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

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.

1. Introduction and Related Work

The textile, apparel, and fashion (TAF) industry is the second-largest polluting industry and one of the most environmentally taxing industries in the world. This industry deeply affects the social, economic, and ecological dimensions [1,2,3] and is outranked by the oil industry, which is the highest contributor to the landfill industry [3,4]. Largely operating around the “take make dispose” linear model, industry accounts for 20% of global water consumption and 10% of global carbon emissions [5,6]. With more than half of the garments discarded within a year, 92 million tons of waste are produced annually [5], and less than 1% of these materials can be recycled into new apparel [5,6].

Due to this alarming record, calls for a transition from the current linear business processes to circular processes (take, make, distribute, use, and recover) have repeatedly been made [7,8]. The circular economy (CE) principles for the TAF industry propose a sustainable and reformative approach designed to reduce waste and minimize environmental impact [2,9,10]. The objective of CE practices is to weaken loops of consumption and production with the aim of improving overall environmental quality, economic wealth, and social equity [11]. Research has highlighted various circular business models (CBMs), technologies, and practices to increase sustainability in the TAF industry by prolonging the life span of textiles by repurposing, recycling, and upcycling, thereby minimizing waste and the demand for virgin materials [8]. However, importantly, the implementation of these new CBMs, technologies, and practices continues to be very slow and fragmented relative to the urgency and scale of the sustainability challenges we face.

A recent report [12] similarly revealed that “the story of the circular economy thus far has often been one of modest ambition, localized initiatives, and small-scale or experimental projects implemented incoherently”. The report calls for the need for a CE to be “scaled up and globally coordinated” (ibid). Another mechanism for doing this that the report proposes is to better align CE initiatives with the United Nations Sustainable Development Goals (SDGs) [13], specifically in the TAF industry [14,15]. To date, CE initiatives have been peripheral to the SDG agenda, and progress on the SDG agenda itself is lagging, with only 17% of the goals achieved. However, the report makes the case that there are strong complementarities between the SDG agenda and the circular economy that need to be leveraged to scale up the global reach of the CE while also reviving the momentum toward the achievement of the SDGs. There are also new initiatives from the European Commission, such as the European Green Deal and the Circular Economy Action Plan, that are driving CE in the TAF [10].

The role of the CE in aligning business strategies with SDG targets is reinforced through diverse applications in the TAF industry, specifically in waste management, material efficiency, and sustainable production. Textile waste management strategies contribute to extending resource lifespans and reducing dependence on virgin materials [14], which aligns with SDG 7 (Clean and Affordable Energy), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production). The integration of agro-industrial waste, such as banana fibers, into textile manufacturing further exemplifies the potential of the CE to support sustainable material sourcing while advancing SDG 12, SDG 13 (Climate Action), and SDG 15 (Life on Land) [16]. In regions such as Bangladesh, where textile and apparel manufacturing generate significant material waste, Akter et al. emphasized the need for waste categorization, economic loss assessments, and mapping of informal waste trading networks to strengthen SDG 12 implementation [17].

In addition to waste reduction, CE initiatives in the apparel sector also foster job creation, technological innovation, and policy collaboration, aligning with SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 17 (Partnerships for the Goals) [15]. The transition toward Smart CE models, enabled by digital solutions and evaluated through decision-making frameworks such as the Best Worst Method (BWM) and gray DEMATEL, is facilitating SDG and net-zero targets by improving industry-wide sustainability practices, as explored by Govindan, K. (2023) [13]. Addressing broader sustainability concerns, Thakker and Sun examined the role of the CE in textiles and fashion, focusing on climate challenges, resource depletion, social inequalities, and production waste while emphasizing corporate responsibility and transparency across value chains [18]. Additionally, innovations such as repurposing bacterial cellulose from kombucha waste into bio textiles illustrate how CE principles can bridge industries, demonstrating the interconnected nature of the SDGs in promoting waste reduction, resource efficiency, and sustainable production [19].

Despite increasing research on CE in the TAF industry, gaps remain in understanding how CE practices align explicitly with the SDGs.

Table 1. Review of studies related to CE in TAF.

Reference	Key Findings	Gaps Identified	Number of Studies and Years
Leal Filho et al. [20]	Reuse and recycling offer socioeconomic benefits, but their implementation across industries is uneven and inconsistent.	Need for sector-specific research on sustainable recycling and CE strategies, particularly in material recovery for textiles.	88 studies from 1998 to 2018
Jia et al. [24]	The paper explores CE in the TAF industry, focusing on waste reduction, supply chain optimization, sustainable performance, and barriers like post consumption waste.	Limited focus on circular business models and institutional challenges in CE adoption within TAF, especially in emerging economies.	109 studies from 1979 to 2020
De Ponte et al. [25]	Identified themes in literature and gaps in research on green apparel and CE.	Lack of analysis on circular business models and their integration with digital technologies for transparency and supply chain traceability.	892 studies from 2020 to 2022
Abbate et al. [5]	Investigated sustainability trends in textile supply chains, highlighting gaps in circular supply chain integration and sustainable practices.	Need for research on consumer engagement and sustainable practices in a circular fashion economy, including behavioral factors affecting CE adoption.	178 studies from 2005 to 2022
Bonelli et al. [22]	Explores socioeconomic disparities in CE adoption within the fashion industry, emphasizing unequal access to circular technologies across regions.	Limited understanding of CE innovations in textile and leather waste valorization, particularly in regions where waste management infrastructure is weak.	117 studies from 2009 to 2023
Leal Filho et al. [6]	Organizations can use design thinking (DT) to implement the UN SDGs, providing human-centered, cost-effective solutions that enhance sustainability outcomes.	Need for research on CE innovations in textile and leather waste valorization, linking design thinking with sustainable materials and biodegradable alternatives.	22 studies case studies until 25 February 2023
Oliveira Neto et al. [21]	Developed a blended business model consisting of 27 CE practices, emphasizing resource recovery, product lifecycle extension, and waste reduction applicable to the TAF industry.	Insufficient studies on circular fashion supply chains and digital innovations for sustainability, particularly blockchain and IoT-driven traceability solutions.	48 studies from 2017 to 2023
Palm et al. [26]	Women are often underrepresented in policy and higher-value roles in CE. More inclusive policies are needed to address gendered labor in CE.	Lack of research on systemic barriers and enabling factors affecting CE adoption in textile and apparel supply chains, particularly from a gender and social equity perspective.	76 studies until 2024
Hossain et al. [23]	The paper emphasizes the need for cross-sectoral collaboration in business models and policies.	Limited focus on multistakeholder engagement in CE adoption within the TAF sector, particularly for integrating SMEs and large firms.	167 studies from 2013 to 2022
Saha et al. [8]	The study identifies that sustainability-oriented innovation and transition challenges dominate CE research in the TAF industry.	Research is needed on CE principles in TAF based on resource efficiency, with an emphasis on systemic implementation challenges across global supply chains.	132 studies from January 2014 to 2023

provides a summary of related review studies on the topic of CE and TAF, highlighting key findings and research gaps while positioning this study as a necessary step toward a more systematic understanding of CE–SDG linkages in the TAF industry. Several review studies have explored specific attributes of the CE, such as reuse and recycling [20], circular supply chain integration [5], and sustainable business models [21]. Others have examined socioeconomic disparities in CE adoption [22] and the role of cross-sectoral collaboration [23]. However, research often remains fragmented, lacking a comprehensive framework that systematically links CE strategies in the TAF industry to the full spectrum of all SDGs. Existing studies frequently focus on isolated aspects, such as material recovery, supply chain challenges, or consumer behavior, without addressing the broader systemic interconnections between the CE and sustainable development. While some research highlights the potential of circular business models [24] and digital innovations [25], there is limited empirical work assessing how these approaches collectively contribute to the SDGs. Furthermore, gender dimensions [26], institutional barriers [8], and multistakeholder engagement remain underexplored in the context of CE adoption in TAF.

To address these gaps, this study explicitly maps CE research in the TAF industry to all the SDGs, supporting a structured analysis of how circular strategies contribute to sustainable development. First, by integrating insights from key thematic areas—sustainable recycling, circular business models, resource efficiency, consumer engagement, textile waste valorization, and digital innovations—this study offers a more holistic perception of the role of the CE in achieving global sustainability targets. Second, through a qualitative review of case studies of CE in the TAF industry, we examine the practical aspects of how businesses have implemented CE principles, practices, and business models and how far their actions align with the SDGs. This mixed-methods approach enables the integration of broad thematic insights derived from topic modeling with the context-specific perspectives offered by case studies. Topic modeling helps identify overarching trends and recurring themes in the CE literature, such as practices and their alignment with the SDG, whereas case studies provide deeper insights into the practical challenges and opportunities of CE adoption in the TAF sector. The ADO framework [27,28] systematically categorizes (i) what drives CE adoption (A), (ii) what strategic decisions are taken by firms and policymakers (D), and (iii) what outcomes emerge (O), providing a structured approach to defining future research directions.

Accordingly, we propose the following research questions.

• RQ1: What are the emerging topics in the literature concerning the transition to a circular economy in the TAF industry? How do these topics link to specific SDGs?
• RQ2: What specific circular practices, circular business models (CBMs), and technologies have been implemented in specific contexts in the TAF industry, and how does this implementation map into the different SDGs and targets?
• RQ3: What are the systemic barriers and enabling factors identified through case studies for CE adoption in the TAF industry, and how can multistakeholder collaboration across TAF value chains mitigate these challenges to address the SDGs?

Against this background, the paper is organized as follows: Section 2 details the methodological approach, and Section 3 presents the results derived from these methods, emphasizing the key themes identified through topic modeling and the insights gained from case studies. Section 4 presents a discussion exploring the theoretical, policy, and practical implications of the findings and future research directions guided by the ADO framework while also addressing the study’s limitations. Finally, Section 5 concludes by synthesizing the main contributions of the research.

2. Methodology

A mixed-methods research design is utilized that integrates the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, SDG alignment mapping, bidirectional encoder representations from transformers (BERT) topic modeling, and case study analysis. (Figure 1). Patterns identified through topic modeling are validated against real-world practices described in case studies, reducing potential biases and ensuring robust findings.

2.1. PRISMA Protocol

This study incorporated the PRISMA guidelines [29] to ensure methodological rigor and transparency, recognizing their proven effectiveness in bibliometric research across multiple disciplines [30,31]. Scopus, selected for its comprehensive coverage of multidisciplinary journals, accounts for 20% more articles than the Web of Science (WoS) database does, ensuring that the literature review captures both academic and applied aspects of the CE in the TAF industry [32]. The literature search took place on 29 September 2024, encompassing publications from 2014–2024—a period chosen to align with the initial discussion of the SDGs by the United Nations in 2014.

