Corresponding Manager: Helen S. Du (s.du@psbedu.paris)
Track Manager(s): Helen S. Du, Juan Xu
Description
The Circular Economy (CE) seeks to extend product life cycles and minimize resource use and waste, generating environmental benefits through reduced emissions, greater renewable energy use, and efficient resource management. Artificial Intelligence (AI) can accelerate this transition towards a circular economy by enabling data-driven decision-making, automation, and optimization across supply chains, production, and governance. AI can reduce waste and emissions, encourage green business models, promote new clear energy, and improve resilience against climate changes. However, AI integration can also raise challenges related to data transparency, privacy, trust, and ethical and economic implications. Therefore, it is important to explore both the benefits and costs of AI in the circular economy.
This track invites research that examines how AI can enhance the efficiency, sustainability, and equity of circular systems, as well as the barriers and governance mechanisms required for responsible adoption. We encourage and welcome the research investigating how AI can be strategically leveraged to support the circular economy and the sustainability of geographical areas such as cities, regions and nations, which barriers need to be considered, and what ethical issues existing in AI adoption in the circular economy. We welcome theoretical, empirical, and policy-oriented contributions on these topics.
Keywords
The Circular Economy (CE), Artificial Intelligence (AI); environmental impacts; sustainability, ethics of AI
Key References
Stoyanov, S., & Stoyanova, V. (2025). Mitigating liabilities of foreignness in migrant entrepreneurship: The role of AI in building virtual embeddedness. Technological Forecasting and Social Change, 220, 124323.