Enhancing Metadata Management And Data-Driven Decision-Making In Sustainable Food Supply Chains Using Blockchain And AI Technologies
DOI:
https://doi.org/10.56294/dm2025683Keywords:
Blockchain, Artificial Intelligence, Metadata Management, Sustainable Supply Chain, Food Supply Chains, Decision-MakingAbstract
Sustainability in food supply chains is a critical global challenge, particularly in resource-constrained regions like Jordan, where operational inefficiencies and environmental concerns are prevalent. This study explores the integration of blockchain and artificial intelligence (AI) technologies to enhance metadata management, forecast sustainability metrics, and support decision-making in Jordan’s food supply chains. Blockchain's ability to improve metadata accuracy, standardization, and traceability, combined with AI’s predictive capabilities, offers a powerful solution for addressing sustainability challenges.
Methods
The research employed a mixed-methods approach, combining real-time data from blockchain transaction logs, AI-generated forecasts, and stakeholder surveys. Blockchain data from platforms like Hyperledger Fabric and Ethereum provided insights into metadata accuracy and traceability. AI models were developed using machine learning techniques, such as linear regression, to forecast food waste reduction, carbon footprint reduction, and energy efficiency. Multi-Criteria Decision Analysis (MCDA), using AHP and TOPSIS, was applied to evaluate trade-offs among sustainability goals.
Results
The results revealed significant improvements in metadata accuracy (from 83% to 96.66%) and reductions in traceability time (from 4.0 to 2.35 hours) following blockchain implementation. AI models demonstrated high predictive accuracy, explaining 88%, 81%, and 76% of the variance in food waste reduction, carbon footprint reduction, and energy efficiency, respectively.
Conclusion
This study underscores the transformative potential of blockchain and AI technologies in achieving sustainability goals. By fostering transparency, predictive insights, and data-driven decision-making, these innovations can address key challenges in Jordan’s food supply chains, offering actionable strategies for stakeholders.
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Copyright (c) 2025 Anber Abraheem Shlash Mohammad, Ammar Mohammad Al-Ramadan, Suleiman Ibrahim Mohammad, Badrea Al Oraini, Asokan Vasudevan, Muhammad Turki Alshurideh, Qian Chen, Imad Ali (Author)
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