Blockchain for Supply Chain Transparency in Fast Fashion: A Scoping Review of Primary Studies, Implementation Barriers, and Sustainability Pathways

The fast-fashion model accelerates product turnover and intensifies the environmental burden of the textile and clothing value chain, including water use, chemical pollution, greenhouse-gas emissions, and large volumes of waste (N​i​i​n​i​m​ä​k​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​0). At the same time, textile and apparel supply chains are globally fragmented and socially risk-laden, which makes supplier transparency, lower-tier monitoring, and socially sustainable supply-chain management particularly difficult to achieve in practice (K​ö​k​s​a​l​ ​e​t​ ​a​l​.​,​ ​2​0​1​7). Against this background, blockchain has been proposed as a trusted digital infrastructure for supply-chain management because immutable ledgers and smart contracts can improve traceability, provenance, and inter-organizational information sharing (S​a​b​e​r​i​ ​e​t​ ​a​l​.​,​ ​2​0​1​9).

For this review, fast fashion is treated as a specific supply-chain configuration rather than as a synonym for the whole textile industry. Its distinctive features are short design-to-retail cycles, large and frequently changing assortments, volatile supplier allocation, intense cost compression, and multi-tier subcontracting. Studies located in adjacent textile or fiber contexts were retained only when their evidence was directly transferable to fast-fashion transparency, for example where they examined fiber provenance, product-passport design, batch-level life-cycle assessment, or upstream compliance documentation. The Results therefore differentiate fast-fashion/apparel-specific evidence from broader textile evidence instead of treating the wider textile sector as a homogeneous proxy. These three problem streams converge directly in fast fashion. The sector is characterized by short product life cycles, frequent sourcing changes, extensive subcontracting, and intense price pressure, all of which create incentives for speed and opacity rather than for durable record keeping or comprehensive disclosure. Conventional transparency tools, such as periodic audits, supplier declarations, and fragmented enterprise databases, often provide only partial visibility and are especially weak beyond first-tier suppliers. As a result, brands may be able to document compliance at the point of purchase while still struggling to verify fiber origin, process integrity, environmental performance, or labor conditions deeper in the chain.

Blockchain is attractive in this setting because it promises an auditable chain of custody across geographically distributed actors. In principle, raw-material producers, mills, manufacturers, logistics firms, brands, and even consumers can access verified event records linked to a product or batch. When blockchain is connected to Internet of Things (IoT) sensors, radio frequency identification (RFID) tags, quick response (QR) codes, or enterprise resource planning systems, the technology can support time-stamped provenance claims, certification checks, and sustainability reporting at a finer level of granularity than traditional paper-based systems. Yet the practical feasibility of this promise remains uncertain because implementation in fashion supply chains must contend with uneven digitization, data-quality problems, high onboarding costs, and commercial reluctance to share information.

Published work on blockchain in fashion and textile supply chains has grown quickly, but the literature is heterogeneous. Some papers present conceptual architectures or prototype designs, others examine pilot implementations or case studies, and a substantial share of the literature consists of reviews rather than original studies. That heterogeneity makes it difficult to understand what has actually been tested, where evidence is concentrated, which transparency functions are most mature, and which barriers remain unresolved in real supply chains.

A scoping-review design was particularly appropriate because the available literature spans managerial analyses, systems engineering, design-science studies, surveys, and industry cases that do not share a single evaluative outcome. A conventional effectiveness review would therefore have obscured important variation in how transparency is conceptualized and operationalized. In this study, transparency was treated broadly as the capacity to generate trusted, retrievable, and actor-relevant information on product origin, material flows, production events, certifications, and sustainability attributes across the chain. That broader framing made it possible to map both technical and organizational dimensions of transparency rather than reducing the concept to a single traceability indicator.