To explore the adoption of CE principles in the TAF, we designed a targeted search strategy. The aim was to focus on key terms that align strictly with circular economy practices while excluding broader concepts that might dilute the specificity of the results. The terms were logically grouped into the following categories:

Core circular economy concepts: This category encompasses terms that are fundamental to circular economy frameworks, emphasizing the closed-loop nature of resource flows. Terms such as “circular economy”, “circular business”, and “closed loop supply chain” reflect systemic approaches focused on curtailing waste, extending product life, and fostering reuse and recycling within the textile industry. “Life cycle sustainability” was also included to capture research on minimizing environmental impacts across all stages of the product lifecycle, an integral aspect of circular economy thinking.

Design and innovation for circularity: Innovations in product design play an imperative role in enhancing circularity in the TAF sector. Terms such as “circular design” and “zero waste fashion” focus on approaches that prioritize end-of-life considerations in product development, facilitating easier recycling or reuse and minimizing waste throughout the production process. These terms highlight the role of design in achieving the goals of the CE by enhancing the efficiency of materials and energy.

Exclusion of broader terms: Several terms commonly associated with sustainability were deliberately excluded because of their broader scope, which does not always align with the principles of circularity:

• “Sustainable fashion” and “green fashion” are umbrella terms that encapsulate a spectrum of practices aimed at mitigating ecological degradation, such as using organic materials or reducing water usage. However, these terms do not necessarily emphasize the closed-loop, resource-circulation model that defines the circular economy.
• “Eco-friendly” and “environmentally friendly” also refer to environmentally responsible practices, but they lack the specific focus on resource loops and material recovery that characterize circular economy strategies.
• “Sustainable design” and “green design” focus broadly on reducing environmental footprints but do not explicitly address core circularity principles such as product life extension, reusability, or recycling.

By narrowing the scope to terms that explicitly reflect circular economy principles, we ensured that our research would specifically address innovations and practices related to the closed-loop system in textile production, design, and supply chains.

The final search query is as follows: TITLE-ABS (“circular economy” OR “circular business” OR “closed loop supply chain” OR “circular design” OR “circular fashion” OR “life cycle sustainability” OR “zero waste fashion” OR “circular consumption”) AND (cloth OR textile OR apparel OR garment OR fabric).

As a result, 801 publications were initially retrieved. During the screening phase, entries lacking essential bibliographic information, such as author details or digital object identifiers, were removed, leaving a total of 801 publications for the subsequent analysis. The inclusion criteria were peer-reviewed articles and conference proceedings written in English, excluding books, book chapters, editorials, letters, and short surveys.

2.2. SDG Mapping Framework

To determine whether each publication addressed one or more SDGs, the study utilized Elsevier’s machine-learning-based classification system integrated within the Scopus platform. This approach was guided by existing SDG mapping frameworks [33] from Aurora-Network-Global, the University of Auckland, and Elsevier. The first step of this classification applies predefined queries containing SDG-related keywords, ensuring that relevant articles are not overlooked. A subsequent phase employed a machine-learning model trained to analyze titles, abstracts, keywords, descriptor terms, and journal subject classifications to detect patterns aligned with each of the SDGs. The system assigned a numerical value (sdg_id) ranging from 1–16, corresponding to specific goals such as SDG 1 (End Poverty) or SDG 16 (Peace, Justice, and Strong Institutions). Built on a Scikit-learn (Sklearn) pipeline, the model uses a Tf–Idf vectorizer to retain the 50,000 most frequent tokens in bigram form and classify them through a multinomial logistic regression. This two-step process, validated through expert review, achieves a precision of 91.6% and a recall of 93%, reflecting its robust ability to recognize specialized SDG-related language. Applying this SDG mapping procedure reduced the dataset to 655 publications mapped to at least one SDG.

2.3. BERTopic Modeling

The output from the SDG mapping framework was subjected to machine learning-based BERTopic modeling [34] to map the intellectual landscape of the CE in the TAF field (Figure 2).

Various strategies for topic modeling exist, such as nonnegative matrix factorization (NMF), latent Dirichlet allocation (LDA), probabilistic latent semantic analysis (PLSA), and To2Vec. However, these methods frequently lack the capacity to capture deeper semantic relationships among words and often face limitations with short-text formats [35,36]. BERT, developed by Google as a deep-learning language model [37], differs from conventional bag-of-words (BoW) approaches that rely on term frequency. Instead, BERTopic uses embeddings [38] to represent documents in lower-dimensional vectors, capturing semantic nuances for more contextual insights [39,40,41]. BERTopic’s modularity enables flexible customization across diverse datasets and applications [42]. It often demonstrates superior topic coherence compared with conventional models and provides robust topic variety [43].

In our study, we utilized the BERTopic Python 0.16.3 library hosted on GitHub, starting with default configurations [44]. The process begins by transforming text into numerical embeddings, followed by dimensionality reduction through Unified Manifold Approximation and Projection (UMAP) to cluster similar points and elucidate topic groups [45]. Hierarchical density-based spatial clustering of applications with noise (HDBSCAN) subsequently identifies dense clusters while removing extraneous points. Within HDBSCAN, min_cluster_size dictates the smallest valid cluster; adjusting this parameter can enhance the silhouette score, thereby improving topic coherence [46]. Key terms are then derived from each cluster via the class-based term frequency-inverse document frequency (c-TF-IDF), which highlights words on the basis of their distribution patterns across documents [47]. For our analysis, we employed the “all-MiniLM-L6-v2” text representation model, which was designed for clustering and semantic retrieval [48,49]. The model assigns topics to documents on the basis of these representative terms, with probabilities indicating how strongly each document correlates with topics [50].

To refine topic modeling, we emphasized three main hyperparameters: the n-gram range, the number of topics, and the minimum topic size [51]. We set the n-gram range to (1, 2) to capture both single- and two-word expressions, enhancing the context without overcomplicating the analysis. The number of topics was tested from 5–20, striking a balance between precision and clarity. A minimum topic size of 20 was employed to maintain relevance while restricting each topic to 20 keywords while keeping the results focused. The commonly used words, such as “use”, “add”, and “related”, were removed to minimize noise [38]. We ran UMAP with default configurations, activated “calculate probabilities” for document—topic associations, and specified English as the language. Trials with 4–20 topics were guided by intertopic distance and coherence scores, with a 0.05 minimum distance preserving clear distinctions between topics. Coherence scores serve as a primary measure of topic quality in BERTopic; higher scores indicate more coherent, interpretable topics [30]. The cosine metric computes angular similarity across vectors, bolstering topic precision. A random state of 100 ensured reproducibility, whereas a n_neighbors value of 15 balanced local detail with overarching patterns [52]. This process resulted in the identification of six topics, each with twenty representative publications.

To reinforce the reliability and interpretability of our machine-learning outputs, we implemented a rigorous manual review of the identified topics and their representative publications. This process involved three domain experts, each possessing specialized knowledge in the relevant field, who independently examined the coherence, contextual relevance, and thematic consistency of each topic. They reviewed associated keywords and underlying publications, mirroring the approach of similar BERTopic investigations [53,54]. Discrepancies in expert assessments were resolved through structured discussions, ensuring that final decisions reflected a consensus supported by sound theoretical and empirical considerations. Finally, we chose the five representative publications from each of the six topics.

2.4. Case Study Approach

A case study approach is a widely adopted research method across disciplines, providing in-depth insights into specific contexts through detailed empirical analysis [55]. In sustainability and circular economy research, case studies serve as critical tools for understanding complex real-world implementations, allowing researchers to explore industry-specific challenges, stakeholder interactions, and policy implications in greater depth. A case study approach is widely employed in sustainable development [56] and circular economy research [57], either as a standalone method or in combination with other approaches, to provide concrete examples of CE adoption in specific contexts. In this study, case studies serve as empirical illustrations of how CE principles are implemented in the TAF industry to support sustainable development. To identify relevant case studies, we conducted a structured search of 655 publications, screening abstracts and titles for the terms “case study” or “case studies”, which resulted in 64 publications. A panel of two researchers and two industry practitioners specializing in the CE further refined the selection through consensus-based discussions. The final selection criteria included (1) a demonstrable contribution to understanding CE adoption or implementation in the TAF industry; (2) coverage of key CE thematic areas, including resource efficiency, waste management, innovative technologies, and sustainable supply chains; and (3) the use of novel business models, frameworks, or methodologies with practical relevance for advancing CE research. On the basis of these criteria, 10 case studies were selected for in-depth analysis.

3. Results

3.1. CE Publications Mapped to SDGs

Figure 3 shows the mapping of CE publications in the TAF by SDG.

Most researched SDGs: The research on CE in TAF is most frequently linked to SDG 9 (Industry, Innovation, and Infrastructure), with 449 publications, and SDG 12 (Responsible Consumption and Production), with 406 publications. This strong mapping reflects the industry’s ongoing shift toward sustainable production practices, innovative recycling technologies, and circular business models. The high representation of SDG 9 highlights the importance of technological advancements, infrastructure investment, and industrial collaboration in enabling large-scale circular economy adoption. Moreover, the prominence of SDG 12 underscores the focus on responsible material sourcing, waste reduction, and extended producer responsibility (EPR) schemes.

Moderately researched SDGs: A second tier of SDGs has moderate representation, reflecting a growing interest in the economic, environmental, and urban sustainability dimensions of circular fashion. SDG 8 (Decent Work and Economic Growth), with 129 publications, signals increasing recognition of the labor implications of circular fashion, including job creation, ethical labor practices, and fair working conditions in circular supply chains. SDG 6 (Clean Water and Sanitation), with 103 publications, and SDG 7 (Affordable and Clean Energy), with 95 publications, emphasize the environmental footprint of textile production, particularly water conservation, pollution control, and renewable energy integration in circular operations. Similarly, SDG 13 (climate action), with 95 publications, reflects the industry’s push toward carbon reduction strategies, sustainable material choices, and net-zero commitments. Another significant SDG in this category is SDG 11 (Sustainable Cities and Communities), with 73 publications highlighting the role of urban waste management, sustainable fashion consumption, and localized circular textile systems in creating more sustainable cities. The moderate focus on SDG 14 (Life Below Water), with 25 publications, suggests that some attention should be provided to the impact of microplastics and textile waste on marine ecosystems, although further research is needed to address this pressing issue.

Least-researched SDGs: Some SDGs remain underexplored in circular economy research for textiles, indicating potential gaps in scholarship. SDG 3 (good health and well-being) and SDG 4 (quality education), each with 33 publications, suggest a limited but emerging focus on the health impacts of textile chemicals and the role of education in circular fashion awareness. SDG 10 (reduced inequalities), with 17 publications, and SDG 5 (gender equality), with only 6 publications, highlight the need for further investigation into how circular economy strategies can support social equity, gender-inclusive policies, and fair labor practices in textile production and waste management. SDG 15 (Life on Land), with 23 publications, reflects some engagement with land degradation, deforestation, and biodiversity impacts of textile supply chains. However, more research is needed on sustainable raw material sourcing, regenerative agriculture for textile fibers, and the ecological effects of waste disposal practices. Similarly, SDG 16 (Peace, Justice, and Strong Institutions), with 14 publications, remains one of the least explored despite its relevance to corporate transparency, ethical governance, and anticounterfeiting measures in a sustainable fashion. At the lower end of the research attention, SDG 2 (Zero Hunger), with 13 publications, and SDG 1 (No Poverty), with 7 publications, show that the potential socioeconomic benefits of circular economy adoption—such as job creation, financial inclusion, and economic resilience in marginalized communities—have not been extensively analyzed. Exploring how circular business models can contribute to poverty reduction and food security through economic empowerment and resource efficiency presents a valuable avenue for future research.

