사용자 특성이 빅데이터 기반 레스토랑 평가 애플리케이션 이용의도에 미치는 영향

The purpose of this study is to investigate how user characteristics such as self-efficacy, individual innovativeness, and knowledge can affect perceived usefulness and the intention to use restaurant evaluation applications based on big data. The sample was defined as adults who have experience of using restaurant evaluation applications (App). A total of 250 valid samples were ensured from overall survey respondents who had used the App at least once. The survey was conducted through both a Google online survey and by distributing questionnaires directly to respondents. The R program was used to analyze descriptive statistics including frequency analysis and reliability analysis. The AMOS program was also used to analyze confirmatory factor analysis, correlation analysis, and structural equation models. Several interesting findings were come out. First, the factors of self-efficacy and knowledge, which have the ability to utilize App appeared to have a positive effect on perceived usefulness. Secondly, perceived usefulness has a positive effect on intention to use. Finally, IT related workers had a significant impact on Knowledge as well as self-efficacy and individual innovativeness. In conclusion, using App based on big data is more useful to users who are able to embrace and utilize new technologies, and those who have relevant knowledge. Additionally, this study shows that self-efficacy, individual innovativeness, and knowledge as personal qualities are very important factors for perceived usefulness.