Emerging markets face a unique challenge: how to pursue economic growth while avoiding the environmental costs of linear "take-make-dispose" models. At the same time, Artificial Intelligence is opening up remarkable new possibilities for resource efficiency, waste reduction, and circular value creation. Our forthcoming book, "From Linear to Circular Business Models: AI-Driven Sustainable Growth in Emerging Markets", brings these two conversations together for the first time in a single comprehensive volume.

What is this book about?

This edited book, published by Palgrave Macmillan (Springer Nature) and Scopus-indexed, sits at the intersection of AI innovation, circular economic principles, and sustainable development in emerging economies. It integrates insights from business management, environmental sustainability, information technology, development economics, and public policy — combining rigorous theoretical frameworks with real-world case studies, implementation strategies, and policy recommendations. The book directly engages multiple UN Sustainable Development Goals, including SDG 9, SDG 12, SDG 13, SDG 8, and SDG 17.

Why is this book important?

While much of the existing literature on circular economy and AI focuses on advanced economies, the most dramatic opportunities — and the most pressing needs — lie in emerging markets. Countries across ASEAN, the BRICS, and beyond are urbanizing rapidly, building new infrastructure, and shaping industrial systems that will define resource consumption patterns for decades. This book addresses a critical gap by examining how AI can help these nations leapfrog linear models entirely and build circular systems from the ground up. For researchers, this is a chance to contribute to a field that is both intellectually rich and urgently relevant to global sustainability.

Why contribute to this book?

Your chapter will be published by Palgrave Macmillan, one of the world's leading academic publishers, and the book will be Scopus-indexed — giving your work visibility and scholarly impact. You will join a distinguished editorial team led by Prof. Mani Venkatesh (Asper School of Business, University of Manitoba, Canada) and Dr. Giang NT Nguyen (Ho Chi Minh City University of Economics and Finance, Vietnam), alongside an international community of contributors working at the frontier of AI, sustainability, and development research.

Who is involved?

The book is led by Prof. Mani Venkatesh, whose research expertise spans business innovation and sustainable development, and Dr. Giang NT Nguyen, a Senior Research Fellow specializing in emerging market economies and circular transitions. Together, they bring a cross-continental editorial perspective that reflects the global scope of the book itself.

Topics we welcome include (but are not limited to):

 1. Foundations of AI and the Circular Economy in Emerging Markets

Explore foundational frameworks linking how AI can drive circular economic transitions in emerging markets, connecting innovation with sustainable development.

2. AI Technologies Enabling Circular Transitions

Examine how machine learning, computer vision, IoT, and blockchain enable circular value creation, drawing on industrial ecology and socio-technical transition theories

3. The Emerging Market Context: Opportunities and Constraints

Examine how economic development, environmental challenges, digital infrastructure, policy landscapes, and socio-cultural factors shape AI-driven circular transitions in emerging markets.

4. Smart Manufacturing and Industrial Symbiosis

Explore AI-optimized production systems for waste reduction, predictive maintenance, asset lifecycle management, and industrial symbiosis platforms.

5. Intelligent Waste Management and Recycling Systems

Explore AI-powered waste sorting, smart collection logistics, informal-sector integration, and municipal waste management in emerging market cities.

6. Circular Supply Chains and Product Lifecycle Management

Examine AI-enabled supply chain transparency, reverse logistics, take-back systems, and product-as-a-service models across electronics, textiles, and consumer goods.

7. Agriculture, Food Systems, and Resource Recovery

Explores precision agriculture, AI-driven food waste reduction, nutrient recovery, and biomass valorization, with applications in emerging nations.

8. Built Environment and Urban Circularity

Addresses smart buildings, construction waste reduction, material reuse, urban mining, and smart city initiatives in emerging market megacities.

9. Circular Business Models and Innovation Strategies

Analyze AI-enabled circular business models, start-up ecosystems, corporate sustainability strategies, and financing considerations.

10. Policy Frameworks and Governance

Review national circular economy strategies, digital and AI governance, regulatory challenges, and public–private partnership models.

11. Social Dimensions and Just Transitions

Examine employment impacts, informal-sector workers, digital divides, and consumer behavior change in AI-driven circular transitions.

12. Financing and Investment for Circular Innovation

Explore green finance, blended finance, impact investing, and ESG considerations for AIcircular ventures.

13. Challenges, Risks, and Limitations of AI for the Circular Economy

Address data privacy, AI's energy footprint, rebound effects, and implementation barriers in emerging markets.

14. Comparative and Cross-Country Case Studies

Present empirical analyses across China, India, ASEAN nations, and other emerging markets, identifying common patterns and context-specific variations.

15. Regional Cooperation, Knowledge Transfer, and Scaling

Examine cross-border collaboration, South–South knowledge sharing, technology diffusion, and pathways for scaling AI-enabled circular innovations.

16. Future Pathways and Research Agenda

Outline emerging technologies, research gaps, and how emerging market experiences can contribute to global circular economy transitions.

How can I submit my chapter?

 Proposal Submission: Interested authors should submit a 300-word abstract outlining the proposed chapter’s focus, objectives, and contribution to the field. Please include the authors' affiliations and contact information.

Full Chapter Submission: If selected, full chapters should be 7,000-10,000 words, including references and appendices. All submissions must follow Palgrave Macmillan’s Manuscript Guidelines.

Key Dates:

Abstract submission deadline: 30 August 2026

Notification of acceptance: 15 September 2026

Full chapter deadline: 31 December 2026

Final manuscript deadline: 30 August 2027

 
 We look forward to receiving your contributions!