Artificial Intelligence’s Contribution to the Circular Economy in the Transition to Industry 5.0 via Industry 4.0

Dear Colleagues,

Artificial intelligence (AI) emerges as a promising catalyst in reshaping how humans and societies view sustainability (Ukonu, 2023). This Special Issue aims to explore the potential of AI to enable the circular economy in the transition to Industry 5.0 via Industry 4.0. The circular economy refers to an economic system based on reuse, reduction, recycling, and the extraction of materials from end-of-life products to accomplish long-term sustainable development goals (Awan et al., 2021; Kirchherr al., 2017). The term Industry 5.0 has been coined to describe the creation of a hyperconnected, data-driven industrial environment with an emphasis on sustainable development (Javaid & Haleem, 2020). Industry 5.0 is characterized by the integration of sustainability, resilience, and human-centric AI architecture into industrial value creation (van Erp et al., 2024). This Special Issue is envisioned to showcase state-of-the-art research on AI’s contribution to the circular economy in the transition to Industry 5.0 via Industry 4.0. To this end, this Special Issue invites empirical research articles and theoretical review papers that explore the intersection between two emerging megatrends: AI and the circular economy. More specifically, authors are encouraged to submit their research investigating the potential of transformative AI technologies and machine learning algorithms to contribute to the circular economy.

In this Special Issue, original research articles and systematic reviews are welcome. Research areas and themes may include (but are not limited to) the following:

• Transformative AI’s contribution to sustainability (environmental, economic, and social) and sustainable development goals (SDGs);
• The role of AI in the acceleration of the transition to a circular economy;
• The use of AI, machine learning, and deep learning in price forecasting/setting for circular business models;
• The social responsibility of AI-empowered businesses for sustainable development goals in diverse industry sectors (agriculture, biotechnology, construction, education, electronics, energy, fashion, finance, food, healthcare, hospitality, media, telecommunication, transportation, and so forth);
• The use of AI for the improvement and optimization of infrastructure for a circular economy;
• The use of AI to boost the reuse of electronic devices;
• The potential of AI for the development of circular products, components, and materials;
• The potential of AI for building a circular food system;
• The potential of AI for a sustainable energy future;
• Social, ethical, economic, and policy implications of AI technologies for the transition to Industry 5.0 via Industry 4.0.

I look forward to receiving your contributions.

References and Recommended Readings:

1. Awan, U., Sroufe, R., & Shahbaz, M. (2021). Industry 4.0 and the circular economy: A literature review and recommendations for future research. Business Strategy and the Environment, 30(4), 2038-2060.
2. Filho, W. L., Mbah, M. F., Dinis, M. A. P., Trevisan, L, V., de Lange, D., et al. (2024). The role of artificial intelligence in the implementation of the UN Sustainable Development Goal 11: Fostering sustainable cities and communities. Cities, 150, 105021.
3. Hallioui, A., Herrou, B., Santos, R. S., Katina, P. F., & Egbue, O. (2022). System-based approach to contemporary business management: An enabler of business sustainability in a context of industry 4.0, circular economy, competitiveness, and diverse stakeholders. Journal of Cleaner Production, 373, 133819.
4. Javaid, M., & Haleem, A. (2020). Critical components of Industry 5.0 towards a successful adoption in the field of manufacturing. Journal of Industrial Integration and Management, 5(3), 327-348.
5. Kar, A. K., Choudhary, S. K., & Singh, V. K. (2022). How can artificial intelligence impact sustainability: A systematic literature review. Journal of Cleaner Production, 376, 20, 134120.
6. Kirchherr, J., Reike, D., & Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources, Conservation and Recycling, 127, 221–232.
7. Madanaguli, A., Sjödin, D., Parida, V., & Mikalef, P. (2024). Artificial intelligence capabilities for circular business models: Research synthesis and future agenda. Technological Forecasting and Social Change, 200, 123189.
8. Sjödin, D., Parida, V., & Kohtamäki, M. (2023). Artificial intelligence enabling circular business model innovation in digital servitization: Conceptualizing dynamic capabilities, AI capacities, business models and effects. Technological Forecasting and Social Change, 197, 122930.
9. Ukonu, C. (2023). 4 ways AI can super-charge sustainable development. World Economic Forum. https://www.weforum.org/agenda/2023/11/ai-sustainable-development/#:~:text=AI's%20unparalleled%20data%2Dharnessing%20abilities,large%20round%20to%20the%20cause.
10. Van Erp, T., Carvalho, N. G. P., Gerolamo, M. C., Goncalves, R., Maly-Rytter, N. G., & Gladysz, B. (2024). Industry 5.0: A new strategy framework for sustainability management and beyond. Journal of Cleaner Production, 461, 142271.
11. Zechiel, F., Blaurock, M., Weber, E., Büttgen, M., & Coussement, K. (2024). How tech companies advance sustainability through artificial intelligence: Developing and evaluating an AI x sustainability strategy framework. Industrial Marketing Management, 119, 75-89.

Dr. Seunga Venus Jin
Guest Editor

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• artificial intelligence
• machine learning
• deep learning
• circular business models
• algorithm-based decision making
• digital transformation
• sustainability
• circular economy
• Industry 4.0
• Industry 5.0
• sustainable development goals (SDG)