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      콘텐츠 원본성과 AI 서명이 소비자 반응에 미치는 영향 연구: 지각된 진정성과 도덕적 혐오의 매개효과 = The Impact of Content Originality and AI Authorship on Consumer Responses: Mediating Roles of Perceived Authenticity and Moral Disgust

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      https://www.riss.kr/link?id=T17370469

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This study examines how content originality and authorship (AI vs. human) influence consumers’ cognitive, emotional, and behavioral responses within the context of emotion-based marketing communication. As generative AI becomes widely adopted in producing emotional messages and brand storytelling, understanding how consumers interpret the source and authenticity of such content has become increasingly important. Reflecting this shift, the present research investigates how content type (original vs. replicated) affects perceived authenticity and moral disgust, and how these psychological variables mediate the formation of positive word-of-mouth and customer loyalty.

      Using the experimental data from Kirk and Givi, 2025 Study 6 of the original research, this study employs PROCESS Macro Models 6 and 83. Content type serves as the independent variable; perceived authenticity and moral disgust function as mediators; positive word-of-mouth and loyalty are treated as dependent variables; and authorship (AI vs. human) is incorporated as a moderator to test moderated mediation effects.

      The results indicate, first, that replicated content consistently and significantly undermines perceived authenticity, with the consequent reduction in authenticity serving as a significant determinant of increased moral disgust. Second, both authenticity and disgust significantly invoke positive word-of-mouth and loyalty, with two mediators acting in sequence within a stable "psychological chain mechanism." It is of particular importance that the type of content has no direct effect, which means that consumers do not react based on the information that content is replicated but rather on their judgments regarding the authenticity and ethical meaning of the content before forming behavioral intentions.

      Third, authorship moderation was one of the leading moderating factors at each significant stage of the chain mechanism. Under human authorship, replicated content significantly decreased perceived authenticity, which raised moral disgust and culminated in adverse behavioral outcomes. For example, consumers react with less severity to replicated content with AI authorship, and the degree of adverse psychological impact is significantly reduced. This indicates that consumers have much higher expectations of "emotional authenticity" and "creative responsibility" from human creators while applying those expectations much less rigorously to AI, which leads to a more negligible psychological gap when encountering replicated content made by AI.

      Overall, the findings demonstrate that in the era of artificial intelligence, content originality, authenticity, ethical perception, and authorship cues collectively shape consumer judgment. These factors do not operate in isolation but interact closely to influence consumer evaluation processes. Particularly in emotional marketing contexts, human-authored content is subject to stricter scrutiny regarding sincerity and ethicality, implying that brands must carefully consider how authorship decisions shape consumer interpretation. Practically, when content relies heavily on emotional expression, uniqueness, and sincerity, human authorship may be more persuasive—but only if originality is ensured. Conversely, for standardized or repetitive messages, AI authorship may help reduce expectation gaps and lower the risk of negative evaluation. As AI-generated content becomes more prevalent, brands must develop strategies that integrate human creativity with AI-generated materials to maintain consistency between content form and authorship, thereby better managing consumer psychological expectations.
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      This study examines how content originality and authorship (AI vs. human) influence consumers’ cognitive, emotional, and behavioral responses within the context of emotion-based marketing communication. As generative AI becomes widely adopted in pro...

      This study examines how content originality and authorship (AI vs. human) influence consumers’ cognitive, emotional, and behavioral responses within the context of emotion-based marketing communication. As generative AI becomes widely adopted in producing emotional messages and brand storytelling, understanding how consumers interpret the source and authenticity of such content has become increasingly important. Reflecting this shift, the present research investigates how content type (original vs. replicated) affects perceived authenticity and moral disgust, and how these psychological variables mediate the formation of positive word-of-mouth and customer loyalty.

      Using the experimental data from Kirk and Givi, 2025 Study 6 of the original research, this study employs PROCESS Macro Models 6 and 83. Content type serves as the independent variable; perceived authenticity and moral disgust function as mediators; positive word-of-mouth and loyalty are treated as dependent variables; and authorship (AI vs. human) is incorporated as a moderator to test moderated mediation effects.

      The results indicate, first, that replicated content consistently and significantly undermines perceived authenticity, with the consequent reduction in authenticity serving as a significant determinant of increased moral disgust. Second, both authenticity and disgust significantly invoke positive word-of-mouth and loyalty, with two mediators acting in sequence within a stable "psychological chain mechanism." It is of particular importance that the type of content has no direct effect, which means that consumers do not react based on the information that content is replicated but rather on their judgments regarding the authenticity and ethical meaning of the content before forming behavioral intentions.

