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    Relationships Between Review Types and Consumer Repurchase Intent Remark in the Cosmetic Industry = 화장품 산업에서 리뷰 유형과 소비자의 재구매 의사 언급 간의 관계

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    https://www.riss.kr/link?id=T17315137

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    This study investigates how the content of online consumer reviews—particularly emotional versus functional expressions—relates to the mention of repurchase intention in the cosmetics industry. We collected 10,000 reviews from the top ten best-selling cosmetic products in base, lip, and eye makeup categories on Olive Young (a major Korean beauty retailer) in January 2025. Each review was categorized by its content type (functional or emotional) and sentiment polarity (positive or negative). Additionally, we identified reviews that explicitly mentioned an intention to repurchase using text mining techniques. Using binomial logistic regression, we examined how functional-positive, functional-negative, emotional-positive, and emotional-negative content relates to repurchase intention mentions. Emotional positivity was strongly associated with higher repurchase mention likelihood, whereas emotional negativity had the opposite effect. Functional content alone was not significant. However, when emotional positivity co-occurred with functional negativity, the likelihood of expressing repurchase intent significantly increased. This interaction implies that emotional engagement can compensate for dissatisfaction with product functionality. In our base model, control variables were included to account for category-specific effects. Among possible interactions, we focused on functional-negative × emotional-positive to test whether affective responses can override functional dissatisfaction. The findings highlight the dominant role of emotional cues in driving customer loyalty signals in the beauty sector.
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    This study investigates how the content of online consumer reviews—particularly emotional versus functional expressions—relates to the mention of repurchase intention in the cosmetics industry. We collected 10,000 reviews from the top ten best-sel...

    This study investigates how the content of online consumer reviews—particularly emotional versus functional expressions—relates to the mention of repurchase intention in the cosmetics industry. We collected 10,000 reviews from the top ten best-selling cosmetic products in base, lip, and eye makeup categories on Olive Young (a major Korean beauty retailer) in January 2025. Each review was categorized by its content type (functional or emotional) and sentiment polarity (positive or negative). Additionally, we identified reviews that explicitly mentioned an intention to repurchase using text mining techniques. Using binomial logistic regression, we examined how functional-positive, functional-negative, emotional-positive, and emotional-negative content relates to repurchase intention mentions. Emotional positivity was strongly associated with higher repurchase mention likelihood, whereas emotional negativity had the opposite effect. Functional content alone was not significant. However, when emotional positivity co-occurred with functional negativity, the likelihood of expressing repurchase intent significantly increased. This interaction implies that emotional engagement can compensate for dissatisfaction with product functionality. In our base model, control variables were included to account for category-specific effects. Among possible interactions, we focused on functional-negative × emotional-positive to test whether affective responses can override functional dissatisfaction. The findings highlight the dominant role of emotional cues in driving customer loyalty signals in the beauty sector.

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    목차 (Table of Contents)

    • Abstract (2)
    • Introduction(4)
    • Literature Review(5)
    • Methodology(7)
    • Base Model Specification (12)
    • Abstract (2)
    • Introduction(4)
    • Literature Review(5)
    • Methodology(7)
    • Base Model Specification (12)
    • Results of Base Model (14)
    • Interaction Model Specification (17)
    • Results of Interaction Model (17)
    • Discussion (19)
    • Conclusion (20)
    • References (22)
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