This scoping review therefore maps primary studies on blockchain for supply-chain transparency in fast fashion and closely related textile-apparel contexts. The review had four objectives: to characterize the study designs, settings, and technical architectures used in primary research; to synthesize reported transparency outcomes and sustainability implications across environmental, economic, and social dimensions; to identify recurrent barriers and enabling conditions for implementation; and to clarify where empirical evidence is strongest and where the field remains predominantly conceptual. Figure 1 presents the guiding framework used to interpret blockchain not as a self-sufficient solution, but as a socio-technical infrastructure whose sustainability value depends on source-data credibility, governance, and incentives across supply-chain tiers.

The methodology is organized to separate the search strategy, eligibility criteria, study selection, charting, synthesis, and transparency limitations. Because raw database-by-database retrieval logs were not preserved, the manuscript avoids reconstructing database-specific counts post hoc and reports the verified de-duplicated screening set (n = 122) together with a dedicated limitation statement in Section 2.7.

In this study, the search was conducted in PubMed/MEDLINE, EMBASE, Web of Science, Scopus, PsycINFO, and CINAHL. Accordingly, the search concept was translated into PubMed/MEDLINE, EMBASE, Web of Science, Scopus, PsycINFO, and CINAHL. The core search combined controlled vocabulary where available and free-text terms for four domains: blockchain technology, supply-chain management, transparency/traceability, and the fashion-textile-apparel sector. A representative PubMed-style string was as follows: (“Blockchain”[Mesh] OR blockchain*[tiab] OR “distributed ledger*”[tiab]) AND (“Supply Chain Management”[Mesh] OR “supply chain*”[tiab] OR “value chain*”[tiab]) AND (transparency[tiab] OR traceab*[tiab] OR visibil*[tiab] OR provenance[tiab]) AND (“Textiles”[Mesh] OR “Clothing”[Mesh] OR “fast fashion”[tiab] OR fashion[tiab] OR apparel[tiab] OR textile*[tiab] OR clothing[tiab]). Equivalent syntax was adapted for the remaining databases using Boolean operators, truncation, and field restrictions. Searches were limited to English-language records.

The search period was set from January 1, 2010, to June 30, 2025. An English-language restriction was applied because the full-text extraction materials available for manuscript development were in English, and because most technical reporting in this area is disseminated in English-language outlets. After retrieval, records were assumed to have been consolidated in a master library and de-duplicated before screening.

In this paper, records were eligible when they: (1) focused on blockchain or distributed-ledger applications in supply-chain management; (2) addressed fast fashion, textiles, clothing, apparel, or directly transferable textile-apparel contexts; (3) examined transparency-related outcomes, including traceability, provenance, visibility, authenticity, compliance, or sustainability disclosure; (4) reported substantial primary-study content, such as empirical research, case studies, pilot studies, proof-of-concept implementations, design-science development, or system-testing studies; and (5) were peer-reviewed or otherwise provided sufficient technical substance for analysis. Records were excluded when blockchain was peripheral to the paper, when supply-chain management was not the application focus, when transparency was not an outcome of interest, or when only an abstract/editorial/opinion piece was available.

Screening proceeded sequentially at the title/abstract and full-text stages using the eligibility criteria. Of 122 deduplicated records, 16 were excluded during title/abstract screening because they lacked sufficient blockchain focus, textile-apparel relevance, or publication substance. Reports were sought for the remaining 106 records; 48 could not be retrieved because full text was unavailable. The 58 retrieved reports were assessed for eligibility, and 27 were excluded: insufficient blockchain focus (n = 2), no relevant transparency outcome (n = 1), ineligible study type or methodology (n = 1), no supply-chain management application (n = 1), secondary research (n = 13), and other reasons or evidence below the review threshold (n = 9). The final corpus comprised 31 primary studies. Figure 2 presents the selection flow.

To preserve consistency across heterogeneous designs, extraction focused not only on whether blockchain was mentioned, but on what role it played in the transparency chain. Thus, studies were distinguished according to whether blockchain functioned as the principal intervention, one component of a broader digital ecosystem, or a conceptual governance mechanism for supply-chain documentation. Outcome charting likewise distinguished among direct performance evidence, implementation-process evidence, and forward-looking claims not yet tested in operational environments. This distinction was essential because many papers contained strong normative claims about what blockchain should achieve, but fewer provided operational evidence about what it had actually achieved.

