온라인 리뷰를 통해 무엇을 확인하는가?: 신규 이용자의 서비스 수용 의도에 영향을 미치는 요인 발굴

초록

The advent of mobile services that enable real-time information exchange anytime and anywhere has greatly facilitated users’ exploration, purchase, and sharing behaviors in the consumption process. In this study, we focus on the role of early service users’ evaluations as persuasive information for new service users, combining text mining and structural equation modeling in a mixed-method research approach. To achieve this, we utilized text mining techniques to extract service characteristics related to satisfaction and dissatisfaction from user reviews. We then applied and extended these findings to a value-based acceptance model to empirically demonstrate their impact. The analysis results confirmed that service characteristics derived from reviews have a significant influence on perceived value. This study holds significance as it combines big data analysis techniques with traditional statistical methods, highlighting the potential perception of service users’ evaluations as persuasive cues for new users.

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