Green Logistics and Sustainable Supply Chain Strategies
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".
Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 3363
Special Issue Editors
Interests: manufacturing/remanufacturing; maintenance/production; simulation; discrete event system theory; risk assessment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Given the current circumstances, companies are increasingly recognizing the importance of integrating sustainable practices into their operations in order to reduce their impact on the environment, preserve the Earth's resources and satisfy consumer expectations. Overall, sustainability has become a priority for many supply chain managers, who recognize the importance of balancing economic, environmental and social concerns in their operations. Indeed, managers should implement a range of strategies to ensure supply chain sustainability, such as reducing waste, enhancing energy efficiency, sourcing materials and components from sustainable suppliers, and adopting circular economy principles.
Due the complexity of the current socio-economic situation, manufacturers face challenges such as the increasing scarcity of raw materials, unstable costs and unpredictable lead times. In order to reduce the environmental impact of business operations, this Special Issue aims to focus on sustainable approaches by rethinking the product life cycle and promoting reuse, recycling and remanufacturing (reverse logistics). Therefore, we would like to invite you to submit a research paper related to the topic of reverse logic and the reuse of products.
This Special Issue aims to compile contributions that implement the application of digital technology in the factory, enabling the widespread dissemination of the concepts related to product reuse and material saving, and to inspire experts in the field.
The aim of this Special Issue is to create a community in which different players can share their expertise and contribute to all stages of reverse logistics, applying the concept of product reuse.
The scope of this Special Issue includes, but is not limited to, sustainable precision reverse logistics, focusing on REUSE in the following key areas:
- Application of big data and data analytics in order to achieve sustainable development in reverse logistics;
- Artificial intelligence (machine learning and deep learning) for logistics;
- Internet of Things (IoT) and traceability of reused and reintegrated products;
- Sustainability aspects (environmental–social–economic) of new technologies for reuse;
- Method and models for the simulation of the transport system for reused products;
- Life cycle assessment (LCA) and carbon footprint applications for reused products.
This Special Issue welcomes the submission of original research, analysis and review papers, in consultation with the editors.
We look forward to receiving your contributions.
Prof. Dr. Nidhal Rezg
Dr. Nadia Ndhaief
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.
Keywords
- sustainable development
- reuse
- supply chain and reverse logistics management
- circular economy
- Industry 4.0 to supply reused products
- multi-criteria decision-making
- optimization techniques and applications
- big data and data mining
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