3.2. Theoretical Underpinnings

Table 2 below provides a comparison of theoretical lenses used in Circular Economy-Textile, Apparel, and Fashion (CE-TAF) research. It emphasizes the basic concepts of each theory, noteworthy applications, distinctive contributions to CE transitions, and limitations with respect to TAF of each theory.

3.2.1. Institutional Theory

Institutional pressures (e.g., increasing stakeholder demands for transparency) compel apparel firms to shift from fast fashion to more sustainable “slow” models [58]. The study contributes to institutional theory by demonstrating how stakeholder-driven demands and supplier certification requirements alter firms’ value propositions and supply chain design [59]. Homogeneity or heterogeneity explores the outdoor sporting goods industry, showing how institutional isomorphism leads to moderate-to-high uniformity in CE practices [60]. This research clarifies that even in an industry seen as progressive, institutional factors can produce similar CE activities across multiple brands, thus reinforcing the role of isomorphic pressures in shaping corporate sustainability. Drivers of and barriers to CE transition combine institutional theory with the natural resource-based view [61], revealing how market, regulatory, and societal forces influence CE adoption in the Pakistani textile industry. By illustrating the interplay of institutional and resource-based drivers, this study shows how both formal policies and firm-level capabilities matter in developing economies transitioning toward CE. Taken together, these papers extend institutional theory by highlighting how formal rules, cultural expectations, and stakeholder scrutiny interact to encourage (or sometimes hinder) sustainable practices in textile and apparel supply chains.

3.2.2. Natural-Resource-Based View

Several papers use the natural-resource-based view (NRBV) and, in one case, dynamic capabilities to explain how internal resources and capabilities enable successful CE implementation. The dynamic development and execution of closed-loop supply chains [59,62] integrate the NRBV and dynamic capabilities to show how firms with strong technological, knowledge-based, and relational resources achieve successful closed-loop supply chains. By emphasizing the dynamic reconfiguration of resources, this paper moves the NRBV beyond a static view and places collaboration at the core of strategic resource renewal. Enabling a circular economy through green manufacturing [63] applies the NRBV to Chinese apparel manufacturers, connecting environmental orientation and green manufacturing to superior performance and CE capacity. The study shows how firms build on environmental commitments to develop both business and sustainability benefits, underscoring the NRBV’s focus on resource synergies for competitive advantage.

Attaining sustainable excellence [64] further validates the NRBV in the Bangladeshi green garment sector, linking sustainable supply chain management and a circular economy to enhanced firm performance. By presenting sustainable practices as strategic resources, the study indicates that the NRBV can explain why environmentally oriented supply chains confer a competitive advantage. Circular economy practices and sustainable performance [65] employ NRBV (and social cognitive theory) to demonstrate how firms’ internal resources—particularly corporate environmental ethics—foster CE practices that improve economic, environmental, and social performance in apparel manufacturing. This dual-theory foundation indicates a need to integrate resource-based and behavioral factors to understand successful sustainability transitions. Collectively, these studies extend the NRBV by demonstrating how environmental orientation, cross-firm collaboration, and strategic resource configurations enable circular solutions in various textile contexts. Dynamic capabilities reinforce that constant adaptability is essential for leveraging resources under changing market conditions.

3.2.3. Stratification Theory

A stratified fuzzy decision-making approach for sustainable circular supplier selection [66] illustrates how stratification theory supports a multiple-criteria decision-making framework under uncertainty. Here, the theory is operationalized to separate decision layers (criteria weighting, supplier prioritization) for selecting suppliers in a circular context. By embedding future event impacts and expert judgments into stratified layers, this study broadens the applicability of stratification theory to sustainability-based procurement.

Table 2. Comparative analysis of theoretical applications in CE-TAF studies.

Authors	Theory	Core Focus	Key Studies and Applications	Unique Contributions in CE-TAF	Limitations/Scope
[58,59,60,61]	Institutional Theory	External pressures (regulations, norms, stakeholder expectations)	- Transition from fast to slow fashion due to stakeholder transparency demands - Homogeneity in CE across outdoor brands via isomorphism - Pakistani textile CE influenced by market and societal norms	- Explains CE adoption driven by coercive, normative, and mimetic pressures - Highlights how certification requirements and scrutiny lead to similar CE patterns across firms	- Does not account for internal capabilities or strategic reconfiguration - More applicable to antecedents than decisions or outcomes
[59,62,63,64,65]	Natural Resource-Based View (NRBV) and Dynamic Capabilities	Strategic use and reconfiguration of internal resources	- Closed-loop supply chain enabled by technology, knowledge, and relationships - Green manufacturing in Chinese firms - Competitive advantage via sustainable supply chains in Bangladesh - Environmental ethics driving CE performance	- Connects resource synergy and environmental orientation to CE success - Dynamic Capabilities show how firms adapt and innovate under changing sustainability demands	- Often firm-centric and assumes access to strategic resources - Less suited for explaining cross-firm or ecosystem-level transitions
[67]	Systems Theory	Interdependence and readiness across stakeholders and infrastructure	- Multilayered CE readiness model for Turkish SMEs integrating tech, org, stakeholder systems	- Supports holistic assessment across digital, organizational, and regulatory dimensions - Useful for mapping system-level readiness and bottlenecks	- Limited use in predictive modeling - Needs integration with firm-level theories for operational strategies
[66]	Stratification Theory	Layered decision-making in uncertain, multicriteria contexts	- Circular supplier selection using stratified fuzzy logic	- Offers structured decision logic for supplier evaluation under uncertainty - Applies well in procurement and multiple criteria decision analysis environments	- Niche application; not explanatory for firm-level CE behavior or macro transitions
[68]	Theory of Planned Behavior	Behavioral intent shaped by attitude, norms, and perceived control	- CE adoption influenced by firm maturity, attitudes, social pressures in Bangladesh	- Useful for analyzing managerial perceptions and intent in CE decisions - Highlights role of psychological and cultural dimensions	- Used in isolated cases - Not deeply integrated with other strategic or institutional frameworks in CE-TAF

Table 2. Comparative analysis of theoretical applications in CE-TAF studies.

Authors	Theory	Core Focus	Key Studies and Applications	Unique Contributions in CE-TAF	Limitations/Scope
[58,59,60,61]	Institutional Theory	External pressures (regulations, norms, stakeholder expectations)	- Transition from fast to slow fashion due to stakeholder transparency demands - Homogeneity in CE across outdoor brands via isomorphism - Pakistani textile CE influenced by market and societal norms	- Explains CE adoption driven by coercive, normative, and mimetic pressures - Highlights how certification requirements and scrutiny lead to similar CE patterns across firms	- Does not account for internal capabilities or strategic reconfiguration - More applicable to antecedents than decisions or outcomes
[59,62,63,64,65]	Natural Resource-Based View (NRBV) and Dynamic Capabilities	Strategic use and reconfiguration of internal resources	- Closed-loop supply chain enabled by technology, knowledge, and relationships - Green manufacturing in Chinese firms - Competitive advantage via sustainable supply chains in Bangladesh - Environmental ethics driving CE performance	- Connects resource synergy and environmental orientation to CE success - Dynamic Capabilities show how firms adapt and innovate under changing sustainability demands	- Often firm-centric and assumes access to strategic resources - Less suited for explaining cross-firm or ecosystem-level transitions
[67]	Systems Theory	Interdependence and readiness across stakeholders and infrastructure	- Multilayered CE readiness model for Turkish SMEs integrating tech, org, stakeholder systems	- Supports holistic assessment across digital, organizational, and regulatory dimensions - Useful for mapping system-level readiness and bottlenecks	- Limited use in predictive modeling - Needs integration with firm-level theories for operational strategies
[66]	Stratification Theory	Layered decision-making in uncertain, multicriteria contexts	- Circular supplier selection using stratified fuzzy logic	- Offers structured decision logic for supplier evaluation under uncertainty - Applies well in procurement and multiple criteria decision analysis environments	- Niche application; not explanatory for firm-level CE behavior or macro transitions
[68]	Theory of Planned Behavior	Behavioral intent shaped by attitude, norms, and perceived control	- CE adoption influenced by firm maturity, attitudes, social pressures in Bangladesh	- Useful for analyzing managerial perceptions and intent in CE decisions - Highlights role of psychological and cultural dimensions	- Used in isolated cases - Not deeply integrated with other strategic or institutional frameworks in CE-TAF

3.2.4. Systems Theory

Assessing smart circular supply chain readiness [67] draws on systems theory to evaluate how Industry 4.0 and CE concepts integrate into “smart” supply chains. This work demonstrates how a multilayered systems perspective unifies readiness dimensions (technological, organizational, and stakeholder) for SMEs in the Turkish textile sector, confirming the holistic nature of circular transitions.

3.2.5. Theory of Planned Behavior

The application of the revised theory of planned behavior (TPB) [68] examines attitudes, social pressure, environmental commitment, green economic incentives, and firm maturity as factors shaping CE readiness in Bangladesh’s ready-made garment sector. By adopting the TPB, this study contributes a unified framework for understanding how managerial perceptions and societal norms drive the adoption of CE practices in a developing economic context.

3.3. Emerging Topics

Next, we analyze the content of the topics generated through BERTopic modeling, examining their mapping with specific SDGs to identify thematic patterns and contributions to sustainability (Figure 4).

3.3.1. Sustainable Recycling and CE Strategies for Textile Waste Management

Studies on this topic explore sustainable textile waste recycling within the CE, emphasizing waste management innovations in the TAF industry. Keywords such as “circular economy”, “textile waste”, “recycling”, “biobased materials”, and “sustainable alternatives” are central to these studies.

Rhodes address the pressing issue of plastic pollution, discussing how recycling and waste management of textile products can reduce environmental harm, aligning with SDG 12.5 on waste reduction and SDG 14.1 on mitigating marine pollution [69]. Furthermore, the study also connects to SDG 11.6, which emphasizes minimizing urban waste impacts. Meyer et al. proposed fungal biotechnology as a sustainable alternative to petroleum-based textiles [70]. This bio-based approach aligns with SDG 9.4, which promotes resource efficiency and industrial upgrades. In addition, it aligns with SDG 13.2, which highlights the potential of fungal materials to reduce greenhouse emissions and support climate initiatives. This study also underscores SDG 4, with education on sustainable biotech practices seen as vital for future generations. In contrast, Cerimi et al. further investigated bio-based textiles, particularly through patents, to foster innovation in circular textile systems [71]. This aligns with SDG 9.5, which encourages scientific research, and SDG 12.4, which focuses on sound chemical and waste management throughout product life cycles. By minimizing reliance on fossil fuels, bio-based materials foster environmentally responsible industrial practices. Furthermore, Patti et al. explored recycled fibers in composite materials, showing the potential for textile waste to become a valuable resource, supporting SDG 12.5 by reducing waste [72]. This study proposes a closed-loop industry model in which materials are continuously repurposed, reducing the overall environmental impact. Similarly, Agamuthu et al. discussed textile waste in the context of marine pollution, focusing on the effects of microplastics on ecosystems, aligning with SDG 14.1, tackling marine pollution, and SDG 12.5, promoting recycling [73].

