중국 해외직구 쇼핑 앱 서비스 품질 속성이 만족도에 미치는 영향: 텍스트 마이닝 기법을 기반으로

Chinese cross-border e-commerce(CBEC) has grown rapidly in recent years. With the increasing use of mobile applications for CBEC shopping, this study explores customers’ overall perception and service quality(SQ) attributes of AliExpress, a China-based cross-border e-commerce platform. We analyzed user reviews from the Apple App Store to identify the service quality attributes that Korean customers consider important when shopping through the app. A text mining technique was applied to analyze the data using Python, followed by further empirical analysis using R, a statistical software package, to examine the effect of service quality attributes on customers’ overall satisfaction. Based on previous studies, review data were classified into six service quality attributes (topics): ease-of-use, trust, economy, responsiveness, information, and convenience. The effect of these service quality attributes on overall satisfaction was examined using a Tobit regression model. The result showed that the ease-of-use, economy, information and convenience are significant factors in assessing overall satisfaction with the app service, while trust is not. This study not only offers valuable insights for developingservice quality management strategies to enhance customer satisfaction in Korea-China e-commerce but also provides fundamental data to help e-commerce platform companies strengthen their competitiveness. Additionally, it broadens mobile shopping-related research methodologically by incorporating text mining techniques to analyze customers’ actual opinions from both linguistic and emotional perspectives.