Artificial Intelligence and Big Data Strategies for Sustainable and Resilient Supply Chain Management

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Supply Chain Management".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 896

Special Issue Editor


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Guest Editor
Department of Management, “Nicolae Balcescu” Land Forces Academy, 550170 Sibiu, Romania
Interests: intangible assets; sustainability; ESG supply chains; digital transformation; AI in economic and management; bibliometric analysis

Special Issue Information

Dear Colleagues,

The rapid development of Artificial Intelligence (AI) and Big Data analytics is transforming supply chain management (SCM), offering new opportunities for efficiency, resilience, and sustainability. Global supply chains face increasing challenges due to disruptions, regulatory pressures, and the growing importance of ESG (Environmental, Social, and Governance) compliance. Leveraging AI-driven models, predictive analytics, and data-intensive strategies offers a pathway toward smarter, more adaptive, and sustainable supply chains.

This Special Issue explores the integration of AI-driven models, predictive analytics, and data-driven strategies into supply chains, with particular attention to ESG (Environmental, Social, and Governance) compliance, risk management, and digital transformation. We welcome both theoretical and applied research, including empirical studies, econometric analyses, simulation models, optimization approaches, and case-based investigations.

Topics of interest may include, but are not limited to, the following:

  • AI-enabled decision support systems, machine learning, and deep learning applications in procurement, logistics, and demand forecasting.
  • Big Data–driven risk analytics, blockchain, IoT, and digital twin solutions for resilient and transparent supply chains.
  • Econometric modeling and causal inference approaches for analyzing resilience, productivity, and ESG outcomes.
  • Quantitative evaluation of sustainability and climate policies in digitalized supply chains.
  • Productivity and efficiency measurement in AI-enabled operations and logistics networks.
  • Input–output and computable general equilibrium (CGE) models to assess economic, social, and environmental spillovers of digital SCM.
  • Cross-country and sectoral comparative studies on AI and Big Data adoption and their macroeconomic implications.
  • Bibliometric and scientometric analyses of innovation trends at the intersection of AI, Big Data, and sustainable SCM.

This Special Issue fits the scope of Systems by examining supply chains as complex socio-technical systems shaped by technological, environmental, and institutional dynamics. The integration of AI, Big Data, and digital tools reflects a systemic and holistic perspective on resilience, sustainability, and ESG compliance. By combining systems theory, econometric modeling, and interdisciplinary approaches, this Issue addresses operations, logistics, and digitalization in line with the journal’s focus on complex adaptive systems and socio-technical integration.

We look forward to receiving your contributions.

Dr. Sebastian-Emanuel Stan
Guest Editor

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Keywords

  • artificial intelligence in supply chain management
  • big data analytics
  • sustainable supply chains
  • ESG-oriented management
  • digital transformation
  • smart logistics
  • resilience and risk management
  • econometric modeling
  • productivity and efficiency
  • decision support systems

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Published Papers (1 paper)

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38 pages, 916 KB  
Systematic Review
Integrating Business Intelligence and Operations Research for Sustainable Supply Chain Systems: A Systematic Review
by Rui Pedro Marques and Dorabella Santos
Systems 2025, 13(12), 1111; https://doi.org/10.3390/systems13121111 - 10 Dec 2025
Viewed by 584
Abstract
This systematic review explores how business intelligence (BI) and operations research (OR) help organizations ensure sustainable practices in supply chain management (SCM). Drawing on 56 peer-reviewed studies, this review synthesizes how BI tools support sustainability by transforming large and complex datasets into actionable [...] Read more.
This systematic review explores how business intelligence (BI) and operations research (OR) help organizations ensure sustainable practices in supply chain management (SCM). Drawing on 56 peer-reviewed studies, this review synthesizes how BI tools support sustainability by transforming large and complex datasets into actionable insights, enhancing transparency, improving forecasting, optimizing production and inventory, reducing waste, and enabling circular economy practices. Complementarily, OR provides methodological rigor through optimization models, simulation, and multicriteria decision-making, enabling organizations to balance economic, environmental, and social objectives in supply chain design and operations. The findings reveal that BI and OR jointly contribute to 11 of the 17 United Nations Sustainable Development Goals (SDGs), demonstrating their strategic relevance for global sustainable development. This paper’s contribution is twofold: it consolidates fragmented academic research through an integrative framework clarifying how BI and OR reinforce sustainability within SCM, and it provides practitioners with evidence of how these tools can generate both operational efficiency and a competitive advantage while meeting environmental and social responsibilities. Future research should focus on bridging existing gaps in the literature and advancing the practical applications of these technologies. Full article
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