호텔 온라인 리뷰 신뢰가 리뷰 수용도에 미치는 영향 - 리뷰 출처 유형(인간 vs. AI)에 따른 차이 검증 -
The Impact of Trust in Hotel Online Reviews on Review Acceptance - Examining Differences by Review Source (Human vs. AI) -
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초록
This study examined the impact of trust in online hotel reviews on review acceptance and analyzed differences based on review authorship (human vs. AI). Online review trust was conceptualized as a multidimensional construct comprising usefulness, benevolence, and truthfulness, with each component's differential effects on consumer acceptance behavior empirically investigated. A survey was conducted with 200 Korean adults who had online accommodation booking experience. Participants were randomly assigned to either human-written review groups (100 participants) or AI-generated review groups (100 participants) using a between-subjects experimental design with scenario manipulation. The results revealed that usefulness and truthfulness had significant positive effects on review acceptance, while benevolence did not show significant effects. Regarding group differences, AI-generated reviews showed significantly higher levels of review acceptance and truthfulness compared to human- written reviews, contradicting expectations based on prior studies. The theoretical implications include deepening understanding of the multidimensional structure of online review trust and discovering new patterns in consumer perceptions of AI reviews that challenge existing assumptions about AI-generated content. The practical implications suggest that businesses should focus on enhancing review usefulness and truthfulness, and platform operators can positively consider implementing AI-based review systems.
Abstract
This study examined the impact of trust in online hotel reviews on review acceptance and analyzed differences based on review authorship (human vs. AI). Online review trust was conceptualized as a multidimensional construct comprising usefulness, benevolence, and truthfulness, with each component's differential effects on consumer acceptance behavior empirically investigated. A survey was conducted with 200 Korean adults who had online accommodation booking experience. Participants were randomly assigned to either human-written review groups (100 participants) or AI-generated review groups (100 participants) using a between-subjects experimental design with scenario manipulation. The results revealed that usefulness and truthfulness had significant positive effects on review acceptance, while benevolence did not show significant effects. Regarding group differences, AI-generated reviews showed significantly higher levels of review acceptance and truthfulness compared to human- written reviews, contradicting expectations based on prior studies. The theoretical implications include deepening understanding of the multidimensional structure of online review trust and discovering new patterns in consumer perceptions of AI reviews that challenge existing assumptions about AI-generated content. The practical implications suggest that businesses should focus on enhancing review usefulness and truthfulness, and platform operators can positively consider implementing AI-based review systems.