Blockchain technology has gained growing scholarly and industrial attention for its ability to improve transparency, optimize operational efficiency, and support food safety protocols in food supply chain (FSC) traceability systems. Yet, despite this fast rise in prominence, current scholarly discourse demonstrates a noticeable gap in knowledge regarding the systemic implementation and wider implications of blockchain in FSC traceability. To fill this research gap, the present study delivers what is, to the best of our knowledge, the first large-scale bibliometric examination exclusively focused on blockchain-enabled FSC traceability. Using 620 publications indexed in the Scopus database, this study maps the intellectual structure of the field and traces the evolution of research themes concerning blockchain-enabled traceability. The review uncovers several dominant thematic trajectories. More specifically, the adoption of blockchain with complementary advanced technologies such as the Internet of Things (IoT) and artificial intelligence (AI) has become a focal trend. Concurrently, blockchain acts as a mechanism to mitigate concerns related to food safety, authenticity, security, and sustainable supply governance. The findings illustrate the multifaceted utility of blockchain in FSC traceability and signal its potential to impact future trends in supply chain management. Overall, this article addresses a critical gap in the current literature and lays a foundation for further interdisciplinary exploration. By aligning theoretical discourse with practical relevance, the review aims to contribute to the development of transparent, efficient, and sustainable food supply systems, thereby supporting global food safety and security objectives.
The shift to circular supply chains (CSC) in the context of Industry 4.0 has further driven the adoption of artificial intelligence (AI) for production planning, logistics and sustainability considerations. But an increasing body of evidence suggests that the environmental implications are less a matter of AI adoption and more about how effectively AI complements human judgment and human skills. The paper contributes by introducing a meta-analysis on the function of human–AI co-decision systems and labour intelligence as enablers for circular economy (CE) in production systems. Based on PRISMA-2020 checklist, 269 Scopus-indexed empirical studies published through 2018 to 2025 were systematically screened and meta-analyzed by applying random-effect meta-analytic method. The findings reveal a robust and positive association with statistical significance between human–AI co-decision systems and the adoption of circular behavior, which ultimately enhances environmental performance. Workforce intelligence, including digital skills, collaborative capability and organization learning readiness enhances these relationships. Models that are based on a closely working relationship of the human and AI system continue to outperform dominant AI models, as well as highly assistant systems. Social sustainability outcomes are enhanced the most, whereas economic gains are rather modest, proving real-world trade-offs in implementation. Together, the results underscore the significance of human-centric design of AI and workforce readiness in driving sustainable and resilient CSC.
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Abderahman Rejeb, Karim Rejeb, Heba F. Zaher et al.· Quality & Quantity· 0 citations
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