The role of deep learning in supply chain collaboration and cooperation
In today’s globalized and technologically advanced business landscape, supply chain collaboration is crucial for enterprises seeking to gain a competitive edge, enhance operational efficiency, and adapt to market dynamics. Traditional methods often fall short in managing the complexities and rapid c...
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IGI Global
2024
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Online Access: | http://psasir.upm.edu.my/id/eprint/113413/1/113413.pdf http://psasir.upm.edu.my/id/eprint/113413/ https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/JOEUC.342841 |
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my.upm.eprints.1134132024-11-22T08:35:58Z http://psasir.upm.edu.my/id/eprint/113413/ The role of deep learning in supply chain collaboration and cooperation Cai, Junjie Sharkawi, Ismawati Taasim, Shairil Izwan In today’s globalized and technologically advanced business landscape, supply chain collaboration is crucial for enterprises seeking to gain a competitive edge, enhance operational efficiency, and adapt to market dynamics. Traditional methods often fall short in managing the complexities and rapid changes within supply chains. This study introduces an innovative deep learning model, combining BERT, GAT, and RL, to address these challenges effectively. The model demonstrates its prowess in processing supply chain data, accurately predicting market trends, and optimizing decision-making processes. By leveraging deep learning, this research not only expands theoretical applications in supply chain management but also provides practical tools to boost operational efficiency, highlighting the immense potential and practical value of deep learning technology in modern supply chain management. IGI Global 2024 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/113413/1/113413.pdf Cai, Junjie and Sharkawi, Ismawati and Taasim, Shairil Izwan (2024) The role of deep learning in supply chain collaboration and cooperation. Journal of Organizational and End User Computing, 36 (1). pp. 1-23. ISSN 1546-2234; eISSN: 1546-5012 https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/JOEUC.342841 10.4018/JOEUC.342841 |
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In today’s globalized and technologically advanced business landscape, supply chain collaboration is crucial for enterprises seeking to gain a competitive edge, enhance operational efficiency, and adapt to market dynamics. Traditional methods often fall short in managing the complexities and rapid changes within supply chains. This study introduces an innovative deep learning model, combining BERT, GAT, and RL, to address these challenges effectively. The model demonstrates its prowess in processing supply chain data, accurately predicting market trends, and optimizing decision-making processes. By leveraging deep learning, this research not only expands theoretical applications in supply chain management but also provides practical tools to boost operational efficiency, highlighting the immense potential and practical value of deep learning technology in modern supply chain management. |
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Article |
author |
Cai, Junjie Sharkawi, Ismawati Taasim, Shairil Izwan |
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Cai, Junjie Sharkawi, Ismawati Taasim, Shairil Izwan The role of deep learning in supply chain collaboration and cooperation |
author_facet |
Cai, Junjie Sharkawi, Ismawati Taasim, Shairil Izwan |
author_sort |
Cai, Junjie |
title |
The role of deep learning in supply chain collaboration and cooperation |
title_short |
The role of deep learning in supply chain collaboration and cooperation |
title_full |
The role of deep learning in supply chain collaboration and cooperation |
title_fullStr |
The role of deep learning in supply chain collaboration and cooperation |
title_full_unstemmed |
The role of deep learning in supply chain collaboration and cooperation |
title_sort |
role of deep learning in supply chain collaboration and cooperation |
publisher |
IGI Global |
publishDate |
2024 |
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http://psasir.upm.edu.my/id/eprint/113413/1/113413.pdf http://psasir.upm.edu.my/id/eprint/113413/ https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/JOEUC.342841 |
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