Smart Transitions: Digital Technologies Empowering Sustainability and Circular Economy in Industry
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 41
Special Issue Editors
Interests: operations and quality management with a focus on service innovation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Industry sectors are facing urgent environmental and social challenges. Digital transformation is emerging as a catalyst for change. This Special Issue invites the submission of cutting-edge research that explores how technologies such as the Internet of Things (IoT), artificial intelligence (AI), and/or big data analytics can drive sustainability and circular economy principles in industrial operations.
We welcome the submission of both theoretical and empirical contributions that propose novel management tools or decision support systems aimed at integrating the three pillars of sustainability and/or circularity with digital innovations. Tools may include assessment software, assessment checklists, circularity indicators, or simulators. Systems are understood as integrated sets of data, algorithms, and interfaces designed to support comprehensive and strategic decision-making for circularity in industrial sectors.
Topics of interest include, but are not limited to, the integration of digital tools specifically for sustainability and circular economy in industry and highlighting the novelty of combining AI, IoT, and big data analytics explicitly for circularity in industrial sectors, such as the following areas:
- Management tools for diagnosing digital technologies’ circularity:
Decision support tools aimed at diagnosing and evaluating the circularity of digital technologies combining AI, IoT, and big data, assisting industrial sectors in integrating circular practices into their operational strategies.
- Digital solutions for circular supply chains:
Digital tools and decision support systems combining AI, IoT, and big data designed to manage circular supply chains by optimizing the flow of materials, resources, wastes, and information in industrial sectors.
- Predictive analytics for resource efficiency:
Predictive analytics tools that support decision-making combining AI, IoT, and big data by optimizing resource usage and minimizing waste through product lifecycles for circularity in industrial sectors.
- Sustainable sourcing and traceability:
AI-, IoT-, and big data-based tools supporting strategic decisions in sustainable sourcing and enhancing material traceability throughout the value chain for circularity in industrial sectors.
This Special Issue seeks to bridge the gap between digital innovation, sustainability, and circularity impact, encouraging interdisciplinary perspectives in engineering.
Dr. Marlene Amorim
Guest Editor
Dr. Adriane Cavalieri
Guest Editor Assistant
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.
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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
- circular economy in industrial sectors
- circular supply chains
- circular waste management
- circular-oriented decision support systems
- circular decision support tools
- Internet of Things
- artificial intelligence
- big data analytics
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