Blockchain-Enabled Machine Learning Framework for Demand Forecasting in Supply Chain Management
Rejuwan Shamim, Badr Bentalha · Advances in logistics, operations, and management science book series · 2023
Supply chain efficiency relies heavily on being able to accurately predict future demand. In this chapter, the authors offer a machine learning framework for supply chain management demand forecasting that makes use of blockchain technology. The framework improves the precision of demand forecasts while maintaining data integrity and openness through the use of machine learning algorithms and blockchain technologies. Demand data is collected and preprocessed, machine learning models are applied, and blockchain is used to validate and secure the data. Results from experiments show that the framework is useful, with significant gains in accuracy and recall compared to more conventional methods. The results show the promise of merging machine learning with blockchain in demand forecasting, giving supply chain professionals a potent instrument with which to enhance the effectiveness of inventory management and overall operations. To fully reap the benefits of this approach, more study into scalability and implementation difficulties is necessary.