Advanced supply chain analytics: Leveraging digital twins, IoT and blockchain for resilient, data-driven business operations
Open accessAbstract
The evolution of supply chain analytics has been accelerated by digital transformation, with Digital Twins, the Internet of Things (IoT), and Blockchain emerging as pivotal technologies for creating resilient, data-driven business operations. Traditional supply chains face challenges such as demand fluctuations, logistical inefficiencies, supply disruptions, and lack of real-time visibility. Advanced supply chain analytics, powered by Artificial Intelligence (AI) and big data, enables organizations to transition from reactive to predictive and prescriptive decision-making, optimizing efficiency and mitigating risks. Digital Twins facilitate real-time simulations of physical supply chain processes, allowing businesses to model disruptions, optimize inventory, and improve logistics planning before implementing changes in the physical world. IoT-enabled devices, such as smart sensors and RFID trackers, provide continuous monitoring of goods in transit, ensuring visibility into factors like temperature, location, and shipment integrity. Meanwhile, Blockchain technology enhances supply chain transparency, traceability, and security, enabling secure data sharing and fraud prevention in multi-stakeholder ecosystems. These technologies collectively enable organizations to achieve real-time supply chain optimization, proactive risk management, and sustainable operations. However, challenges such as data standardization, integration complexity, and cybersecurity risks must be addressed for seamless implementation. This paper examines the methodologies, industry applications, and future potential of advanced supply chain analytics, providing strategic insights into how businesses can leverage Digital Twins, IoT, and Blockchain to enhance agility, reduce operational costs, and build resilient global supply networks.
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- Authors
- Owusu-Berko, L.
- Affiliations
- University of South Carolina (US)
- Corresponding author
- Louis Owusu-Berko
- Venue
- World Journal of Advanced Research and Reviews
- Publisher
- GSC Online Press
- Published
- 2025-02-28
- Volume
- 25
- Issue
- 2
- Pages
- 1777-1799
- ISSN
- 2581-9615 (ISSN-L)
- OpenAlex
- W4407849237
- Cited by
- 29
- References
- 0
- Citations by year
- 2026: 20 · 2025: 9
- FWCI
- 22.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- World Journal of Advanced Research and Reviews (publishedVersion, cc-by)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Strategy and Management › Supply Chain Resilience and Risk Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Keywords
- supply chain analytics, digital twin, Internet of Things, blockchain, supply chain resilience, supply chain visibility, inventory optimization, logistics planning, supply chain risk management, supply chain traceability, artificial intelligence, big data, data standardization, cybersecurity risks
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