Earticle

초록

영어

AI recommendation services are widely utilized across industries. However, users’ perceptions of algorithmic bias, lack of transparency, and privacy risks may influence the formation of trust and satisfaction. This study comparatively examines how risk perceptions affect trust, satisfaction, and reuse intentions in e-commerce and FinTech services. A survey was conducted with adults who have experience using AI recommendation services, and the data was analyzed using structural equation modeling. Risk perception was conceptualized as three dimensions: bias, opacity, and privacy risk. The results revealed that the impact of the three risk factors differed between the two industries. In the e-commerce environment, algorithmic bias was interpreted as a result of personalized recommendations rather than being perceived as a traditional risk factor, and it actually acted as a factor that increased trust and satisfaction. In contrast, in fintech, where service usage is linked to high-risk decision-making regarding assets, loans, and investments, algorithmic bias and privacy risks acted as key factors undermining trust, whereas opacity did not have a significant impact. These findings suggest that the influence of risk perceptions is contingent upon industry characteristics. And provide practical implications for the design and management of AI recommendation services.

목차

Abstract
1. 서론
2. 이론적 배경
2.1 AI 기반 추천 서비스
2.2 전자상거래와 핀테크에서의 AI 추천 서비스특성 비교
2.3 AI 추천 서비스 리스크 인식 요인
3. 연구설계
3.1 연구모형과 가설
3.2 조작적 정의
3.3 연구방법
4. 실증분석
4.1 표본의 특성
4.2 타당성 및 신뢰도 검증
4.3 가설 검증
5. 결론
5.1 연구결과의 요약
5.2 시사점 및 한계점
[References]

키워드

저자

• 송하 [ Ha Song | 한양대학교 공학대학원 프로젝트관리학 석사 ] 제1저자
• 이다솔 [ Dasol Lee | 우석대학교 글로벌문화경영학부 조교수 ] 공동저자
• 백동현 [ Donghyun Baek | 한양대학교 ERICA 경영학부 교수 ] 교신저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  프로젝트경영연구 [Project Management Review]

• 간기

  반년간

• eISSN

  2799-3434

• 수록기간

  2021~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 325 DDC 658