AI for Sustainable Supply Chain-Driven Business Transformation
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 31 March 2026 | Viewed by 49
Special Issue Editors
Interests: supply chain management; decision analysis; artificial intelligence applications; e-commerce
Special Issues, Collections and Topics in MDPI journals
Interests: educational technology; gamified learning; generative AI in teaching; human resource development (HRD); organizational learning; learning analytics; competency-based education; smart campus development
Special Issue Information
Dear Colleagues,
The rise in Artificial Intelligence (AI), particularly Generative AI, presents an unprecedented opportunity to address these challenges head-on. This Special Issue, “AI for Sustainable Supply Chain-Driven Business Transformation”, seeks to deeply explore how AI technologies can become the core engine driving sustainable innovation in supply chains and transformative change in enterprise operations. We are interested in practical applications of AI, such as enhancing resource efficiency through intelligent decision-making, reengineering processes with data-driven insights, accurately forecasting and mitigating risks, and pioneering new models for the circular economy. This Special Issue looks beyond the technology itself, emphasizing its profound impact on areas like organizational learning and talent development.
Past research has often treated AI in supply chain management and business transformation as separate domains. However, we believe the two are inextricably linked, and that their synergy is the key to unlocking their full potential. This Special Issue therefore aims to bridge this research gap. We seek integrative, systemic perspectives that explore practical pathways to sustainability at both the operational and strategic levels. Our core objective is to investigate how AI can help build greener, more efficient, and more resilient business models, positioning the supply chain as the strategic pivot for this transformation.
We sincerely invite submissions of all types, including theoretical frameworks, applied research, and case studies, especially those that highlight cross-functional collaboration and the value of human–AI synergy. We look forward to bringing together your insights and expertise to collectively contribute to the long-term goals of environmental, economic, and organizational sustainability.
Recommended topics include, but are not limited to, the following:
Generative AI for Sustainable Supply Chain Strategy Design:
Explore how Generative AI can support the creation of innovative, sustainability-focused supply chain strategies by simulating scenarios and co-developing adaptive solutions with human experts.
AI-Driven Supply Chain Decision Support Systems:
Analyze how AI technologies enhance decision-making across supply chains by processing complex operational, environmental, and logistical data in real time to optimize sustainability performance.
Human–AI Collaboration in Sustainable Operations:
Investigate models of collaborative intelligence where human decision-makers and AI systems jointly contribute to the development and implementation of green business solutions.
Process Reengineering with AI for Low-Carbon Operations:
Examine how AI tools identify inefficiencies and redesign supply chain workflows to reduce emissions, improve energy efficiency, and support lean-green manufacturing practices.
Digital Twins for Environmental Simulation and Forecasting:
Assess how digital twin technologies combined with AI can simulate supply chain activities to evaluate environmental impact and support agile responses to sustainability challenges.
AI Applications in Circular Economy and Resource Recovery:
Study how AI supports circular supply chain models by forecasting material flow, optimizing recycling logistics, and enabling closed-loop production planning.
Knowledge Management and Organizational Learning with Generative AI:
Explore how Generative AI can enhance sustainability-related knowledge sharing by generating contextualized learning materials and synthesizing insights from organizational data.
AI-Enhanced Talent Development for Green Supply Chains:
Analyze how AI technologies enable personalized training, competency mapping, and workforce development aligned with the skills needed for sustainable operations.
Ethical and Governance Issues in AI-Powered Sustainability Initiatives:
Examine the ethical implications, regulatory challenges, and governance mechanisms required to ensure responsible use of AI in environmentally sensitive business transformations.
Explainable AI for Transparent Sustainability Practices:
Investigate how explainable AI supports stakeholder trust, improves decision transparency, and ensures compliance in AI-driven supply chain sustainability efforts.
Prof. Dr. Shu-Chu Liu
Dr. Chih-Hung Chung
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence (AI)
- sustainable supply chain management
- business transformation
- human–AI collaboration
- decision support systems
- process reengineering
- organizational learning
- risk management
- circular economy
- digital twin
- Gen AI
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