Call for Chapters: From Linear to Circular Business Models – AI-Driven Sustainable Growth in Emerging Markets (Palgrave Macmillan, Scopus-Indexed)
Published in Social Sciences, Sustainability, and Business & Management
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!
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Dear Editors,
I would like to submit the following chapter proposal for consideration in your edited volume *From Linear to Circular Business Models — AI-Driven Sustainable Growth in Emerging Markets*.
Proposed Chapter Title
Generative AI and Social Media Intelligence for Circular Business Model Innovation in Emerging Markets: A Capability‑Based Framework and Research Agenda
Abstract
Emerging markets face mounting pressure to move from linear, extractive models toward circular business models (CBMs) while simultaneously navigating rapid digitalization and fragmented data ecosystems. Although artificial intelligence is widely recognized as a catalyst for sustainable, growth‑oriented transformation, the specific mechanisms through which generative AI (GenAI) and social media intelligence enable circular business model innovation remain under‑theorized, particularly in resource‑constrained and institutionally complex contexts. This chapter addresses this gap by proposing a capability‑based conceptual framework that links GenAI‑driven social media intelligence to circular business model innovation in emerging markets.
We conceptualize generative AI models (large language models, multimodal generators, conversational agents) as augmenting a multi‑layer social media intelligence capability. The framework distinguishes three interrelated mechanisms: (1) generative extraction and sense‑making of circularity‑relevant signals from unstructured social data, allowing firms to detect reuse, repair, and recycling preferences in real time; (2) AI‑enabled stakeholder engagement and co‑creation of closed‑loop value propositions via platform‑mediated interactions; and (3) predictive sustainability analytics for anticipating resource flows and demand fluctuations, thereby supporting the redesign of value loops and circular supply‑chain configurations. Anchored in dynamic capabilities and socio‑technical transition perspectives, the framework explains how these mechanisms can reorient firms from linear value capture toward regenerative, circular growth trajectories.
Methodologically, the chapter combines a focused, Scopus‑based mapping of work at the intersection of GenAI, social media analytics, circular economy, and emerging markets with illustrative cases (e.g., Indian textile SMEs, Kenyan agritech platforms, Southeast Asian electronics recycling ecosystems) to ground the framework empirically. The chapter concludes with a targeted research agenda specifying propositions, methodological pathways, and governance issues (including data sovereignty and algorithmic bias) for scaling AI‑driven circular business models in emerging economies.
Author
Dr. Nidal Al Said, Associate Professor, College of Mass Communication, Ajman University, Ajman, United Arab Emirates.
Email: n.alsaid@ajman.ac.ae
Kind regards,
Dr. Nidal Al Said
Dear Editors,
My abstract is ready but I am unable to find where it is to be sent. So, pls provide email id or any other option for the same.
Chapter Title: Strategic use of Eco-Labels for Circular Value Creation: Sustainable Marketing Strategies in Emerging Agrifood Markets
Authors
Chetan Khanna, Assistant Professor, Department of Commerce, LPC, Lucknow, Uttar Pradesh, India
Mustfa Hussain, Associate Professor, Department of Agriculture, IIAST, Integral University, Lucknow, Uttar Pradesh, India
Correspondence Author: mail2drmustfahussain@gmail.com
Abstract
Background
The emerging environmental issues and resource constraints in developing economies have intensified the need to transition from linear to circular economic systems. In the agrifood sector, eco-labeling has emerged as a prominent sustainability signaling mechanism; however, its role in enabling circular value creation remains underexplored, particularly in emerging markets such as India where consumer awareness and trust remain limited.
Objectives
This study aims to: (i) analyze the role of eco-labeling in influencing consumer trust and sustainable purchase behavior, (ii) examine its linkage with circular supply chain practices, and (iii) develop a conceptual framework integrating eco-labeling with circular value creation.
Research Methodology
The study adopts a mixed-method approach, combining secondary data analysis from global reports (FAO, World Bank) with multiple case studies of leading Indian agrifood firms. The analysis is supported by thematic interpretation and comparative assessment.
Major Findings
The findings shows that eco-labeling enhances consumer trust and positively influences purchase intentions when supported by transparency and credible certification. However, its contribution to circular value creation depends on its integration with supply chain practices such as waste reduction, resource efficiency, and traceability. Key barriers include lack of standardization, weak regulatory frameworks, and low consumer awareness.
Conclusion
The study concludes that eco-labeling can serve as a catalyst for circular transformation only when embedded within broader sustainable marketing and supply chain strategies. It provides important implications for policymakers and practitioners to strengthen certification systems and promote sustainable consumption.