3.3.2. Circular Business Models for Sustainability in the TAF

This topic focuses on “circular business models”, as well as “institutional challenges” and “sustainability” efforts in the textile industry. Keywords such as “circular economy”, “business models”, “value creation”, “upcycling”, and “institutional incentives” are central to the studies.

Fischer and Pascucci focused on the Dutch textile sector and discussed two primary CE frameworks: Status Quo (SQ) and Product-as-a-Service (PaaS). SQ enhances current upcycling technology [74], whereas PaaS proposes new business models extending product life, supporting SDG 12.6 by encouraging sustainable practices and reporting in business operations. In contrast, Franco delved into the operational challenges of the CE, particularly in product design and reverse logistics, stressing the role of collaboration between suppliers and buyers [75]. This study emphasizes the infrastructure upgrades needed to support sustainable production, aligning with SDG 9.4 and SDG 12 for waste reduction. D’Amato et al. focused on a unique approach within the CE model in Finland’s SMEs in a circular bioeconomy context [76], highlighting the use of bio-based materials, thus supporting scientific advancements that align with SDG 9.5 and sustainable resource use (SDG 15.1), as well as bio-based innovations that align with SDG 9.b. Similarly, Rossi et al. developed CE indicators to measure sustainability within the TAF industry, promoting multidimensional assessments that capture social, economic, and environmental impacts [77]. This aligns with SDG 9.b for sustainable industry innovation and with SDG 8.4 for encouraging resource efficiency. Jia et al. [24] emphasized the environmental benefits of CBMs by addressing waste reduction aligned with SDG 12.5 and resource efficiency in supply chains with SDG 8.4, highlighting industry innovations to foster sustainable practices (SDG 9.b). Collectively, these studies demonstrate how diverse CE approaches in the TAF industry can support sustainable development goals, with each study offering unique frameworks for circular practices across different contexts.

3.3.3. CE Principles in Textile Waste Management and Sustainable Production

Highlighting “product/service systems” for “decoupling economic growth from resource consumption”, studies on this topic stress that circular strategies do not guarantee “absolute resource decoupling”. Textile waste from “fast fashion” and “throwaway culture” demands “reuse, recycling, and policy interventions”. The socioeconomic benefits of “textile recycling” include “employment and revenue”. Global waste policies, such as “China’s foreign waste ban”, shift burdens, requiring a “cohesive circular framework”. “Life cycle assessment” confirms that reuse reduces the environmental impact, reinforcing “systemic circular strategies”.

First, Castellani et al. [78] emphasized the importance of reuse practices through LCA, demonstrating that extending product lifespans can significantly reduce waste and resource demand. This aligns with SDG 12.2, which promotes sustainable resource use, and SDG 9.4, which encourages resource-efficient industrial practices by prioritizing reuse over new production. Building on this foundation, Kjaer et al. [79] propose product–service systems (PSSs) as a model to decouple economic growth from resource consumption, suggesting a shift toward service-based textile economies. By extending product lifecycles and minimizing waste, this study directly supports SDG 12.5 and aligns with SDG 9.4 by encouraging sustainable industry infrastructure and innovation. Leal Filho et al. [20] focused on the socioeconomic benefits of CE practices in textile recycling, highlighting how recycling fosters industrial innovation and opens economic opportunities for small enterprises (SDG 9.3). The study also aligns with SDG 12.5 by promoting these practices as vital strategies for reducing environmental impact and waste generation in the textile sector. Similarly, Qu et al. [80] explored the global consequences of China’s waste import ban, which encouraged developed countries to reconfigure waste management practices. This study connects to SDG 10.1 by addressing inequalities in waste distribution and SDG 11.6 by encouraging improvements in local waste processing for sustainable urban environments. By promoting global collaboration in sustainable waste management, this study aligns with SDG 12.4, supporting environmentally responsible waste practices. In contrast, Shirvanimoghaddam et al. [81] highlighted an innovative business model for addressing the environmental impacts of fast fashion pollution, particularly micro pollution, which directly affects marine ecosystems, with a focus on SDG 14.1. The study also highlights health risks associated with textile pollution, aligning with SDG 3.9 on health. It emphasized recycling and innovative waste solutions supporting SDG 9.4 by promoting sustainable upgrades in the TAF industry infrastructure.

3.3.4. Consumer Engagement and Sustainable Practices in a Circular Fashion

Consumer viewpoints and expectations for circular clothing stand out in this topic, spotning “recycling, reuse, and sustainable solutions”. The role of “corporate social responsibility”, particularly post-COVID-19, has influenced consumer demand for sustainable products. Digital platforms such as “Instagram microcelebrities” and “online renting” drive behavioral intent toward a circular fashion. Additionally, the “value and risk perceptions” of secondhand, upcycled, and recycled clothing shape consumer attitudes, impacting retailing and promotional strategies. Sustainable design and “eco-friendly practices” across the “clothing supply chain” are essential for achieving CE goals.

Moorhouse and Moorhouse [82] researched sustainable design and eco-friendly textile practices to reduce the ecological footprint in the fashion industry. Their emphasis on waste minimization and achieving a 95% recycling rate supports SDG 12.5 for substantial waste reduction. The study also aligns with SDG 9.4 and SDG 8.4 by advocating sustainable industrial practices and reducing the link between economic growth and environmental harm. However, Vehmas et al. [83] delved into consumer interest in textile recycling, emphasizing the need for clear communication on how clothing choices affect the environment. By promoting better-informed consumer behavior, this study supports SDG 9.4 in fostering sustainable infrastructure and SDG 12, with a focus on responsible consumption. Similarly, Shrivastava et al. [84] took a step further and highlighted the role of social media, particularly Instagram influencers, in promoting circular fashion, which showed that social platforms encourage secondhand clothing and rentals, contributing directly to SDG 12.5 in terms of waste reduction. The study underscores SDG 9.4 by demonstrating how digital channels can shape consumer attitudes toward sustainability through social influence and accessibility. Furthermore, Vătămănescu et al. [85] explored the shift in CSR practices in fashion due to COVID-19, observing a growing consumer demand for sustainable products, aligning with SDG 12.6 by reassuring companies to integrate sustainability into their CSR reporting. The study also supports SDG 9.b by promoting innovative production methods, along with SDG 2.4 in promoting organic materials. Kim et al. examine consumer perceptions of risk and value circularly, showing that emotional value drives the adoption of upcycled products, whereas perceived risk has minimal impact [86]. This aligns with SDG 8.4 by emphasizing resource efficiency and SDG 13.1 in promoting resilience to climate challenges, highlighting eco-friendly materials as essential in the sustainable fashion landscape.

3.3.5. CE Innovations in Textile and Leather Waste Valorization

Research on this topic underscores “zero waste” strategies by repurposing “oil press-cakes” to extract “bioactive compounds, enzymes, and biofuels”. Textile waste solutions include “green technology for fiber recovery”, “cocombustion of plastics and dyeing sludge”, and “oxy-fuel combustion for CO₂ capture”. Sustainable leather production is explored via “bagasse-derived tanning agents”, which promote “biodegradability” over traditional methods. These studies highlight “waste-to-energy conversion”, “material recovery”, and “circular processes” for the sustainable textile and leather industries.

Ariram and Madhan focused on biodegradable leather waste via a novel bagasse-based tanning process [87], promoting cradle-to-cradle leather production and supporting SDG 9.4 by emphasizing sustainable industrialization and SDG 8.4, which encouraged efficient resource use. Their model exemplifies a CE practice that turns waste into valuable resources within the leather sector, aligning with cradle-to-cradle principles in the broader TAF industry. Furthermore, Ancuța and Sonia explored the potential of converting oil press cakes into bioactive compounds for textiles [88], contributing to SDG 7.2 by supporting renewable energy sources and SDG 12.5 by minimizing waste. Their zero-waste approach offers a model for valorizing industrial byproducts, showcasing a CBM where waste from oil production is repurposed for sustainable textile applications. Another innovative strategy by Yousef et al. highlighted the use of green technology for recycling cotton and polyester fibers from textile waste, which resonated with SDG 12.4’s goal of sound chemical waste management [89] and SDG 13.1’s goal of climate mitigation through reduced carbon emissions. This model exemplifies the CE by reintegrating waste fibers into production, promoting a closed-loop system that reduces landfill waste and greenhouse gas emissions. Similarly, Ding et al. investigated the cocombustion of plastics and textile dyeing sludge for energy recovery [90], linking SDG 13.2 for integrating climate strategies and SDG 7.3 for global energy efficiency. This process provides a circular model that not only manages waste but also generates energy, optimizing the TAF industry’s ecological footprint. Furthermore, Wu et al. extended this model by combining phytoremediation biomass with textile sludge, increasing CO₂ capture and energy conversion [91]. This process supports SDG 12.2 for resource efficiency and SDG 15.1 for reducing environmental degradation. Their study presents a CE approach that aligns waste recovery with natural resource conservation. Thus, these studies illustrate various circular strategies across the TAF industry, contributing to sustainability by transforming waste into resources, reducing emissions, and optimizing resource use, thus advancing both environmental and economic goals in alignment with key SDGs.

3.3.6. Technology-Driven Circular Models in Textile and Fashion Supply Chains

The studies explore “textile-to-textile recycling” and “closed-loop supply chains”, highlighting the “technology, innovation, and systemic changes” needed for circular fashion. “Blockchain” and “IoT” enhance “traceability and transparency”, supporting “sustainable rent-based models” and “e-commerce for secondhand apparel”. Challenges include “high R&D costs”, “logistics complexity”, and “quality-based return segmentation”. The adoption of “digital solutions”, such as “blockchain-enabled platforms”, mitigates “counterfeiting risks” and improves consumer trust, advancing “circular economy principles” in fashion.

