Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation
基于资源基础观，研究AI和生成式AI在供应链与运营管理13个决策领域（如需求预测、库存管理）的应用，提出一个能力框架，帮助管理者和研究者识别应用场景、提升效率与韧性。
This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM).Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas.These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management.With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers.The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development.Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness.The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research.