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논문 기본 정보

저자정보
(Cadi Ayyad University) (EMG Rabat) (Cadi Ayyad University)
저널정보
대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems Vol.24 No.1
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    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.

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