For instance, Hu et al. examined a rent-based, closed-loop supply chain for fashion products to extend product life and reduce waste [92]. By promoting rental systems and responsive pricing, this model encourages sustainable consumption, aligning with SDG 12.1 on responsible production and SDG 9.4 on sustainable industrial practices. This closed-loop model provides an early example of fast circularity. Similarly, Masoudipour et al. extended these circular supply chain practices, modeling a zero-waste strategy through quality-based segmentation for returned textiles [93]. By emphasizing remanufacturing, repair, and recycling, this approach supports SDG 9.4, showcasing a CE model that maximizes both environmental and economic gains through resource-efficient supply chains. However, Sandvik and Stubbs focused on the drivers of textile-to-textile recycling in Scandinavia through blockchain, emphasizing the importance of technology and collaboration with SDG 9.4 by advocating cleaner technologies and SDG 12.5 for waste reduction through recycling [94]. This study also addresses industry challenges in building circularity. Moreover, Alves et al. explored the role of blockchain and the IoT in enhancing supply chain transparency and traceability [95]. By recording every value-chain activity, this model aligns with SDG 9.5 in advancing technological capabilities and with SDG 12.4 in responsible waste management. Blockchain integration underscores a technological pathway to the CE, improving recycling and material traceability. Similarly, Jain et al. investigated blockchain’s application in secondhand apparel retail to address consumer trust in authenticity [96]. In support of SDG 6.3 on pollution reduction and sustainable resource management, this model leverages technology to facilitate CE practices in second-hand markets.

3.4. Case Studies

Circular economy (CE) initiatives in the TAF industry have gained traction globally, yet their integration into sustainable development remains fragmented. The analysis of 10 case studies reveals both commonalities and divergences in approaches to CE implementation, emphasizing key aspects such as stakeholder engagement, waste management, transparency, supply chain challenges, business model transformation, and their links with the SDGs (Table 3).

A dominant theme across several case studies is the transition from fast fashion to sustainable business models. Abbate et al. underscore the environmental impact of fast fashion in Italy and advocate for slow fashion models and stakeholder engagement strategies, aligning with SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action) [5]. In contrast, Mahanty and Domenech highlight the lack of stakeholder alignment in CE transitions, emphasizing the importance of social learning and participatory circular business models (CBMs) to foster collaboration across the value chain (SDG 11, 12, 13, 17) [97]. Their study, which was based in the UK, suggested that stakeholder engagement theory plays a pivotal role in addressing systemic challenges within circular transitions. The challenge of waste management and resource inefficiency is another crucial focus area. Chowdhury et al. analyzed Industry 4.0 challenges in Bangladesh and proposed a smart waste management system (SWMS) that optimizes waste control through hybrid decision-making frameworks and the gray analytical network process (ANP) (SDG 12, 9) [98]. Similarly, Coppola et al. explored pollution prevention and product stewardship in Italy, advocating for closed-loop supply chains and “born-circular” business models that extend product life cycles (SDGs 12, 13) [99]. While both studies address waste reduction, Coppola et al. focus on firm-level capabilities using a natural-resource-based view [99], whereas Chowdhury et al. emphasize technological optimization for waste control [98].

Regulatory and transparency challenges emerge as critical barriers to circular fashion. Hrouga and Michel identify the lack of regulatory frameworks in France as a key inhibitor of CE adoption, leading to fragmented supply chain practices and limited performance measurement metrics (SDG 9, 12, 13) [100]. The circular supply chain dashboard for SMEs provides a practical solution for firms struggling with compliance. In parallel, Shou and Domenech examine traceability and transparency challenges in CE supply chains in Germany and the UK, proposing a blockchain and life cycle assessment (LCA) integration model to enhance data collection and environmental impact tracking (SDG 12, 13) [101]. Both studies highlight the critical role of digital solutions in overcoming information asymmetry, although Shou and Domenech take a more technological approach with blockchain integration [102], whereas Hrouga and Michel advocate for regulatory and performance-based solutions [100]. Adoption readiness for Industry 4.0 and CE transitions significantly contributes to shaping business models. Kayikci et al. examined SME readiness for Industry 4.0-driven circular economy adoption in Turkey, using systems theory and maturity models to propose a Smart Circular Supply Chain (SCSC) (SDG 9, 12) [67]. This contrasts with Martina and Oskam, who focus on scalability and collaboration in recycling business models (RBMs) in the Netherlands, leveraging design science and collaborative frameworks (SDG 12) [102]. While both studies aim to enable CE transitions, Kayikci et al. [67] emphasize technological preparedness, whereas Martina and Oskam advocate for structural collaboration among firms [102].

A more critical perspective on CE assumptions is provided by Siderius and Poldner, who discuss the circular economy rebound (CER) effect in the Netherlands, where the environmental benefits of CE practices may be overestimated due to unintended resource consumption patterns (SDGs 12, 13) [103]. Their work, grounded in rebound effect theory and lifecycle thinking, suggests that mitigating rebound effects is crucial to achieving true sustainability. Finally, Rovanto and Bask explore the differences in CE adoption between native and adopter companies in Finland and Japan, proposing circular economy native and adopter models (SDGs 8, 9) [104]. Their work, which is based on systems thinking and circular business model theory, reveals that firms with embedded circular principles perform better in long-term sustainability than late adopters do, reinforcing the need for early integration of CE strategies.

Table 3. Review of relevant case studies related to CE in TAF.

Author(s)	Case Study Focus	SDGs Mapped	Countries Involved	Theories Used	Tailored Business Models
Abbate et al. [5]	Environmental impact of fast fashion, transition to sustainable business models	SDG 12, 13	Italy	Institutional theory, sustainable business model frameworks	Slow fashion model, stakeholder engagement models
Mahanty and Domenech [97]	Lack of stakeholder alignment, need for social learning in CE transitions across the value chain	SDG 11, 12, 13, 17	UK	Stakeholder engagement theory, social learning	Participatory CBM to foster stakeholder collaboration
Chowdhury et al. [98]	Waste management, resource inefficiency, Industry 4.0 challenges	SDG 12, 9	Bangladesh	Hybrid decision-making frameworks, gray Analytical Network Process	Smart waste management system (SWMS) for optimized waste control
Coppola et al. [99]	Pollution prevention, product stewardship, and sustainable development in circular transition	SDG 12, 13	Italy	Natural-resource-based view, dynamic capabilities framework	CBMs focusing on closed-loop supply chains, born-circular and growing-circular firms
Hrouga and Michel [100]	Challenges in CE implementation, lack of regulation, sustainable supply chain practices	SDG 9, 12, 13	France	Systems theory, sustainable supply chain management, performance metrics	Circular supply chain dashboard for SMEs
Shou & Domenech [101]	Lack of transparency, traceability in the supply chain, data collection challenges in environmental impacts	SDG 12, 13	Germany, United Kingdom	Blockchain and LCA integration for CE	Circular economy model using blockchain for transparency
Kayikci et al. [67]	Readiness and maturity for Industry 4.0 and circular economy adoption in SMEs	SDG 9, 12	Turkey	Systems theory, readiness, and maturity models	Smart Circular Supply Chain (SCSC)
Siderius and Poldner [103]	Circular Economy Rebound (CER) effect, environmental benefits overestimation in CE practices	SDG 12, 13	Netherlands	Rebound effect theory, lifecycle thinking	CBM focuses on mitigating rebound
Martina and Oskam [102]	Recycling challenges need for scalable and collaborative business model	SDG 12	Netherlands	Design science, collaborative business models	Recycling business models (RBMs), collaborative models
Rovanto and Bask [104]	Challenges in CE adoption for native vs. adopter companies	SDG 8, 9	Finland, Japan	Systems thinking, circular business model theory	Circular economy native and adopter models

Table 3. Review of relevant case studies related to CE in TAF.

Author(s)	Case Study Focus	SDGs Mapped	Countries Involved	Theories Used	Tailored Business Models
Abbate et al. [5]	Environmental impact of fast fashion, transition to sustainable business models	SDG 12, 13	Italy	Institutional theory, sustainable business model frameworks	Slow fashion model, stakeholder engagement models
Mahanty and Domenech [97]	Lack of stakeholder alignment, need for social learning in CE transitions across the value chain	SDG 11, 12, 13, 17	UK	Stakeholder engagement theory, social learning	Participatory CBM to foster stakeholder collaboration
Chowdhury et al. [98]	Waste management, resource inefficiency, Industry 4.0 challenges	SDG 12, 9	Bangladesh	Hybrid decision-making frameworks, gray Analytical Network Process	Smart waste management system (SWMS) for optimized waste control
Coppola et al. [99]	Pollution prevention, product stewardship, and sustainable development in circular transition	SDG 12, 13	Italy	Natural-resource-based view, dynamic capabilities framework	CBMs focusing on closed-loop supply chains, born-circular and growing-circular firms
Hrouga and Michel [100]	Challenges in CE implementation, lack of regulation, sustainable supply chain practices	SDG 9, 12, 13	France	Systems theory, sustainable supply chain management, performance metrics	Circular supply chain dashboard for SMEs
Shou & Domenech [101]	Lack of transparency, traceability in the supply chain, data collection challenges in environmental impacts	SDG 12, 13	Germany, United Kingdom	Blockchain and LCA integration for CE	Circular economy model using blockchain for transparency
Kayikci et al. [67]	Readiness and maturity for Industry 4.0 and circular economy adoption in SMEs	SDG 9, 12	Turkey	Systems theory, readiness, and maturity models	Smart Circular Supply Chain (SCSC)
Siderius and Poldner [103]	Circular Economy Rebound (CER) effect, environmental benefits overestimation in CE practices	SDG 12, 13	Netherlands	Rebound effect theory, lifecycle thinking	CBM focuses on mitigating rebound
Martina and Oskam [102]	Recycling challenges need for scalable and collaborative business model	SDG 12	Netherlands	Design science, collaborative business models	Recycling business models (RBMs), collaborative models
Rovanto and Bask [104]	Challenges in CE adoption for native vs. adopter companies	SDG 8, 9	Finland, Japan	Systems thinking, circular business model theory	Circular economy native and adopter models

4. Discussion

While there is growing attention to sustainability, waste management, and digital innovations, the integration of CE principles remains fragmented. Key areas of convergence across these studies include sustainable recycling strategies, circular business models, resource efficiency, consumer engagement, waste valorization, and digital innovations. The synthesis of these topics with case studies reveals challenges in implementation, the role of policy frameworks, technological barriers, and gaps in behavioral and social sustainability aspects.

Both topic modeling results and case studies emphasize the role of textile waste recycling as a key component of the CE [7]. Studies such as those of Rhodes [69] and Meyer et al. [70] have proposed sustainable alternatives to petroleum-based textiles, suggesting the use of biobased materials and innovative waste management strategies. These findings align with case studies such as Chowdhury et al. [98], which examine the challenges of Industry 4.0 adoption in textile waste management in Bangladesh [105] and propose a smart waste management system (SWMS) to optimize waste control. More recently, Islam et al. [64] investigated the impact of sustainable supply chains and the CE on the green garment industry in Bangladesh. Similarly, Coppola et al. [99] advocated for closed-loop supply chains and “born-circular” business models as essential for reducing textile pollution. However, while Chowdhury et al. focused on technological efficiency [98], Coppola et al. emphasized firm-level capabilities and product stewardship [99]. Both highlight SDG 12 (responsible consumption and production) and SDG 9 (industry, innovation, and infrastructure) as key drivers of sustainable waste strategies.