A structured charting form was used to extract study-level information on authorship, year, setting, study design, blockchain type, complementary technologies, transparency function, development stage, reported outcomes, barriers, success factors, sustainability implications, and stakeholder perspectives. For conceptual and architecture papers, charting focused on the problem addressed, the proposed system components, and the implementation claims made by the authors. For case studies, pilots, and surveys, charting additionally captured the reported context, stakeholder group, and any quantitative or comparative results provided in the paper. The charting form was iteratively refined to ensure that technical design features and implementation context were captured alongside substantive outcomes.

The synthesis combined descriptive mapping with qualitative thematic analysis. First, the included studies were summarized in a study-characteristics table and grouped by methodological design, geography, blockchain architecture, and development stage. Second, findings were organized into recurrent thematic domains: transparency functions and outcomes; implementation barriers; success factors and enablers; sustainability impacts; stakeholder perspectives; and technical architectures. Third, where studies reported direct comparisons or quantitative performance indicators, these were extracted into a comparative summary table rather than pooled statistically. Formal risk-of-bias assessment was not undertaken because scoping reviews aim to map the extent and character of evidence rather than generate a weighted estimate of effect (A​r​k​s​e​y​ ​&​ ​O​’​M​a​l​l​e​y​,​ ​2​0​0​5; P​e​t​e​r​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; T​r​i​c​c​o​ ​e​t​ ​a​l​.​,​ ​2​0​1​8).

To improve reproducibility and make the evidence base easier to audit, Appendix Table A1 lists each included primary study with publication year, country/region, study design or evidence type, research context, and the main transparency contribution.

Because the raw database-by-database retrieval logs were not preserved in the review record available for revision, the identification stage cannot be audited with the same precision as a fully prospectively registered systematic review. This limitation could introduce retrieval bias, including possible under-identification of non-English studies, grey literature, or records indexed in only one database. The limitation does not affect the numerically verified screened set, full-text screening decisions, or included-study count reported here, but it narrows the evidentiary claim of the article. Accordingly, the review is presented as a transparent scoping map of preserved primary-study evidence rather than as a fully reproducible effectiveness review.

Figure 2 summarizes the study-selection process. The deduplicated screening set comprised 122 records. 16 records were excluded during title/abstract screening, leaving 106 reports sought for retrieval. Full text was unavailable for 48 reports, so 58 reports underwent eligibility assessment. Of these, 27 were excluded, including 13 secondary-research reports. The remaining 31 primary studies were retained for data charting and synthesis.

The included literature is summarized in Table 1, which now reports the transparency outcome or evidence contribution for each study. Publication years ranged from 2020 to 2025, indicating a recent and still rapidly developing field. The primary-study corpus comprised qualitative interview or observational inquiries (C​u​c​,​ ​2​0​2​3; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5), multi-case and case-based investigations (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4), survey-based quantitative analyses (D​h​i​l​l​o​n​,​ ​2​0​2​4; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5), mixed-method studies (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​o​g​o​s​ ​&​ ​F​r​a​g​a​p​a​n​e​,​ ​2​0​2​2; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5), design-science or prototype-development papers (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4), and conceptual architecture papers (G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; M​a​j​u​m​d​a​r​,​ ​2​0​2​5; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; S​h​a​k​i​r​,​ ​2​0​2​5). Evidence was classified as fast-fashion/apparel-specific when it examined fashion brands, garment production, apparel retail, or buyer-driven apparel chains directly; evidence from wool, cotton, textile processing, or digital-passport contexts was treated as transferable textile evidence rather than as direct fast-fashion evidence. This distinction prevents the broader textile sector from being used uncritically as a substitute for fast fashion.

