Enhancing Supply Chain Transparency and Risk Management Using CNN-LSTM With Transfer Learning

IF 3.6 3区 管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Organizational and End User Computing Pub Date : 2023-11-08 DOI:10.4018/joeuc.333472
Yongping Zhang, Achyut Shankar
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Abstract

Enhancing supply chain transparency and risk management is crucial in modern businesses. The supply chain involves multiple stages and participants, including suppliers, manufacturers, and logistics companies. However, supply chain data is often vast and complex, encompassing various types of information. Effectively analyzing and leveraging this data can help businesses identify potential risks and improvement opportunities. Therefore, a powerful method is needed to process supply chain data and provide accurate predictions and decision support. In this article, the authors approach is based on CNN-LSTM and transfer learning. By comparing with traditional methods and baseline models, this CNN-LSTM model achieved significant improvements in supply chain transparency and risk management. This model accurately predicts potential supply chain risks, providing corresponding decision support. This research is of great significance to enhance the efficiency, reliability, and transparency of the supply chain, offering valuable support for business decision-making.
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基于迁移学习的CNN-LSTM提高供应链透明度和风险管理
提高供应链透明度和风险管理在现代企业中至关重要。供应链涉及多个阶段和参与者,包括供应商、制造商和物流公司。然而,供应链数据通常庞大而复杂,包含各种类型的信息。有效地分析和利用这些数据可以帮助企业识别潜在的风险和改进机会。因此,需要一种强大的方法来处理供应链数据,并提供准确的预测和决策支持。在本文中,作者的方法是基于CNN-LSTM和迁移学习。通过与传统方法和基线模型的比较,该CNN-LSTM模型在供应链透明度和风险管理方面取得了显著的进步。该模型能够准确预测潜在的供应链风险,提供相应的决策支持。本研究对提高供应链的效率、可靠性和透明度具有重要意义,为企业决策提供有价值的支持。
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来源期刊
Journal of Organizational and End User Computing
Journal of Organizational and End User Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
6.00
自引率
9.20%
发文量
77
期刊介绍: The Journal of Organizational and End User Computing (JOEUC) provides a forum to information technology educators, researchers, and practitioners to advance the practice and understanding of organizational and end user computing. The journal features a major emphasis on how to increase organizational and end user productivity and performance, and how to achieve organizational strategic and competitive advantage. JOEUC publishes full-length research manuscripts, insightful research and practice notes, and case studies from all areas of organizational and end user computing that are selected after a rigorous blind review by experts in the field.
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