      Third, authorship moderation was one of the leading moderating factors at each significant stage of the chain mechanism. Under human authorship, replicated content significantly decreased perceived authenticity, which raised moral disgust and culminated in adverse behavioral outcomes. For example, consumers react with less severity to replicated content with AI authorship, and the degree of adverse psychological impact is significantly reduced. This indicates that consumers have much higher expectations of "emotional authenticity" and "creative responsibility" from human creators while applying those expectations much less rigorously to AI, which leads to a more negligible psychological gap when encountering replicated content made by AI.

      Overall, the findings demonstrate that in the era of artificial intelligence, content originality, authenticity, ethical perception, and authorship cues collectively shape consumer judgment. These factors do not operate in isolation but interact closely to influence consumer evaluation processes. Particularly in emotional marketing contexts, human-authored content is subject to stricter scrutiny regarding sincerity and ethicality, implying that brands must carefully consider how authorship decisions shape consumer interpretation. Practically, when content relies heavily on emotional expression, uniqueness, and sincerity, human authorship may be more persuasive—but only if originality is ensured. Conversely, for standardized or repetitive messages, AI authorship may help reduce expectation gaps and lower the risk of negative evaluation. As AI-generated content becomes more prevalent, brands must develop strategies that integrate human creativity with AI-generated materials to maintain consistency between content form and authorship, thereby better managing consumer psychological expectations.

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      목차 (Table of Contents)

      • 제1장 서론 1
      • 제1절 연구배경 및 목적 1
      • 1.1.1 연구의 배경 1
      • 1.1.2 연구의 목적 4
      • 제2절 논문의 구성 7
      • 제1장 서론 1
      • 제1절 연구배경 및 목적 1
      • 1.1.1 연구의 배경 1
      • 1.1.2 연구의 목적 4
      • 제2절 논문의 구성 7
      • 제2장 이론적 배경 및 선행연구 9
      • 제1절 이론적 배경 9
      • 2.1.1 콘텐츠 독창성과 복제성 9
      • 2.1.2 AI와 AI서명 11
      • 2.1.3 지각된 진정성 13
      • 2.1.4 도덕적 혐오 15
      • 2.1.5 긍정적 구전 17
      • 2.1.6 고객 충성도 18
      • 제2절 선행연구 20
      • 제3장 가설설정 및 연구모형 23
      • 제1절 연구모형 23
      • 제2절 가설설정 23
      • 3.2.1 콘텐츠 유형의 주효과 24
      • 3.2.2 지각된 진정성의 매개 역할 25
      • 3.2.3 도덕적 혐오의 매개 역할 26
      • 3.2.4 지각된 진정성이 도덕적 혐오에 미치는 영향 27
      • 3.2.5 연쇄매개효과 27
      • 3.2.6 서명 주체의 조절 역할 28
      • 제4장 연구설계 29
      • 제1절 실험설계 29
      • 제2절 원데이터 표본특성과 설문자료수집 31
      • 4.2.1 표본 특성 31
      • 4.2.2 변수 정의 및 측정 31
      • 제3절 윤리적 고지 및 소결 33
      • 제5장 실증분석 34
      • 제1절 데이터 출처 및 척도 설명 34
      • 제2절 조작 검증 35
      • 제3절 기술통계 및 상관분석 36
      • 5.3.1 기술통계 및 상관분석 해석 37
      • 5.3.2 상관관계 분석 38
      • 제4절 주효과 분석 40
      • 5.4.1 콘텐츠 유형이 긍정적 구전에 미치는 주효과 40
      • 5.4.2 콘텐츠 유형이 고객 충성도에 미치는 주효과 41
      • 제5절 매개효과 및 연쇄 매개효과 분석 41
      • 5.5.1 콘텐츠 유형이 지각된 진정성에 미치는 영향 42
      • 5.5.2 콘텐츠 유형이 도덕적 혐오에 미치는 영향 42
      • 5.5.3 매개변수가 결과변수에 미치는 영향 43
      • 5.5.4 지각된 진정성이 도덕적 혐오에 미치는 영향 45
      • 5.5.5 직접효과, 총효과 및 간접효과 분석 45
      • 제6절 조절된 매개효과 분석 49
      • 5.6.1 서명 주체가 콘텐츠 유형과 지각된 진정성 간 관계에 미치는 조절 효과 49
      • 5.6.2 서명 주체는 지각된 진정성과 도덕적 혐오 간 관계를 조절하지 않음 50
      • 5.6.3 서명 주체가 매개변수와 긍정적 구전 간 관계에 미치는 조절 효과 51
      • 5.6.4 조절된 매개효과 지수 검증 53
      • 5.6.5 서명 주체가 콘텐츠 유형과 심리 기제 및 고객 충성도 간 관계에 미치는 조절된 매개효과 분석 55
      • 제6장 결론 58
      • 제1절 연구의 요약 및 시사점 58
      • 제2절 연구 한계와 향후 연구 방향 60
      • 참고문현 63
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