The urgency for circular business models (CBMs) is evident across both topic modeling results and case studies. Studies such as Fischer and Pascucci [74] and Franco [75] examine different business model frameworks, including product-as-a-service (PaaS) and status quo (SQ) upcycling strategies, demonstrating how business model transformation can extend product life cycles. These insights align with Abbate et al. [5], who explore how slow fashion and stakeholder engagement models are replacing fast fashion approaches in Italy. Similarly, Mahanty and Domenech [97] argue for participatory CBMs, emphasizing the need for stakeholder collaboration to align supply chains with CE principles [106]. However, while Fischer and Pascucci [74] focused on business model mechanics, Mahanty and Domenech [97] highlighted the need for institutional and behavioral shifts. The case study by Rovanto and Bask [104] reinforces this distinction by comparing native circular economy firms with late adopters, demonstrating that firms with embedded CE principles outperform those adopting CE strategies reactively. The topic modeling results align with this by highlighting institutional challenges such as regulatory gaps, financial constraints, and fragmented supply chains [100]. These discussions point to SDG 9 and SDG 8 (Decent Work and Economic Growth) as key enablers of successful CBM adoption.

The results emphasize resource efficiency as a cornerstone of CE implementation. Castellani et al. [78] and Kjaer et al. [79] propose Product–Service Systems (PSSs) as an apparatus for dissociating economic growth from resource consumption, aligning with SDG 12 (Sustainable Production) and SDG 9 (Industry Innovation). Case studies such as Shou and Domenech [101] reinforce this perspective by exploring blockchain-enabled transparency solutions to track resource flows and improve traceability in supply chains. However, while Shou and Domenech [101] focused on technological solutions, case studies such as Hrouga and Michel [100] emphasized regulatory frameworks and policy interventions. Additionally, the topic modeling results highlight global waste policies and their implications. Qu et al. examined the impact of China’s waste import ban, which forced developed nations to reconfigure waste management strategies [80]. This aligns with the case study by Siderius and Poldner on circular economy rebound (CER) effects, demonstrating how overestimating the benefits of CE can lead to increased resource use [103]. Both discussions reinforce SDG 12 and SDG 10 (reduced inequalities), urging a more nuanced approach to resource efficiency.

The role of consumer attitudes, corporate social responsibility (CSR), and digital engagement emerges across both studies. The study by Hassan et al. [107] also confirms the definite role of digital technologies in the circular transition of TAFs. Studies such as Vehmas et al. [82] and Shrivastava et al. [83] highlight how social media platforms and digital marketing strategies influence consumer behavior in a circular fashion. These findings align with those of Mahanty and Domenech [96], who underscore the role of social learning in fostering circular business models. Similarly, case studies such as Kim et al. [85] explore the value and risk perceptions of secondhand and upcycled clothing, reinforcing findings from Encino-Munoz and Yilan [108] and Moorhouse and Moorhouse [82] that emphasize the role of sustainable design in mitigating textile waste. However, while Moorhouse and Moorhouse [82] focused on the supply side of sustainable fashion, Kim et al. [85] examined consumer perceptions and behavioral intent [109]. These insights reinforce the importance of multistakeholder engagement across the value chain to align business strategies with SDG 12 and SDG 9 (sustainable industry).

The transformation of textile and leather waste into new materials has emerged as another key theme. The results highlight innovative approaches such as fungal biotechnology [70], green technology for fiber recovery [89], and bio-based tanning alternatives [86]. Case studies such as those of Coppola et al. [98] reinforce these findings by advocating for closed-loop supply chains that extend product life cycles. However, while Yousef et al. [89] focused on the chemical recovery of textile fibers, Ding et al. [89] examined waste-to-energy solutions and suggested that material recovery and energy recovery should be considered together. The case study by Wu et al. [91] extends this by integrating phytoremediation biomass with textile sludge cocombustion, demonstrating how waste-to-energy conversion can align with CO₂ capture strategies. Material recovery in the CE extends resource utility by converting waste into secondary raw materials and looping them back into production to minimize the environmental footprint of the TAF [14]. Benchmarking emerging textile waste valorization technologies through life cycle assessment is essential to ensure their environmental, social, and economic fit within the local circular economy before scale-up [110]. These findings connect to SDG 12, SDG 7 (Affordable and Clean Energy), and SDG 15 (Life on Land).

Technologies driven by blockchain, the IoT, and artificial intelligence are emerging as key enablers of circular fashion supply chains, but the lack of adaptation to these emerging technologies is a concern [11]. The results highlight studies such as Sandvik and Stubbs [94] and Alves et al. [95], who propose blockchain-based traceability models to reduce counterfeiting risk and improve transparency in textile supply chains. These findings align with case studies such as Shou and Domenech [101], who proposed blockchain–LCA integration for CE tracking. Similarly, case studies such as Jain et al. [96] emphasize blockchain’s role in second-hand apparel markets, reinforcing SDG 9 (Industry Innovation) and SDG 12 (Sustainable Production). While Shou and Domenech [101] focus on blockchain for supply chains, Jain et al. [96] explore its application in consumer engagement, highlighting the potential for technology to bridge transparency gaps across CE initiatives.

The integration of topic modeling insights with case studies highlights gaps in policy, behavioral engagement, and technological scalability within CE transitions in the TAF industry. While material efficiency and digital innovations are driving progress [107], challenges related to stakeholder alignment, regulatory barriers, and rebound effects persist [10] in the European Union’s policies for sustainable fashion in the TAF. Future research and industry action should prioritize policy reinforcement [111], social learning, and systemic change across the entire supply chain to ensure that CE initiatives align effectively with SDGs.

Although considerable progress has been made in exploring the technological, industrial, and environmental dimensions of circular fashion, a more comprehensive perspective is critical for addressing social, economic, and governance-related sustainable development goals (SDGs). In particular, greater attention to social sustainability concerns—such as fair wages, labor rights, and gender equity (SDGs 5, 8, and 10)—is essential for building equitable supply chains. It is also imperative to investigate the public health implications of circular textiles (SDG 3), especially with respect to chemical safety and microplastic pollution (SDG 14). Educational initiatives (SDG 4) can further accelerate community-level adoption of circular practices, whereas deeper consideration of biodiversity impacts (SDG 15) will clarify how textile production affects ecosystems. Strengthening institutional mechanisms (SDG 16) through robust policy enforcement, corporate accountability, and transparent supply chains is equally important for fostering long-term change. Collaboration on an international scale (SDG 17) can facilitate standardized frameworks and increase the scalability of CE efforts across markets. By broadening SDG-aligned research, practitioners and scholars in textiles and apparel can move beyond merely reducing waste and emissions toward strategies that are ethical, inclusive, and economically viable, forging long-term sustainability in the TAF industry.

4.1. Implications

The findings from topic modeling and case studies highlight key areas for advancing circular economy (CE) transitions in the textile, apparel, and fashion (TAF) industry. While recycling innovations, circular business models, and digital supply chain solutions have gained traction, challenges remain in waste management, regulatory alignment, stakeholder engagement [112], and the scalability of circular practices [2]. To ensure that CE strategies contribute meaningfully to sustainability goals, policy and business interventions must address these gaps while integrating emerging developments such as carbon credit mechanisms and net-zero commitments [113] and digital traceability solutions.

4.1.1. Implications for Theory

These findings enrich existing theories by illustrating how different theoretical lenses can complement one another when applied to circular economy transitions in the TAF industry, aligning with key SDGs. In particular, institutional theory is advanced through evidence that both industry-wide isomorphic pressures (e.g., certifications, norms for upcycled materials) and region-specific regulatory drivers encourage firms to adopt circular strategies. These institutional shifts contribute to SDG 12 (Responsible Consumption and Production) by fostering sustainable material use and regulatory compliance. The observed nuances of stakeholder influence, including demands for transparency and the formalization of ownership structures in product-as-service models, deepen our understanding of the mechanisms by which formal rules, cultural expectations, and market signals converge to shape organizational behavior—critical for advancing SDG 16 (Peace, Justice, and Strong Institutions) by promoting accountability and ethical governance in supply chains.

The natural resource-based view (NRBV) (often combined with dynamic capabilities) is extended by revealing how strategic collaboration across supply chains and continual reconfiguration of resources are prerequisites for closing material loops. The cases suggest that merely possessing technological or knowledge resources is insufficient unless firms can continually adapt those resources to emerging market realities and sustainability expectations. This evidence strengthens the case for SDG 9 (Industry, Innovation, and Infrastructure) by emphasizing the role of innovation, coevolution with customers and suppliers, and resource deployment aimed at reducing environmental impacts to sustain competitive advantage in circular ecosystems—the key to fostering sustainable industrialization.

At the methodological level, stratification theory and systems theory receive further elaboration through their application to complex, uncertain contexts such as multitiered supplier networks and small-to-medium enterprise ecosystems. Integrating stratified decision-making frameworks with systems thinking highlights the importance of assessing readiness and maturity at multiple organizational layers, a principle that reinforces SDG 8 (Decent Work and Economic Growth) by improving sustainability-oriented decision-making in SMEs. Finally, the theory of planned behavior is refined by incorporating environment-specific constructs—such as green economic incentives and environmental commitment—that elucidate how attitudes, subjective norms, and perceived behavioral control interact with firm-level maturity. This extended TPB framework offers a more detailed map of how belief systems and social pressures shape readiness for circular adoption in emerging economies, contributing to SDG 13 (climate action) by fostering behavioral shifts toward low-carbon, circular business models.

Taken together, these insights broaden the theoretical scope of institutional, resource-based, and behavioral perspectives on sustainability, underscoring the necessity for multi theory integration to capture the complexities of circular transformations and their alignment with global sustainability goals.

4.1.2. Implications for Policy

Governments play a central role in aligning circular economy (CE) transitions with broader sustainability goals [12] by strengthening regulations on waste management, incentivizing circular business models, enforcing supply chain transparency, and integrating CE practices into net-zero strategies (Figure 5). These efforts contribute to key SDGs by ensuring responsible consumption and production patterns, reducing environmental impact, and promoting fair labor practices.

Enhancing Textile Waste Management Regulations: Topic modeling and case studies emphasize recycling inefficiencies, global waste redistribution challenges, and industry-wide barriers to textile-to-textile recycling. Policies should move beyond landfill diversion to mandate extended producer responsibility (EPR) schemes, standardized collection systems, and recycling targets for different material categories. These interventions directly support SDG 12 (Responsible Consumption and Production) by promoting sustainable resource use and minimizing textile waste. Case studies on closed-loop supply chains highlight the importance of structured frameworks that support local processing rather than dependence on the global waste trade, which aligns with SDG 9 (Industry, Innovation, and Infrastructure) by fostering localized, sustainable recycling industries.

