Journal of Smart Computing ISSN 2979-8752 · Biannual
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Research Article · Vol. 2, No. 1 (2026)

Smart Supply Chain Management: A Comprehensive Framework Integrating Artificial Intelligence, Blockchain, and Big Data Analytics

Amir Amin*

Department of industrial engineering,college of engineering , university of Tehran, Tehran, Iran

* Corresponding author: Amir.amin@ut.ac.ir

Abstract Industry 4.0 technologies have changed how firms plan, execute, and monitor supply chain operations, increasing the need for frameworks that are simultaneously predictive, auditable, and analytically grounded. This paper proposes a Smart Supply Chain Management (SSCM) framework that combines artificial intelligence (AI), blockchain, and big data analytics. The architecture comprises three modules: an LSTM-based demand-forecasting engine, a smart-contract traceability platform, and a real-time analytics layer for operational decision-making. In a 24-month simulation of a multi-echelon network, the integrated design achieved 95.8% demand-forecast accuracy, reduced inventory holding costs by 31.2%, shortened the average lead time by 27.7%, and raised the composite transparency score by 141.5% relative to a conventional ERP baseline. Comparisons with AI-only and blockchain-only configurations indicate that the gains are complementary rather than interchangeable. The study contributes an empirically evaluated architecture and a set of implementation implications for firms deploying Industry 4.0 tools in multi-tier chains.

Keywords: Smart Supply Chain Management Artificial Intelligence, Blockchain Technology, Big Data Analytics, Industry 4.0

DOI
10.5281/zenodo.23266305
Pages
53-64
Published
7 Jun 2026
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To cite this article: Amin, A. (2026). Smart Supply Chain Management: A Comprehensive Framework Integrating Artificial Intelligence, Blockchain, and Big Data Analytics. Journal of Smart Computing , 2(1) , 53-64. https://doi.org/10.5281/zenodo.23266305

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