온라인 쇼핑의 데이터 융합 기반 사이즈 추천 서비스: 서비스 품질, 정보 신뢰, 고객 만족의 구매 의도에 대한 역할
Size Recommendation Technology Convergence in e-Shopping: Roles of Service Quality Information Credibility and Satisfaction on Purchase Intention
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초록
본 연구는 온라인 패션 리테일링에서 최근 이용이 증가하고 있는 데이터 융합 기반 사이즈 추천 테크놀로지 서비스 품질이 정보 신뢰와 만족 및 구매 의도에 미치는 영향을 검증하였다. 연구를 위한 설문은 아마존 미케니컬 터크에서 시행되었으며, 사이즈 추천 테크놀로지의 사용 경험이 없는 18세 이상 60세 이하의 미국 거주 여성을 대상으로 하였다. 이들은 설문에 제시된 링크를 클릭하여 특정 패션 온라인 리테일러의 웹페이지에서 사이즈 추천 테크놀로지를 경험한 뒤, 설문에 답하였다. 불성실한 응답을 제외한 213부를 SPSS 27.0과 Process Macro(모델 6번, 5,000 bootstrapping sample)를 이용하여 분석한 결과, 사이즈 추천 테크놀로지 서비스 품질의 하위차원은 반응성과 사용 편의성으로 나타났으며, 두 하위차원은 모두 정보 신뢰와 만족을 매개로 하여 구매 의도에 영향을 미치고 있는 것으로 나타났다. 본 연구는 이와 같은 결과를 바탕으로 사이즈 추천 테크놀로지의 상용화를 위한 전략을 제언하였다.
Abstract
This study investigated the effect of size recommendation technology convergence on purchase intention mediated by information credibility and satisfaction. The survey for this study was conducted on Amazon Mechanical Turk targeting U. S. residing women aged 18 to 60 years old who have never used size recommendation technology. They experienced the size recommendation technology in the provided web page and returned to the survey to answer the questionnaire. The analysis was done with 213 surveys using SPSS 27.0 and Process Macro (model 6, 5,000 Bootstrapping sample). The dimensions of service quality were found to be responsiveness and ease of use, and both have a significant effect on purchase intention through information credibility and satisfaction.
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