Exploring blockchain technologies in sustainable supply chains – unveiling the latent research topics using an AI approach

Peter Madzík, Lukáš Falát and Fatma Pakdil

International Journal of Production Research, 2025, vol. 63, issue 21, 8047-8073

Abstract: Blockchain technology is reshaping sustainable Supply Chain Management (SSCM) by enhancing transparency, efficiency, and security. This study introduces an unsupervised machine learning approach, leveraging Latent Dirichlet Allocation (LDA) to systematically analyse over 4,000 scholarly articles and uncover latent research topics in blockchain applications for SSCM. Our findings reveal 60 key topics, with high-impact areas including food safety, healthcare, smart contracts, agriculture, and blockchain adoption barriers. The study identifies the fastest-growing research domains – food safety and implementation challenges – while highlighting underexplored areas such as trust and privacy protection. Additionally, we provide a first-of-its-kind systematic mapping of blockchain research trends across geographical regions, showing Asia’s dominance, particularly in China and India. Our integration of advanced topic modelling with bibliometric analysis offers a deeper, data-driven understanding of blockchain’s role in SSCM, bridging qualitative insights with quantitative evidence. By identifying research gaps and emerging trends, this study serves as a roadmap for future blockchain innovations in supply chains, emphasising their role in addressing sustainability challenges and enhancing operational resilience, efficiency and transparency.

Date: 2025
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DOI: 10.1080/00207543.2025.2507800

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