Blockchain-enabled Supply Chain Management: Investigating the application of blockchain technology in supply chain management for traceability, transparency, and efficiency
Keywords:
Blockchain, Supply Chain Management, TraceabilityAbstract
Blockchain technology has gained significant attention for its potential to revolutionize supply chain management (SCM). This paper explores the application of blockchain in SCM, focusing on its ability to enhance traceability, transparency, and efficiency. We examine the key features of blockchain that make it suitable for SCM, such as immutability, decentralization, and smart contracts. Case studies and real-world examples are used to illustrate the benefits and challenges of implementing blockchain in SCM. The paper concludes with recommendations for organizations looking to adopt blockchain for SCM and identifies future research directions in this field.
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References
Perumalsamy, Jegatheeswari, Bhargav Kumar Konidena, and Bhavani Krothapalli. "AI-Driven Risk Modeling in Life Insurance: Advanced Techniques for Mortality and Longevity Prediction." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 392-422.
Karamthulla, Musarath Jahan, et al. "From Theory to Practice: Implementing AI Technologies in Project Management." International Journal for Multidisciplinary Research 6.2 (2024): 1-11.
Jeyaraman, J., Krishnamoorthy, G., Konidena, B. K., & Sistla, S. M. K. (2024). Machine Learning for Demand Forecasting in Manufacturing. International Journal for Multidisciplinary Research, 6(1), 1-115.
Karamthulla, Musarath Jahan, et al. "Navigating the Future: AI-Driven Project Management in the Digital Era." International Journal for Multidisciplinary Research 6.2 (2024): 1-11.
Karamthulla, M. J., Prakash, S., Tadimarri, A., & Tomar, M. (2024). Efficiency Unleashed: Harnessing AI for Agile Project Management. International Journal For Multidisciplinary Research, 6(2), 1-13.
Jeyaraman, Jawaharbabu, Jesu Narkarunai Arasu Malaiyappan, and Sai Mani Krishna Sistla. "Advancements in Reinforcement Learning Algorithms for Autonomous Systems." International Journal of Innovative Science and Research Technology (IJISRT) 9.3 (2024): 1941-1946.
Jangoan, Suhas, Gowrisankar Krishnamoorthy, and Jesu Narkarunai Arasu Malaiyappan. "Predictive Maintenance using Machine Learning in Industrial IoT." International Journal of Innovative Science and Research Technology (IJISRT) 9.3 (2024): 1909-1915.
Jangoan, Suhas, et al. "Demystifying Explainable AI: Understanding, Transparency, and Trust." International Journal For Multidisciplinary Research 6.2 (2024): 1-13.
Krishnamoorthy, Gowrisankar, et al. "Enhancing Worker Safety in Manufacturing with IoT and ML." International Journal For Multidisciplinary Research 6.1 (2024): 1-11.
Perumalsamy, Jegatheeswari, Muthukrishnan Muthusubramanian, and Lavanya Shanmugam. "Machine Learning Applications in Actuarial Product Development: Enhancing Pricing and Risk Assessment." Journal of Science & Technology 4.4 (2023): 34-65.
