media platforms. Content creation is gradually moving from a user-only mode toward a collaborative mode in which users remain the main agents while AI ...

    Generative AI is reshaping how user-generated content is produced, edited, and circulated on social media platforms. Content creation is gradually moving from a user-only mode toward a collaborative mode in which users remain the main agents while AI provides supportive assistance. Unlike AI-generated content (AIGC), in which AI functions as the primary content generator, AI-assisted User-Generated Content (AIUGC) refers to a user-led content production condition in which AI supports ideation, expression refinement, information organization, and visual presentation while users retain creative intention and final judgment. Focusing on this context, this study examines how AIUGC influences consumers’ online brand-related activities (COBRAs) through user experience (UX) and psychological empowerment (PE), and whether this pathway differs across stages of the brand life cycle (BLC).
    Taking Xiaohongshu image–text posts as the platform context and Chinese freshly made beverage chain brands as the brand context, this study adopted a 2 × 2 between-subjects scenario experiment. The experimental conditions consisted of content production mode (AIUGC vs. UGC) and brand life cycle stage (growth stage vs. maturity stage). A total of 431 valid responses were collected. The hypotheses were tested using confirmatory factor analysis, structural equation modeling, and Bootstrap analysis.
    The results showed that, under the experimental conditions of this study, AIUGC had a modest but significant positive effect on user experience compared with UGC. This finding does not suggest that AIUGC is inherently superior to UGC or that it can replace user-generated content. Rather, it indicates that when user agency is maintained and the boundary of AI assistance is clearly disclosed, AIUGC can function as a front-end content contact condition that helps users understand, evaluate, and enter the interaction context more smoothly. User experience positively influenced psychological empowerment, and psychological empowerment, in turn, significantly promoted participation tendency in COBRAs. User experience and psychological empowerment also formed a sequential mediating pathway between AIUGC and COBRAs. These findings indicate that AIUGC does not directly or automatically lead to deeper brand-related participation. Instead, its effect is transmitted through a psychological transformation process of experience evaluation, agency perception, and participation deepening.
    The results further showed that brand life cycle moderated the effect of AIUGC on user experience. The effect was stronger in the growth-stage brand condition and relatively weaker in the maturity-stage brand condition. The moderated sequential indirect effect was also supported, suggesting that the pathway from AIUGC to COBRAs through user experience and psychological empowerment differs across brand development stages. This finding indicates that AIUGC should not be understood as a universally effective content strategy, but as a conditional communication and design resource whose effect depends on brand stage, content presentation, creation disclosure, and users’ interpretation of AI assistance.
    This study extends AIUGC research beyond content production efficiency by positioning AIUGC within a sequential relationship among user experience, psychological empowerment, and brand-related participation. From the perspective of visual communication design, this study interprets Xiaohongshu posts as image–text interfaces composed of visual information organization, creation disclosure cues, and interaction entry points. In this sense, AIUGC is not merely a technical tool for producing content, but a content contact condition that shapes how users understand brand information, form brand experience, perceive their own agency, and enter interaction. The findings suggest that the value of AIUGC lies not in replacing user expression, but in supporting clearer understanding, maintaining user agency, and designing differentiated social media brand communication strategies across different stages of the brand life cycle. Future research should further examine credibility, authenticity, and transparency as key variables in AIUGC-based brand communication and visual interaction design.

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    목차 (Table of Contents)

