인공지능기반 건강기능식품 추천서비스 사용의도에 미치는 영향요인 분석

• 영문명: Analysis of the Influence Factors on Intention of Use for Artificial Intelligence-Based Health Functional Food Recommended Service
• 발행기관: 한국IT서비스학회
• 저자명: 윤혜정(Heajeang Yun) 김영대(Yeongdae Kim) 김지영(Ji-Young Kim) 신용태(Yongtae Shin)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제20권 제6호, 1~16쪽, 전체 16쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2021.12.31

영문 초록

The health functional food market continues to grow, and according to that trend, the subdivision sales of personalized health functional foods, which have been legally prohibited, will be operated as a special regulatory pilot project. Personalized health functional food recommendations have a variety of personalized indicators to consider, and it is believed that algorithmic methods will be needed to proceed in a customized manner considering all of them. This study aims to contribute to the development of the AI-based health functional food recommendation service by studying factors that affect the use of the AI-based health functional food recommendation service. This paper analyzed the intention of use for AI-based health functional food recommendation service based on the information system success model and Technology Acceptance Model. This study considered information quality factors, service quality factor, and system quality factor as independent variables influencing perceived usefulness , perceived ease of use and trust. For empirical analysis, 406 questionnaires were used and the collected data were performed using AMOS 22.0 and SPSS 22.0. Research has shown that the accuracy, timeliness, empathy and availability have a positive effect on usefulness. Understandability and availability has been shown to have a positive effect on ease of use. The accuracy, understandability, empathy and availibility has been shown to have a positive impact on Trust. Usefulness, ease of use and trust all have been shown to have a positive influence on intention of use.

목차

Ⅰ. 서론

Ⅱ. 이론적 배경

Ⅲ. 연구 설계

Ⅳ. 실증분석

Ⅴ. 결 론

참고문헌

키워드

The health functional food Personalized nutrition Artificial Intelligence Information Systems Success Model Technology Acceptance Model Intention of Use