The DOI matches its Crossref record.
Impact of Artificial Intelligence's Part in Supply Chain Planning and Decision Making Optimization
Open accessAbstract
Artificial intelligence (AI) is transforming supply chain planning and decision making, enabling organizations to tackle the complexities of modern supply chains. This article explores the various applications of AI in supply chain management, including demand forecasting, inventory optimization, transportation and logistics optimization, supplier selection and risk management, and predictive maintenance and asset management. AI-powered demand forecasting models analyze historical data and market trends to predict future demand accurately, while AI-driven inventory optimization considers factors such as lead times and demand variability to determine optimal inventory levels. AI can also optimize transportation routes, modes, and schedules, and assist in supplier selection and risk assessment. Predictive maintenance using AI helps reduce equipment downtime and maintenance costs. However, organizations must consider challenges such as data quality, algorithmic bias, interpretability of AI models, and ethical considerations when adopting AI in supply chain management. As AI technologies advance and integrate with other emerging technologies, the future of AI in supply chain management looks promising, offering organizations the potential to achieve greater efficiency, agility, and competitiveness. This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends…
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In the citing paper
“AI technologies bolster SMEs' market responsiveness by delivering real-time analytics on market trends, customer sentiment, and demand fluctuations.”
From Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies (2026) · cites this paper as Khoa et al., 2024
In the citing paper
“This intelligence facilitates proactive, data-driven decision-making, enabling SMEs to swiftly adjust their strategies in response to volatile and competitive market conditions (Khoa et al., 2024).”
From Artificial Intelligence Adoption for Sustainable Development in SMEs: Challenges, Strategic Pathways, and Lessons for Developing Economies (2026) · cites this paper as Khoa et al., 2024
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Kumar, R., Singh, A. K., Kassar, A. S. A., Humaida, M. I., Joshi, S., & Sharma, M. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1558772 · Cited by 36
Zhu, X., Lai, P., Li, X., Wang, Y., & Pei, X. (2025) · Systems · doi:10.3390/systems13070514 · Cited by 10
Daram, K., & Senthilkumar, P. (2025) · International Journal on Smart Sensing and Intelligent Systems · doi:10.2478/ijssis-2025-0040 · Cited by 6
Holland, J. (2026) · International Journal of Sustainability in Business and Economics · doi:10.51137/wrp.ijsbe.502 · Cited by 5
The Triple Nexus of Smart, Secure, and Sustainable Supply Chains
Mızrak, F. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-6417-8.ch009 · Cited by 4
Metadata
- Authors
- Khoa, B. Q., Nguyen, H.-T., Anh, D. B. H., & Ngoc, N. M.
- Venue
- International Journal of Multidisciplinary Research and Growth Evaluation
- Publisher
- Anfo Publication House
- Published
- 2024
- Volume
- 5
- Issue
- 6
- Pages
- 837-856
- ISSN
- 2582-7138 (ISSN-L)
- OpenAlex
- W4405137425
- Cited by
- 14
- References
- 0
- Citations by year
- 2026: 6 · 2025: 8
- FWCI
- 4.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- International Journal of Multidisciplinary Research and Growth Evaluation (publishedVersion, cc-by-nc-sa)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Decision Sciences › Management Science and Operations Research › Supply Chain and Inventory Management
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- artificial intelligence in supply chains, supply chain planning, demand forecasting, inventory optimization, supplier selection, supplier risk management, predictive maintenance, asset management, algorithmic bias, interpretability of AI models, AI ethics, artificial intelligence in education, research trends, Internet of Things, swarm intelligence, deep learning, adaptive learning, gamification, immersive learning, affective computing, teacher and student roles
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