    • 1. 서론 1
    • 1.1. 연구 필요성 및 목적 1
    • 1.2. 연구 방법 및 범위 5
    • 1.2.1. 연구 범위 및 이론적 틀 5
    • 1.2.2. 연구 대상 및 범위 한정 6
    • 1. 서론 1
    • 1.1. 연구 필요성 및 목적 1
    • 1.2. 연구 방법 및 범위 5
    • 1.2.1. 연구 범위 및 이론적 틀 5
    • 1.2.2. 연구 대상 및 범위 한정 6
    • 1.2.3. 연구 절차 7
    • 1.3. 선행연구 검토 10
    • 1.3.1. Gen-AI와 콘텐츠 생산 관련 연구 10
    • 1.3.2. 인공지능 환경에서의 콘텐츠 생산과 COBRAs 연구 12
    • 1.3.3. 사용자 경험과 심리적 임파워먼트 관련 연구 13
    • 1.3.4. 브랜드 생애주기와 커뮤니케이션 전략 연구 15
    • 1.3.5. 선행연구와의 차별성 17
    • 2. 이론적 배경 19
    • 2.1. AIUGC의 연구 범위 설정 및 이론적 전제 19
    • 2.1.1. 콘텐츠 생산 방식의 변화와 AIUGC의 위치 19
    • 2.1.2. UGC와 AIUGC의 비교 구조 20
    • 2.1.3. AIUGC의 개념적 공감대와 이론적 경계 21
    • 2.2. 사용자 경험 이론 23
    • 2.2.1. 사용자 경험의 정의와 디지털 환경에서의 확장 23
    • 2.2.2. 인공지능 기반 콘텐츠 생산과 사용자 경험 24
    • 2.2.3. 본 연구 맥락에서의 사용자 경험 26
    • 2.3. 심리적 임파워먼트 이론 27
    • 2.3.1. 임파워먼트와 심리적 임파워먼트 27
    • 2.3.2. 심리적 임파워먼트의 구성 요소 28
    • 2.3.3. 디지털 상호작용 및 AIUGC 환경에서의 심리적 임파워먼트 형성 29
    • 2.4. 소비자 온라인 브랜드 관련 활동 31
    • 2.4.1. 소비자 온라인 브랜드 관련 활동의 개념 31
    • 2.4.2. 소셜미디어 플랫폼과 AI 환경에서의 COBRAs 연구 확장 32
    • 2.5. 브랜드 생애주기 이론과 커뮤니케이션 목표 34
    • 2.5.1. 브랜드 생애주기 단계 구분과 커뮤니케이션 목표 35
    • 2.5.2. 브랜드 생애주기의 조절 효과 37
    • 3. 연구설계 38
    • 3.1. 연구 개요 및 설계 38
    • 3.1.1. 연구설계 개요 38
    • 3.1.2. 실험 설계 38
    • 3.1.3. 실험 절차 및 데이터 품질 통제 42
    • 3.2. 연구모형 및 가설 44
    • 3.2.1. 연구모형 44
    • 3.2.2. 연구문제 45
    • 3.2.3. 연구가설 45
    • 3.3. 변수의 조작적 정의 46
    • 3.3.1. 독립변수: 콘텐츠 생산 방식 46
    • 3.3.2. 매개 변수 1: 사용자 경험 47
    • 3.3.3. 매개 변수 2: 심리적 임파워먼트 49
    • 3.3.4. 종속 변수: 소비자 온라인 브랜드 관련 활동 50
    • 3.3.5. 조절 변수: 브랜드 생애주기 51
    • 3.3.6. 통제 변수: 평가 초점 53
    • 3.3.7. 변수 및 측정 개요 53
    • 3.4. 설문 및 표본 54
    • 3.4.1. 설문 구조 및 측정 절차 54
    • 3.4.2. 표본 선정 및 자료 수집 57
    • 3.5. 자료 분석 전략 57
    • 3.5.1. 자료 준비 및 예비 점검 57
    • 3.5.2. 측정모형 검증 58
    • 3.5.3. 구조방정식모형 및 연쇄 매개효과 검증 59
    • 3.5.4. 조절효과 검증: 상호작용항 검증과 단순기울기 해석 59
    • 3.5.5. 조절된 연쇄 간접효과 검증 59
    • 3.6. 소결 60
    • 4. 실증 결과 61
    • 4.1. 표본 기술 및 기초 통계 61
    • 4.2. 측정모형 검증 결과 67
    • 4.2.1. 신뢰도 및 수렴타당도 68
    • 4.2.2. 측정모형의 전체 적합도 69
    • 4.2.3. 판별타당도 70
    • 4.3. 구조모형 검증 결과 72
    • 4.3.1. 주 경로 가설 검증 결과 73
    • 4.3.2. 연쇄 매개효과 검증 결과 77
    • 4.3.3. 조절 효과 검증 결과 79
    • 4.4. 가설 검증 결과 요약 및 단계 차이 해석 82
    • 4.5. 소결 84
    • 5. 결론 86
    • 5.1. 연구 성과 요약 86
    • 5.2. 시사점 및 제언 90
    • 5.2.1. 디자인학적 시사점 90
    • 5.2.2. 브랜드 커뮤니케이션 실무 제언 92
    • 5.2.3. 플랫폼 및 콘텐츠 창작자 제언 95
    • 5.3. 향후 연구 방향 96
    • 참고문헌 99
    • 부록 108
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