供应链
供应链风险管理
供应链管理
风险管理
风险分析(工程)
业务
工程类
计算机科学
服务管理
营销
财务
作者
A. Deiva Ganesh,P. Kalpana
标识
DOI:10.1016/j.cie.2022.108206
摘要
• Systematic literature review based on 127 papers on supply chain risk management. • Intelligent risk management can enhance the supply chains to be more resilient. • Digitization supports in developing smarter supply chains respond to the disruptions. • A risk management framework is proposed and related future scopes are presented. Supply Chain Risk Management (SCRM) is a rapidly growing field of research encompassing identification, assessment, mitigation, and monitoring of the risks or unexpected and unprecedented events. Among the researchers, there has been a significant focus on identifying, mitigating, and managing the risks that affect the supply chain (SC). Though the research on SCRM remains for an extended period, still the industries are facing difficulties in managing the SC risks. Also, the SC managers have begun to focus on decision-making based on numerous data sources for predicting the uncertainties more accurately to achieve a proactive and predictive intelligent risk management mechanism. These attributes make Artificial Intelligence (AI) and Machine learning (ML) suitable techniques in the SCRM field. The application of these techniques in SCRM is in a nascent stage. In this view, this paper presents a systematic and descriptive review of the literature and identifies the various AI and ML methods applied in different phases related to SCRM. Also, it investigates the different categories of SC risks and the existing articles based on the AI technique used. This analysis focuses on research articles related to SCRM from three scientific databases published between 2010 and 2021 for detailed study. Finally, this review provides unexplored and missing aspects in current research, challenges on implementing AI technologies, and describes promising avenues for the future.
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