Keywords
Eco-labeling, Circular economy, Agrifood markets, Sustainable marketing, Consumer behavior, Emerging economies
Regards
Mustfa Hussain, Associate Professor, Department of Agriculture, IIAST, Integral University, Lucknow, Uttar Pradesh, India
Email: mail2drmustfahussain@gmail.com
Hi
Will you be sharing any link, where we can upload our abstracts?
Do let me know thanks.
hey may i get the link of abstract submission?
Dear Editors,
My abstract is ready but I am unable to find where it is to be sent. So, pls provide email id.
Dear Editors:
Greetings! I would like to submit my abstract for the book chapter. However, I cannot find any email ID or portal where I can submit it. Would you please share the email ID or portal link? Thank you.
Rumi Akter
Lecturer, BRAC University, Bangladesh
Dear Editors,
I hope this message finds you well. I am writing to propose a chapter contribution for your forthcoming edited volume, "From Linear to Circular Business Models: AI-Driven Sustainable Growth in Emerging Markets" (Palgrave Macmillan), in response to the open call published via Springer Nature Research Communities.
I am Sajadul Islam Emon, an undergraduate researcher in the Department of Agricultural Science at Daffodil International University, Dhaka, Bangladesh. My research interests span agricultural biotechnology, crop residue management, and sustainable agricultural systems in South Asian context.
Title:From Stubble to Sustainability: AI-Enabled Agricultural Residue Valorization and Circular Bioeconomy Transitions Among Smallholder Farmers in Bangladesh
Thematic Alignment:
This chapter primarily aligns with Topic 7 (Agriculture, Food Systems, and Resource Recovery) while drawing meaningfully from Topics 5, 11, and 14 that incorporates nformal sector integration, social dimensions of rural transitions, and a comparative South Asian perspective. It contributes a Bangladesh-specific empirical and policy lens that is currently underrepresented in the global circular economy literature.
Abstract:
Agricultural crop residue is one of the largest underutilized biomass resources in South Asia, with an estimated resource of 30-35 million tonnes of agricultural crop residue being produced in Bangladesh every year, of which the major component is the rice straw, jute stalks, wheat straw and sugarcane bagasse. For the 16 million smallholder farm households in the country, that's not a cost, it's a potential circular resource that can fuel a rural bioeconomy.
The chapter explores the potential of AI technologies to revolutionize the way biomass is managed in Bangladesh, from biomass yield prediction using ML to monitoring residues with IoT to optimizing AD processes with AI systems that create a circular biomass value chain. Based on the theoretical framework of the circular bioeconomy and the socio-technical transition model, the chapter describes the status quo of the residue valorization ecosystem in Bangladesh, highlighting relevant bottlenecks in the collection of feedstocks, decentralized biogas production, recovery of biofertilizers, and market access of smallholders.
The chapter introduces a conceptual framework for residue valorisation with artificial intelligence adapted to the specific conditions of low infrastructure rural areas, where the access to data is weak, the farms are small holdings and the informal chain has a major role in aggregating biomass. It analyzes critically the application of precision agriculture AI technologies designed for large farming systems to the context of the smallholder, and identifies the adaptations needed. The socially inclusive pathway for technology dissemination via digital extension services, mobile based AI advisory services and community-level biogas cooperatives is examined.
Comparisons are drawn with similar transitions in circular bioeconomy in India, Vietnam and Indonesia for developing policy recommendations for the Government of Bangladesh. The chapter concludes that AI-powered agricultural waste valorisation can be a replicable solution for Bangladesh to achieve SDG 2, SDG 7, SDG 12, and SDG 13 with a smallholder equity lens.
Keywords: Agricultural residue valorization, circular bioeconomy, smallholder farmers, anaerobic digestion, AI in agriculture, Bangladesh, South Asia, biomass, rural sustainability
I am prepared to submit a full chapter of approximately 7,000–9,000 words within the timeline stipulated by the editorial team following abstract acceptance. I am also open to co-authorship arrangements with researchers whose work complements this chapter's scope, should the editors consider such collaboration beneficial to the volume.
I would be grateful for any feedback on the suitability of this proposal and welcome a conversation at your convenience.
Thank you sincerely for this opportunity and for your dedication to producing a volume of this scope and importance.
Warm regards,
Sajadul Islam Emon
Department of Agricultural Science
Daffodil International University
Savar, Dhaka, Bangladesh
Email: emonkhan56481@gmail.com