Geographically, the evidence base was uneven. Several papers adopted a broadly global or non-site-specific perspective (B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; C​u​c​,​ ​2​0​2​3; D​h​i​l​l​o​n​,​ ​2​0​2​4; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; M​a​j​u​m​d​a​r​,​ ​2​0​2​5; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; S​h​a​k​i​r​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4), whereas others focused on Europe (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​a​n​f​r​i​n​o​,​ ​2​0​2​4), Portugal (A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4), Pakistan (R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5), Bangladesh (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4), Indonesia (H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5), India (S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5), the United States (C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5), or cross-border textile production linking Australia or New Zealand to China (C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2). The settings were therefore concentrated in export-oriented textile-apparel systems, digitally advanced regulatory environments, or conceptual design spaces, rather than in the full range of fragmented upstream tiers that characterize the broader fast-fashion industry.

Across the corpus, permissioned blockchain architectures were dominant, especially Hyperledger Fabric (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Public-chain or tokenized approaches were present but less common and were usually confined to narrower prototyping contexts, such as Ethereum- or non-fungible token (NFT)-oriented solutions (B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Complementary technologies were frequently invoked, including IoT sensors, RFID, QR/near-field communication (NFC) identifiers, smart contracts, enterprise resource planning/management information system (ERP/MIS) integration, and off-chain storage layers (data stored outside the blockchain) (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Table 2 groups the evidence by major technological and implementation approaches.

Another striking pattern was developmental immaturity. Only a small subset of studies described pilots, practical implementations, or deployed industry cases (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5). Many others remained at prototype, conceptual, or early-stage design level (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; D​h​i​l​l​o​n​,​ ​2​0​2​4; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​a​j​u​m​d​a​r​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​g​o​s​ ​&​ ​F​r​a​g​a​p​a​n​e​,​ ​2​0​2​2; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Accordingly, the review captures a field that is rich in proposed architectures and managerial expectations, but still short on replicated real-world evaluations across full multi-tier fast-fashion supply chains.

Traceability was the dominant function across the review corpus and appeared either as an explicit outcome or as the central design goal in almost all included studies (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; C​u​c​,​ ​2​0​2​3; D​h​i​l​l​o​n​,​ ​2​0​2​4; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; M​a​j​u​m​d​a​r​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​g​o​s​ ​&​ ​F​r​a​g​a​p​a​n​e​,​ ​2​0​2​2; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Studies commonly framed transparency as the ability to generate an auditable chain of custody for fibers, yarns, fabrics, finished garments, or associated certifications. Closely related functions included provenance assurance, anti-counterfeiting, authenticity verification, compliance documentation, and sustainability reporting (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4).

Several studies provided more concrete evidence than the broader conceptual literature. The Lenzing case study documented how a permissioned blockchain and digital token system could strengthen fiber-origin verification and audit readiness in the textile and apparel chain (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1). The Blockchain and ERP-Integrated MIS (BE-IMIS) pilot reported faster traceability workflows, with the authors describing movement from day-level to hour-level tracing and audit preparation-time reductions of approximately 40%–60% (T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). In the wool sector, batch-specific blockchain traceability produced materially different life-cycle estimates than generic data, demonstrating the analytical value of more granular provenance information (C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2). A U.S.-linked apparel case study further associated blockchain-enabled resource tracking with lower waste and carbon burden over a 12-month implementation period (C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5).

Quantitative studies also suggested that blockchain contributes to transparency most effectively when it is embedded in a broader digital system rather than deployed alone. The survey-based model by K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​ ​(​2​0​2​4​) showed that IoT and blockchain integration capability had the strongest direct association with real-time supply-chain transparency, exceeding the separate contributions of blockchain alone or IoT alone. Consumer-oriented and organizational survey studies additionally linked blockchain-enabled traceability to trust, perceived efficiency, and readiness to adopt authenticated fashion products or transparent sourcing systems (D​h​i​l​l​o​n​,​ ​2​0​2​4; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). These findings support the idea that blockchain's value lies not simply in ledger immutability, but in the socio-technical network that surrounds it.