Standardizing Circular Business Models and Market Incentives: Case studies indicate that companies adopting slow fashion, repair, and closed-loop production face financial barriers in scaling circular practices. Policies should establish financial mechanisms such as tax incentives, green financing, and subsidies for circular business models, facilitating a transition away from fast fashion. By linking product-as-a-service (PaaS) models and extended product lifespans with incentives, regulators can encourage businesses to adopt sustainable production models. These measures contribute to SDG 8 (Decent Work and Economic Growth) by supporting sustainable business practices and job creation within the circular fashion economy.

Integrating Net-Zero and Carbon Credit Mechanisms: Many CE models focus on waste reduction but do not explicitly integrate carbon impact assessments. Future policies should connect textile recycling, bio-based materials, and digital traceability solutions with carbon credit trading systems. Governments can certify emissions reductions from circular strategies, allowing businesses to offset their footprint through carbon trading linked to textile circularity projects. This policy direction advances SDG 13 (climate action) by reducing emissions from textile production and promoting low-carbon alternatives.

Improving Supply Chain Transparency Through Digital Regulations: Studies emphasize traceability gaps, counterfeiting risks, and difficulties in tracking material flows across circular supply chains. Governments should mandate blockchain-based traceability, digital passports for textiles, and AI-driven supply chain monitoring. Emerging regulations such as the EU’s Digital Product Passport (DPP) will soon require textile products to disclose environmental data, reinforcing responsible sourcing and disposal [114]. These transparency initiatives align with SDG 16 (Peace, Justice, and Strong Institutions) by fostering ethical governance, reducing fraud, and improving accountability in global textile supply chains.

Addressing Social and Ethical Sustainability in CE Policies: The case studies highlight the limited coverage of social aspects in CE models, including labor conditions and equitable access to sustainable materials. Youth engagement in informal textile recycling, gendered division of work in supply chains, and unequal access to sustainable technological innovation have received relatively less attention. Future research opportunities should expand CE frameworks in policy analysis to include labor protection, ethical sourcing requirements, and fair wages in the recycling and remanufacturing industries. Integrating circular economy strategies with SDG 8 (Decent Work and Economic Growth) and SDG 12 (Responsible Consumption and Production) ensures that CE transitions benefit workers and communities, not just material flows. Furthermore, collaboration frameworks should guarantee the participation of underprivileged communities, especially in developing countries where labor vulnerability and informality are widespread. By embedding social sustainability within CE policies, governments can create an inclusive and just transition toward a circular textile economy.

4.1.3. Implications for Practitioners

For businesses, the transition to a circular economy (CE) is no longer an option but rather a necessity driven by consumer demand, evolving regulations, and financial incentives tied to sustainability performance [110]. Topic modeling and case studies reveal that key areas for strategic intervention include scaling recycling infrastructure, digital traceability adoption, circular business model expansion, and net-zero alignment (Figure 6). These strategies contribute to multiple SDGs by promoting responsible production, reducing environmental impact, and fostering innovation in sustainable business practices.

Expanding Textile-to-Textile Recycling Capacity: The limited availability of textile-to-textile recycling infrastructure is a critical barrier identified in case studies. Businesses should invest in fiber recovery technologies, chemical and mechanical recycling solutions, and smart waste-sorting systems. The development of industry-wide collaboration on textile recycling pathways can increase efficiency, reduce dependency on virgin fibers, and contribute to net-zero targets. These efforts directly support SDG 12 (Responsible Consumption and Production) by enabling closed-loop recycling systems and SDG 9 (Industry, Innovation, and Infrastructure) by fostering technological advancements in textile recycling.

Leveraging Digital Solutions for Supply Chain Transparency: Studies indicate that a lack of material traceability and counterfeiting risks hinder circular supply chain development. Companies can implement blockchain, RFID, and AI-powered tracking to monitor resource flows and enhance circular operations. AI-driven reverse logistics optimization can improve collection and processing, whereas blockchain-powered smart contracts can facilitate trade agreements for secondary raw materials. Strengthening digital traceability contributes to SDG 16 (Peace, Justice, and Strong Institutions) by promoting ethical sourcing, reducing fraud, and increasing accountability in supply chains.

Scaling Circular Business Models to Extend Product Lifespan: Case studies suggest that rental fashion, resale platforms, and product repair services are emerging as viable alternatives to disposable fast fashion. Businesses should scale these models by integrating on-demand production, modular product design for repairability, and AI-driven resale recommendations. Innovations in garment customization, digital fitting technologies, and AI-driven demand forecasting can reduce overproduction and textile waste. These strategies align with SDG 8 (Decent Work and Economic Growth) by fostering sustainable employment opportunities and with SDG 12 (Responsible Consumption and Production) by extending product lifespans and reducing textile waste.

Aligning Circular Strategies with Net-Zero Goals: Circular economy strategies must align with broader net-zero and carbon-reduction targets. Businesses can integrate carbon-accounting tools to measure the footprint of materials and production processes. Participation in carbon credit markets through textile circularity projects—such as fiber regeneration, biobased material investment, and closed-loop waste processing—allows businesses to offset emissions while advancing sustainability goals. These initiatives contribute directly to SDG 13 (climate action) by promoting emissions reduction in textile production.

Engaging Consumers in Circular Practices: Studies highlight consumer reluctance due to a lack of awareness, pricing concerns, and perceived risks of secondhand and upcycled clothing. Businesses must focus on clear impact communication, digital product labeling, and incentives for responsible consumption. Digital platforms can enhance engagement through gamified recycling incentives, trade-in programs, and AI-driven resale recommendations. Encouraging sustainable consumption practices supports SDG 12 (Responsible Consumption and Production) by shifting consumer behavior toward circular fashion choices.

Furthermore, the cases are examples of successful initiatives that have brought new business models involving recycling, service business models, and smart logistics to the market, but important SDGs such as SDG 10 (reduced inequalities), SDG 15 (life on the land), and SDG 16 (strong Institutions) are less well addressed. To address these gaps, CE transitions need to embed inclusive models for informal workers [98], implement regenerative sourcing tied to biodiversity metrics [5], and expand blockchain solutions toward participatory governance [101]. This kind of integration also makes circular economic pathways that are not just efficient and innovative but that contribute to social justice, ecological integrity, and institutional accountability in line with possible multidimensional sustainability objectives.

4.2. Future Research Directions Based on the ADO Framework

To chart future research directions for CE practices in the TAF industry, this study adopts the Antecedents–Decisions–Outcomes (ADO) framework [27,28] (Figure 7). The ADO framework provides a structured yet flexible approach to organizing research gaps and opportunities by systematically linking the factors driving CE adoption (antecedents), the strategic responses taken by firms and policymakers (decisions), and the resulting impacts on sustainability and the SDGs (outcomes). Compared with other frameworks, such as the theory, construct, characteristics, and methods (TCCM) framework or the 6 W framework, ADO is particularly effective for guiding future research without imposing rigid theoretical constraints [27]. A significant advantage of using the ADO framework is its ability to highlight interdependencies between these three components. Unlike linear models that separate research gaps into isolated themes, ADO allows researchers to trace how antecedents influence decisions and how these decisions, in turn, shape outcomes. This integrative approach is particularly valuable for CE research in the TAF industry, where regulatory shifts, technological advancements, and evolving consumer behaviors interact in complex ways. Furthermore, the ADO facilitates the identification of research gaps in areas where policy interventions, digital technologies, and circular business models have yet to yield measurable sustainability outcomes. By applying the ADO framework, this study not only organizes existing knowledge but also provides a structured roadmap for future research, ensuring that investigations into the CE in the TAF industry remain impact driven and aligned with global sustainability goals.

4.2.1. Antecedents: Drivers of the CE in the TAF Industry

Research should explore the conditions enabling or inhibiting CE adoption in different regions and industry sectors. Regulatory frameworks, digital transformation, financial mechanisms, and consumer expectations shape how firms transition from linear to circular supply chains. Regulations in the Global North are strengthening, requiring companies to implement traceability systems and responsible production models [101], aligning with SDG 12.6 (encouraging companies to adopt sustainable practices and integrate sustainability information into their reporting). However, many Global South economies face infrastructure gaps in waste collection, recycling, and fair labor practices [80], reinforcing the need for SDG 10.2 (empowering and promoting the inclusion of all, irrespective of status). Bridging these disparities is vital for ensuring that CE transitions create equitable economic and environmental benefits rather than reinforcing global imbalances. Owing to their limited resources, SMEs face great difficulty in adopting Industry 4.0 technologies and CE practices. The case study by Kayikci et al. [67] develops a framework that they apply to analyze the readiness and maturity level of four SMEs in Turkey for smart circular supply chains (SCSCs). Their framework can assist decision-makers in selecting the critical dimensions to integrate Industry 4.0 into their organization. This highlights the importance of monitoring the readiness of all supply chain actors for successful SDG-aligned Industry 4.0 and CE adoption, as unilateral readiness in a single company is not enough for the transformation of the entire system. This integrated assessment along the supply chain is a research gap that future research can address.

Financial incentives play a role in CE transitions, with carbon pricing and tax credits for circular initiatives [100] emerging as mechanisms to drive sustainability, supporting SDG 13.2 (integrating climate change measures into policies and planning). However, the effectiveness of these financial mechanisms is moderated by firm size, market structure, and regulatory consistency. For example, large multinational firms may benefit more from tax incentives, whereas smaller firms in developing economies may face structural barriers to accessing sustainability-linked financing. Future research should assess how carbon credit trading linked to textile recycling can make CE models economically viable, particularly by examining how financial capital access moderates the success of CE transitions.

Consumer behavior remains a critical determinant of CE success. Studies show that consumer willingness to pay for circular products, trust in secondhand textiles, and engagement with rental and repair models [86] influence adoption. The gendered dimensions of circular fashion consumption also warrant attention, as women are both key consumers and disproportionately represented in informal textile waste economies [26], aligning with SDG 5.5 (ensuring full and effective participation of women in leadership roles). The effectiveness of digital engagement strategies, such as blockchain-based product verification and AI-driven resale platforms, may be mediated by consumer digital literacy and trust in digital platforms [94], directly linked to SDG 9.5 (enhancing the research and technological capabilities of industrial sectors).

4.2.2. Decisions: Implementing Circular Business Models and Supply Chain Innovations

The implementation of CE strategies varies across business models and regional supply chains [106,111]. While some firms are investing in textile-to-textile recycling and closed-loop supply chains [99], others are experimenting with product–service systems (PSSs), such as rental fashion, leasing models, and repair networks [5]. Research should focus on the scalability of these models and the role of digital innovations in reducing logistical costs [67], addressing SDG 9.4 (upgrading infrastructure and retrofitting industries to make them sustainable). AI-driven smart circular supply chains (SCSCs) and automated waste-sorting systems could improve operational efficiency and advance digital transformation in CEs, but the effectiveness of these solutions is moderated by digital infrastructure availability, particularly in developing economies.

