Applying Artificial Intelligence in Supply Chain Management

被引:1
作者
Alfawaz, Khaled Mofawiz [1 ]
Alshehri, Ali Abdullah [1 ]
机构
[1] King Abdulaziz Univ, Fac Econ & Adm, Dept Management Informat Syst, Jeddah, Saudi Arabia
来源
COMMUNICATIONS IN MATHEMATICS AND APPLICATIONS | 2022年 / 13卷 / 01期
关键词
Supply chain; Artificial intelligence; Quantitative studies; Qualitative studies; RISK;
D O I
10.26713/cma.v13i1.1976
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
With the international scale context this study, it gives a top level view of the idea of AI pushed supply chain studies, the rising AI primarily based totally enterprise fashions of various case businesses are analysed. Maintainable overall performance and flexibility occupy a huge a part of the charities and studies works associated with the supply chain and logistics, on the only hand due to the dangers innate with inside the supply chain and the opposite hand due to outside turbulences, dangers and crises that may briefly or robustly effect customer's service. Some of the overall performance matrices which includes advertising and marketing techniques of SCM, want destiny amendment of SCM, function of Artificial Intelligence in SCM production, improvement of SCM is the manner to get achievement for the retail production, function of Artificial Intelligence with inside the organization, key reason of Artificial Intelligence and Purpose of SCM with inside the organization need to be taken in count. Along with those overall performance metrics will support to beautify the deliver chain control functionalities which cause enhance the enterprise.
引用
收藏
页码:367 / 377
页数:11
相关论文
共 14 条
[1]  
Ali A., 2019, Uncertain Supply Chain Management, V7, P215, DOI DOI 10.5267/J.USCM.2018.10.004
[2]  
Alzoubi H., 2018, INT J MULTIDISCIPLIN, V7, P363
[3]   Digitalization within food supply chains to prevent food waste. Drivers, barriers and collaboration practices [J].
Annosi, Maria Carmela ;
Brunetta, Federica ;
Bimbo, Francesco ;
Kostoula, Marianthi .
INDUSTRIAL MARKETING MANAGEMENT, 2021, 93 :208-220
[4]   Inter-organizational systems use and supply chain performance: Mediating role of supply chain management capabilities [J].
Asamoah, D. ;
Agyei-Owusu, B. ;
Andoh-Baidoo, F. K. ;
Ayaburi, E. .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2021, 58
[5]   Role of technological dimensions of green supply chain management practices on firm performance [J].
Bag, Surajit ;
Gupta, Shivam ;
Kumar, Sameer ;
Sivarajah, Uthayasankar .
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT, 2021, 34 (01) :1-27
[6]   Supply chain risk management and artificial intelligence: state of the art and future research directions [J].
Baryannis, George ;
Validi, Sahar ;
Dani, Samir ;
Antoniou, Grigoris .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 57 (07) :2179-2202
[7]   Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation [J].
Belhadi, Amine ;
Mani, Venkatesh ;
Kamble, Sachin S. ;
Khan, Syed Abdul Rehman ;
Verma, Surabhi .
ANNALS OF OPERATIONS RESEARCH, 2024, 333 (2-3) :627-652
[8]   Insights from big Data Analytics in supply chain management: an all-inclusive literature review using the SCOR model [J].
Chehbi-Gamoura, Samia ;
Derrouiche, Ridha ;
Damand, David ;
Barth, Marc .
PRODUCTION PLANNING & CONTROL, 2020, 31 (05) :355-382
[9]   Supply chain 2.0 revisited: a framework for managing volatility-induced risk in the supply chain [J].
Christopher, Martin ;
Holweg, Matthias .
INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT, 2017, 47 (01) :2-17
[10]  
Chui M., 2018, Notes from the AI frontier: Applications and value of deep learning