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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Supply chain risk management with machine learning technology: A literature review and future research directions
Mei Yang, Ming K. Lim, Yingchi Qu, et al.
Computers & Industrial Engineering (2022) Vol. 175, pp. 108859-108859
Open Access | Times Cited: 71

Showing 1-25 of 71 citing articles:

Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management
Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, et al.
Logistics (2024) Vol. 8, Iss. 3, pp. 73-73
Open Access | Times Cited: 31
Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy
Md Shihab Shakur, Maishat Lubaba, Binoy Debnath, et al.
Logistics (2024) Vol. 8, Iss. 1, pp. 27-27
Open Access | Times Cited: 20
Deep learning approaches to identify order status in a complex supply chain
Mahmoud M. Bassiouni, Ripon K. Chakrabortty, Karam M. Sallam, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123947-123947
Open Access | Times Cited: 9
Information sharing strategy in supply chains: The role of C2M
Xue Chen, Bo Li, Minxue Wang
Expert Systems with Applications (2024) Vol. 247, pp. 123294-123294
Closed Access | Times Cited: 6
Large scale foundation models for intelligent manufacturing applications: a survey
Haotian Zhang, Stuart Dereck Semujju, Zhicheng Wang, et al.
Journal of Intelligent Manufacturing (2025)
Open Access
Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation
Xiaoming Zhang, Lean Yu, Hang Yin
Financial Innovation (2025) Vol. 11, Iss. 1
Open Access
Leveraging synthetic data to tackle machine learning challenges in supply chains: challenges, methods, applications, and research opportunities
Y. F. Long, Sebastian Kroeger, Michael F. Zaeh, et al.
International Journal of Production Research (2025), pp. 1-22
Open Access
Government Accounting Supervision and Corporate Supply Chain Risk
Yizhen Lyu
Finance research letters (2025), pp. 106785-106785
Closed Access
How do talent and technology factors affect supply chain robustness and resilience? Evidence from Chinese manufacturers
Zheng Li, Guang Song, Shaohua Song, et al.
Industrial Management & Data Systems (2025)
Closed Access
Examining the Impact of Trade Tariffs on Semiconductor Firms' Environmental Performance
Minhao Zhang, Di Liu, Xiaolong Shui, et al.
International Journal of Production Economics (2025) Vol. 281, pp. 109528-109528
Open Access
Machine learning in supply chain management: systematic literature review and future research agenda
Ilias Vlachos, Patlolla Sathvika Reddy
International Journal of Production Research (2025), pp. 1-30
Closed Access
Supply chain network viability: Managing disruption risk via dynamic data and interaction models
Sha-lei Zhan, Joshua Ignatius, C.T. Ng, et al.
Omega (2025), pp. 103303-103303
Closed Access
Machine learning applications in risk management: Trends and research agenda
Alejandro Valencia-Arías, Jesús Alberto Jiménez García, Erica Agudelo-Ceballos, et al.
F1000Research (2025) Vol. 14, pp. 233-233
Open Access
Artificial intelligence applications for supply chain risk management considering interconnectivity, external events exposures and transparency: a systematic literature review
Amir Hossein Ordibazar, Omar Khadeer Hussain, Ripon K. Chakrabortty, et al.
Modern Supply Chain Research and Applications (2025)
Open Access
How Does Digital Capability Shape Resilient Supply Chains?—Evidence from China’s Electric Vehicle Manufacturing Industry
Yanxuan Li, Vatcharapol Sukhotu
Future Internet (2025) Vol. 17, Iss. 3, pp. 123-123
Open Access
Adsorption and modification behavior of single atoms on the surface of single vacancy graphene: Machine learning accelerated first principle computations
Jingtao Huang, Jingteng Xue, Mingwei Li, et al.
Applied Surface Science (2023) Vol. 635, pp. 157757-157757
Open Access | Times Cited: 12
单原子在铝合金中的扩散迁移行为: 可解释机器学习加速第一原理计算方法
Jingtao Huang, Jingteng Xue, Mingwei Li, et al.
Science China Materials (2024) Vol. 67, Iss. 4, pp. 1140-1149
Open Access | Times Cited: 4
Driving Supply Chain Resilience: Exploring the Potential of Operations Management and Industry 4.0
Isam Hafidy, Asmaa Benghabrit, Kamar Zekhnini, et al.
Procedia Computer Science (2024) Vol. 232, pp. 2458-2467
Open Access | Times Cited: 4
Modelling supply chain risk events by considering their contributing events: a systematic literature review
Maryam Shahsavari, Omar Khadeer Hussain, Pankaj Sharma, et al.
Enterprise Information Systems (2025)
Open Access
Economic strategic plans with supply chain risk management (SCRM) for organizational growth and development
Basim Aljabhan
Alexandria Engineering Journal (2023) Vol. 79, pp. 411-426
Open Access | Times Cited: 11
Application of Internet of Things and Machine learning in improving supply chain financial risk management System
Kafila, Nalla Bala Kalyan, Kamal Ahmad, et al.
(2023), pp. 211-216
Closed Access | Times Cited: 11
An Overview of Applications of Hesitant Fuzzy Linguistic Term Sets in Supply Chain Management: The State of the Art and Future Directions
Francisco Rodrigues Lima, Mery Ellen Brandt de Oliveira, Carlos Henrique Lopes Resende
Mathematics (2023) Vol. 11, Iss. 13, pp. 2814-2814
Open Access | Times Cited: 10
TRANSPORT RISKS IN THE SUPPLY CHAINS – POST COVID-19 CHALLENGES
Ewa Chodakowska, Darius Bazaras, Edgar Sokolovskij, et al.
Journal of Business Economics and Management (2024) Vol. 25, Iss. 2, pp. 211-225
Open Access | Times Cited: 3
A Deep Learning Approach to Predict Supply Chain Delivery Delay Risk Based on Macroeconomic Indicators: A Case Study in the Automotive Sector
Matteo Gabellini, Lorenzo Civolani, Francesca Calabrese, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4688-4688
Open Access | Times Cited: 3
A Data-Driven Approach to Predict Supply Chain Risk Due to Suppliers’ Partial Shipments
Matteo Gabellini, Francesca Calabrese, Lorenzo Civolani, et al.
Smart innovation, systems and technologies (2024), pp. 227-237
Closed Access | Times Cited: 2
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