Global supply chains play a key role in CE transitions, with brands in the Global North implementing CE initiatives while outsourcing production to regions with weaker environmental and labor protections [97]. The risk of carbon leakage—where emissions reductions in one region are offset by increased emissions elsewhere [103]—warrants further investigation. The success of circular supply chain policies in preventing environmental externalities may be mediated by governance mechanisms such as extended producer responsibility (EPR) and fair-trade agreements. Research should explore how CE policies can integrate fair trade practices and prevent the externalization of environmental costs to developing economies [104], aligning with SDG 8.8 (protecting labor rights and promoting safe and secure working environments for all workers).

Net-zero commitments influence corporate decision-making, with many brands integrating fiber-to-fiber recycling, biodegradable materials, and renewable energy sources into their operations [115]. Future research should examine how circular supply chains contribute to net-zero goals through lifecycle carbon assessments, investment in green materials, and energy-efficient production processes, supporting SDG 7.2 (increasing the share of renewable energy in the global energy mix) and SDG 13.3 (improving education and awareness of climate mitigation strategies) [115]. However, the success of net-zero strategies in CEs is moderated by policy support and technological maturity, with variations in how firms adopt these solutions on the basis of access to green financing and innovation ecosystems.

4.2.3. Outcomes: Measuring the Impact of Circular Economy Strategies

Assessing the long-term success of CE models requires standardized metrics for economic, environmental, and social performance. Research should focus on developing uniform carbon footprint-reduction measures, material efficiency benchmarks, and waste-diversion tracking systems [97], supporting SDG 12.5 (substantially reducing waste generation through prevention, reduction, recycling, and reuse). However, the effectiveness of these impact assessments may be moderated by data availability and industry transparency, particularly where supply chain opacity limits accurate reporting.

Despite the potential role of CE in promoting social sustainability (for example, through job creation, fair labor standards, and equitable economic opportunities), businesses that incorporate circular flows solely due to environmental regulations (as an antecedent) may not prioritize social concerns (decision) and may run counter to social sustainability goals (outcome). This underscores the need to understand the SDGs as a system and pay close attention to the synergies and trade-offs among the different SDGs in decision-making regarding which circular practices and technologies to adopt. Research should examine how CE transitions can improve working conditions in recycling and repair industries, formalize waste collection economies, and increase financial inclusion for small textile enterprises, contributing to SDG 8.3 (promoting policies that support productive activities, decent job creation, and entrepreneurship). The economic sustainability of circular business models is another area requiring further research, as firms face high upfront costs in transitioning to circular manufacturing, digital traceability, and green material sourcing [102].

The long-term adoption of CE practices may be mediated by firm-level capabilities such as absorptive capacity—the ability of companies to integrate and apply sustainability innovations. Research should investigate how investment strategies, blended finance, and impact investing mitigate risks and create viable financial models for circular enterprises [76]. Additionally, the effectiveness of carbon credit schemes and sustainability-linked financing in accelerating CE adoption should be examined, directly supporting SDG 13.2 (integrating climate change policies into corporate decision-making) and SDG 9.3 (supporting small- and medium–sized enterprises’ access to finance, including sustainable business models).

Gender-responsive CE policies can further increase economic participation in circular industries. Women play a significant role in informal textile recycling economies but face barriers to accessing CE entrepreneurship and decision-making [26]. Addressing these structural inequalities by ensuring fair wages, financial literacy, and access to capital for women-led circular enterprises can contribute to SDG 5.a (ensuring women’s equal rights to economic resources). The social impacts of CE transitions, such as the distribution of economic benefits and their impact on vulnerable communities, require more robust research to align the CE with a just and inclusive sustainability transition.

This study recommends scaled-up solutions, including public—private partnerships (PPPs) and international collaboration, to mitigate the fragmented CE practice. PPPs can accelerate infrastructure development for textile-to-textile recycling, whereas international partnerships can align product labeling, traceability, and material recovery criteria. These scalable governance innovations are consistent with SDGs 9, 10, 12, 15, 16, and 17 and shed light on a model for regional and global mechanisms. For example, Mahanty and Domenech highlighted the absence of a harmonized approach within the UK while making a case for participatory circular business models (CBMs), which are rooted in social learning. This is a call for multistakeholder governance arrangements (such as PPP models) that coordinate policy, private sector innovation, and civil society action (SDG 17) [96]. Similarly, Kayikci et al. [66] introduced Turkish SMEs’ readiness for Industry 4.0 in CE transitions and suggested Smart Circular Supply Chains. Such models illustrate the ways in which global CE capacity building and cross-border knowledge transfer, e.g., through EU or ASEAN platforms, can standardize digital infrastructure for circular innovation [66,116]. Therefore, the conclusions of Mahanty and Domenech and Martina and Oskam [101] confirm that CE can be counteracted via institutionalized PPPs and regional-coordinated cooperation mechanisms. These methods drive co-investment in recycling infrastructure, traceability systems, and the pursuit of standardization—enlisting industry, government and civil society strategies under SDG 17. The gap in CE maturity among Bangladesh, the UK, the Netherlands, and Turkey indicates the need for cross-border CE policies, including joint EPR systems, blockchain-driven traceability harmonized across trade zones, and PPP-based CE centers. The Ellen MacArthur Foundation advocates for efforts that engage in precompetitive collaboration and demonstration projects, strengthening the argument for common CE governance [9].

Furthermore, the ADO checklist is demonstrated via a practical example: Policy requirements for extended producer responsibility (Antecedent) cause firms to implement digital product passports and blockchain tracking systems (decision), leading to decreased textile waste and increased traceability (outcome). That is, these cases illustrate how regulatory antecedents incarnate in technological choices and, in turn, serve SDG 12 and SDG 16 through increased institutional accountability and resource efficiency. For instance:

Policy Antecedent → Tech Adoption → Waste Reduction SMEs adopted supply chain dashboards to better track waste and comply with the law in France, where policy gaps [100] were identified. Likewise, the blockchain application for Germany–UK [101] enhanced traceability in line with CE objectives.

Stakeholder Engagement → Participatory CBM → Collaboration: In response to UK-based misalignment in CE transitions [97], participatory CBMs are introduced to build cross-value chain collaboration and alignment with shared sustainability goals (SDG 17).

Tech Infrastructure → Integration of Blockchain → Transparency: Poor traceability [100] induces the utilization of blockchain and LCA, thereby ensuring better quality of environmental data, as well as transparency in the supply chain (SDG 12, 13).

This study has certain limitations stemming from the scope of the data sources, the chosen machine-learning techniques, and the complexity of the SDG mapping initiatives. Relying on a single bibliometric database can simplify data collection but may not fully capture the breadth of research on CEs in TAF, as database-specific biases can emerge within the PRISMA framework. Although combining multiple databases such as Scopus, Web of Science, and PubMed can lead to a more comprehensive dataset [117], errors in DOI indexing and metadata can complicate the merging process and potentially affect data accuracy [118]. In this study, we mitigate these issues by integrating qualitative case studies that enhance the context-sensitive understanding of the CE in TAF.

While machine-learning-based BERTopic modeling efficiently synthesizes trends, concerns regarding algorithmic bias persist [119]. Pretrained language models such as BERT, which underlie BERTopic, can inadvertently encode social biases related to gender, race, and ethnicity [120,121], as well as publication biases [122]. These issues can impact both the comprehensiveness and objectivity of topic modeling. Nevertheless, BERTopic helps reduce human bias in classification [31], provided that data quality and model assumptions are carefully monitored. We further addressed the risk of misrepresentation by employing mixed methods: in-depth case study analyses complemented the AI-driven insights, enriching the robustness of the findings. Another layer of complexity arises in mapping publications to SDGs [123]. Different SDG mapping initiatives—such as Elsevier’s data-driven approach, the more conceptual strategy of the University of Auckland, and the less detailed but collaborative Aurora Network methodology—each have distinct strengths and limitations [116,123]. Future work should compare multiple SDG mapping methods to improve result validity and accommodate the diverse socioeconomic and cultural contexts of energy access. Through these combined efforts, our study takes steps toward a more comprehensive and equitable examination of gender disparities in energy transitions, although larger datasets, broader case selections, and comparative analyses across regions remain key avenues for future research.

5. Conclusions

This study underscores the evolving landscape of circular economy (CE) practices in the textile, apparel, and fashion (TAF) industries, illustrating how emerging technologies, circular business models (CBMs), consumer behavior, and policy measures converge to drive more sustainable production and consumption patterns. Addressing RQ1, the AI-based topic modeling approach reveals key emerging themes, including waste management, closed-loop supply chains, digital traceability, and consumer engagement, each of which aligns with relevant Sustainable Development Goals (SDGs), such as industrial innovation (SDG 9), responsible consumption (SDG 12), decent work (SDG 8), sanitation (SDG 6), and clean energy (SDG 7). Mapping these topics to the SDGs highlights the sector’s transition toward a more resilient, equitable, and resource-efficient future, with multilevel impacts ranging from greenhouse gas mitigation to improved labor conditions and inclusive economic opportunities.

In response to RQ2, the study identifies specific circular practices, CBMs, and enabling technologies implemented in the TAF industry. Case studies illustrate how innovations such as fiber-to-fiber recycling, product-as-a-service (PaaS) models, AI-driven reverse logistics, and bio-based materials contribute to the scalability and feasibility of CE transitions. However, mapping these implementations to the SDGs also reveals gaps in integration, particularly in areas related to social equity (SDG 10), biodiversity conservation (SDG 15), and governance transparency (SDG 16). These findings suggest that while technological and business model innovations are advancing, a more holistic approach incorporating ethical labor practices, sustainable sourcing, and policy support is essential for meaningful progress.

Addressing RQ3, the case study analysis highlights systemic barriers to CE adoption, including regulatory misalignment, financial constraints, supply chain fragmentation, and consumer skepticism. Despite these challenges, multistakeholder collaborations—involving governments, brands, recyclers, technology providers, and consumers—emerge as critical enablers of CE adoption. Strengthening policy coherence, data-driven decision-making, and participatory approaches can help overcome these barriers and accelerate sustainable transitions in the TAF sector. Additionally, integrating CE strategies with carbon-reduction commitments (SDG 13) and urban sustainability initiatives (SDG 11) can further amplify positive outcomes.

In the future, leveraging frameworks such as Antecedents–Decisions–Outcomes (ADO) can enhance the clarity of future research, ensuring that drivers of CE adoption, strategic choices in supply chains, and sustainability outcomes are systematically addressed. Incorporating topic modeling and SDG mapping into this framework will help pinpoint synergies and trade-offs across environmental, social, and economic dimensions, guiding targeted interventions that bolster the net-zero goals of the TAF industry. Additionally, expanding research on underexplored SDGs—such as gender equity (SDG 5), poverty reduction (SDG 1), and biodiversity conservation (SDG 15)—will ensure a more inclusive and balanced CE transition. Ultimately, cross-sectoral collaboration, inclusive policy measures, and digital innovations will be central to advancing holistic, impactful, and scalable circular economy transformation in the textile and apparel industry.