인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
The integration of artificial intelligence (AI) into supply chain management (SCM) offers significant potential to enhance operational efficiency and decision-making. However, despite its promise, many organizations encounter challenges in effectively implementing AI technologies. This study aims to address this knowledge gap by systematically investigating the barriers and opportunities associated with AI implementation in SCM. Utilizing the Analytic Hierarchy Process (AHP) with an innovative judgment assignment approach, the research delves into the key factors influencing successful AI adoption. Through a comprehensive literature review and expert consultations, the findings reveal critical challenges such as data quality issues, the complexity of AI systems, and resistance to change within organizations. Conversely, the analysis underscores the potential for substantial benefits, including improved demand forecasting accuracy, enhanced logistics efficiency, and reduced operational costs. The theoretical implications of this research highlight the transformative potential of AI in revolutionizing SCM. It provides a framework that organizations can utilize to successfully adopt these technologies and optimize their supply chain operations. This study contributes valuable insights and practical recommendations to the existing body of knowledge on AI-driven SCM, aiding organizations in navigating the challenges and realizing the full potential of AI in this domain.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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