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Circular Economy Transitions in Textile, Apparel, and Fashion: AI-Based Topic Modeling and Sustainable Development Goals Mapping

Author

Listed:
  • Raghu Raman

    (Amrita School of Business, Kollam Campus, Amrita Vishwa Vidyapeetham, Kollam 690525, Kerala, India)

  • Payel Das

    (Amrita School of Business, Amaravati Campus, Amrita Vishwa Vidyapeetham, Amaravati 522503, Andhra Pradesh, India)

  • Rimjhim Aggarwal

    (School of Sustainability, Arizona State University, Tempe, AZ 85287, USA)

  • Rajesh Buch

    (School of Sustainability, Arizona State University, Tempe, AZ 85287, USA)

  • Balasubramaniam Palanisamy

    (Amrita School of Business, Coimbatore Campus, Amrita Vishwa Vidyapeetham, Coimbatore 641112, Tamil Nadu, India)

  • Tripti Basant

    (School of Sustainability, Arizona State University, Tempe, AZ 85287, USA)

  • Urvashi Baid

    (Amrita School of Business, Coimbatore Campus, Amrita Vishwa Vidyapeetham, Coimbatore 641112, Tamil Nadu, India)

  • Pozhamkandath Karthiayani Viswanathan

    (Amrita School of Business, Kollam Campus, Amrita Vishwa Vidyapeetham, Kollam 690525, Kerala, India)

  • Nava Subramaniam

    (Amrita School of Business, Coimbatore Campus, Amrita Vishwa Vidyapeetham, Coimbatore 641112, Tamil Nadu, India)

  • Prema Nedungadi

    (Amrita School of Computing, Amritapuri Campus, Amrita Vishwa Vidyapeetham, Amritapuri 690525, Kerala, India)

Abstract

This study focuses on the shift to a circular economy (CE) in the textile, apparel, and fashion (TAF) sectors, which generate tons of waste annually. Thus, embracing CE practices is essential for contributing to UN Sustainable Development Goals. This study employs a mixed-methods approach, integrating PRISMA for systematic literature selection, BERTopic modeling and AI-driven SDG mapping, and case study analysis to explore emerging CE themes, implemented circular practices, and systemic barriers. Machine-learning-based SDG mapping reveals strong linkages to SDG 9 and SDG 12, emphasizing technological advancements, industrial collaborations, and circular business models. Moderately explored SDGs, namely, SDG 8, SDG 6, and SDG 7, highlight research on labor conditions, water conservation, and clean energy integration. Reviewing 655 peer-reviewed papers, the BERTopic modeling extracted six key themes, including sustainable recycling, circular business models, and consumer engagement, whereas case studies highlighted regulatory frameworks, stakeholder collaboration, and financial incentives as critical enablers. The findings advance institutional theory by demonstrating how certifications, material standards, and regulations drive CE adoption, reinforcing SDG 12 and SDG 16. The natural resource-based view is extended by showing that technological resources alone are insufficiently aligned with SDG 9. Using the Antecedents–Decisions–Outcomes framework, this study presents a structured, AI-driven roadmap for scaling CE in the TAF industry, addressing systemic barriers, and supporting global sustainability goals, highlighting how multistakeholder collaboration, digital traceability, and inclusive governance can improve the impact of CE. The results recommend that CE strategies should be aligned with net-zero targets, carbon credit systems, and block-chain-based supply chains.

Suggested Citation

  • Raghu Raman & Payel Das & Rimjhim Aggarwal & Rajesh Buch & Balasubramaniam Palanisamy & Tripti Basant & Urvashi Baid & Pozhamkandath Karthiayani Viswanathan & Nava Subramaniam & Prema Nedungadi, 2025. "Circular Economy Transitions in Textile, Apparel, and Fashion: AI-Based Topic Modeling and Sustainable Development Goals Mapping," Sustainability, MDPI, vol. 17(12), pages 1-36, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5342-:d:1675327
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    References listed on IDEAS

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    1. Shobod Deba Nath & Syed Sharaf Mustayin & Gabriel Eweje, 2025. "Circular Economy in a Developing Country's Textile and Apparel Industry: Managerial Perspectives on Challenges and Motivators," Business Strategy and the Environment, Wiley Blackwell, vol. 34(3), pages 3600-3617, March.
    2. Lisa Messeri & M. J. Crockett, 2024. "Artificial intelligence and illusions of understanding in scientific research," Nature, Nature, vol. 627(8002), pages 49-58, March.
    3. Joe Miemczyk & Mickey Howard & Thomas Johnsen, 2016. "Dynamic development and execution of closed-loop supply chains: a natural resource-based view," Post-Print hal-01290920, HAL.
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    5. Catarina Carvalho & Carla Joana Silva & Maria José Abreu, 2025. "Circular Economy: Literature Review on the Implementation of the Digital Product Passport (DPP) in the Textile Industry," Sustainability, MDPI, vol. 17(5), pages 1-28, February.
    6. Inhwa Kim & Hye Jung Jung & Yuri Lee, 2021. "Consumers’ Value and Risk Perceptions of Circular Fashion: Comparison between Secondhand, Upcycled, and Recycled Clothing," Sustainability, MDPI, vol. 13(3), pages 1-23, January.
    7. Yi, Jisu & Oh, Yun Kyung & Kim, Jung-Min, 2025. "Unveiling the drivers of satisfaction in mobile trading: Contextual mining of retail investor experience through BERTopic and generative AI," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    8. Raghu Raman & Walter Leal Filho & Hector Martin & Suparna Ray & Dayana Das & Prema Nedungadi, 2024. "Exploring Sustainable Development Goal Research Trajectories in Small Island Developing States," Sustainability, MDPI, vol. 16(17), pages 1-25, August.
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    Cited by:

    1. Netranand Pathak & Shashi Kant Rai & Richa Sharma, 2026. "Identifying and Overcoming Barriers To Circular Supply Chain Management in the Textile Industry: an ISM and MICMAC Approach," Circular Economy and Sustainability, Springer, vol. 6(1), pages 1-35, February.
    2. Garima Singh, 2026. "Ranking Barriers and Interventions for Circular Economy in Fashion: A Theory-Anchored Multi-Stakeholder Study," Circular Economy and Sustainability, Springer, vol. 6(2), pages 1-39, April.

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