Sustainable Supply Chain Management in Industry 4.0

Dear Colleagues,

Over the preceding decades, supply chain management has driven by the development of Industry 4.0  towards to a more efficient and greener system. Industry 4.0 embraces a set of future industrial developments regarding Internet of Things, cyber–physical systems, artificial intelligence, machine learning, data mining, cloud computing, blockchain, and big data analytics. Industry 4.0 represents the fourth industrial revolution and will offer wide prospects to gain competitive advantages and establish future sustainable supply chain practices.

Some of the changes that operations and their connected supply chains face are revolutionary, and this requires careful consideration from both practical and theoretical points of view. However, the implementation of I4.0 in SC remains in its infancy. Going forward, there is a need to explore how the Industry 4.0 helps organizations to monitor metrics on an ongoing basis, troubleshoot poor performance, and identify root cause, as well as enable the delivery of better business decisions and provide tremendous benefits through the improvement of business processes.

Thus, this Special Issue aims to explore the potential of Industry 4.0 opportunities available in supporting the data-driven revolution in sustainable supply chain space. In this Special Issue, we are looking for high-quality original research articles related (but not limited) to the following topics:

1. Environmental, social and governance (ESG) in supply chains;
2. Sustainable supply chain optimization in Industry 4.0;
3. Resilience in supply chains and logistics;
4. Product/service tracibility with blockchain in supply chain;
5. Digital twin frameworks and methodologies for sustainable supply chains;
6. Artificial intelligence in manufacturing and transport logistics;
7. Use of simulation-based advanced data analytics for sustainable supply chain design;
8. Artificial intelligence/digital twin-driven logistics optimization;
9. Big data/artificial intelligence-driven e-commerce supply chains;
10. Data analytics and machine learning in sustainable supply chains;
11. Real-time optimization for green vehicel routing problem.

Dr. Zhitao Xu
Dr. Zhenyong Wu
Prof. Dr. Yaping Fu
Guest Editors

Manuscript Submission Information

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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.

• supply chain
• Industrial 4.0
• sustainability
• data analytics
• sustainable supply chain optimization
• logistics