Yet the review also found that many claims about transparency remained aspirational. Conceptual or early-stage studies often argued that blockchain would prevent data tampering, improve visibility, or reduce counterfeit risk, but without independent implementation evidence or multi-site validation (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; B​u​l​l​ó​n​ ​P​é​r​e​z​ ​e​t​ ​a​l​.​,​ ​2​0​2​0; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; M​a​j​u​m​d​a​r​,​ ​2​0​2​5; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; S​h​a​k​i​r​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Even when transparency outcomes were reported, they were typically drawn from limited pilots, simulations, or bounded case environments rather than from complex production networks spanning multiple opaque tiers. Table 3 therefore isolates the small group of studies that reported direct comparisons, quantified performance changes, or before-versus-after contrasts.

Development stage and evidentiary depth were closely related. Papers at prototype or conceptual stage tended to emphasize architecture, security logic, and anticipated transparency functions, whereas pilot and case studies were more likely to report workflow effects, implementation barriers, or sustainability metrics (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). This pattern suggests that the apparent optimism of the literature is partly an artifact of study maturity: the closer a study moves toward operational deployment, the more visible the frictions of supplier onboarding, data standardization, and governance become. Conversely, papers that remain at design level can more easily assume complete data capture, actor compliance, and interoperable information flows.

Clear differences were also visible between brand-led and supplier-centered perspectives. Brand- or retailer-oriented studies often highlighted provenance claims, product passports, anti-counterfeiting, and consumer communication (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Supplier-centered or production-context studies were more concerned with documentation burden, cost, and the operational challenge of translating diverse process events into structured digital records (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5). Rather than representing conflicting findings, these viewpoints show that blockchain serves different functions at different nodes of the same supply chain. For focal firms, it can support risk management and external disclosure; for suppliers, it may function as an imposed compliance infrastructure unless it also delivers internal efficiency gains.

Taken together, the evidence points to four recurrent implementation patterns. The first is the permissioned enterprise prototype, in which a blockchain layer is added to a controlled multi-actor information system (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). The second is the digital-product-passport or tokenization model, which uses blockchain to carry product identity, circularity, or authenticity information into downstream stages (M​a​n​f​r​i​n​o​,​ ​2​0​2​4; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). The third is the compliance and sustainability-tracking model, in which blockchain is linked to audits, certifications, and environmental or social indicators (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). The fourth is the consumer-facing authentication model, which attempts to convert traceability data into trust at the point of purchase (B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; D​h​i​l​l​o​n​,​ ​2​0​2​4; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). These patterns are not mutually exclusive, but they clarify where current innovation energy is concentrated.

Implementation barriers were consistent across study types and fell into technical, economic, organizational, and governance domains. Technical barriers included scalability limitations, interoperability problems, difficulty integrating blockchain with legacy ERP or management systems, dependence on reliable upstream data capture, and heterogeneous data standards across fragmented supply chains (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Public-chain studies added concerns about transaction fees, throughput, and the practicality of on-chain storage for large or complex documentation (B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4).

Economic barriers were equally prominent. Several studies argued that blockchain adoption requires investment in software development, onboarding, tagging, training, and process redesign that is difficult to justify for small firms or for cost-sensitive production tiers (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; D​h​i​l​l​o​n​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). This concern was especially salient in Bangladesh, India, Indonesia, and other export-oriented manufacturing contexts, where upstream suppliers may be asked to comply with transparency requirements without capturing a proportionate share of the value created (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5). Cost was therefore not simply a budget issue, but a structural issue of uneven incentives across the chain.

Organizational and governance barriers extended beyond cost. Authors repeatedly described weak digital capability, limited blockchain literacy, resistance to changing established documentation routines, and reluctance to share commercially sensitive information among supply-chain actors (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; C​u​c​,​ ​2​0​2​3; D​h​i​l​l​o​n​,​ ​2​0​2​4; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). The multi-tier structure of fast-fashion sourcing exacerbated these problems because transparency depends on the participation of the very actors that often have the least bargaining power, the lowest digital readiness, or the strongest incentives to preserve opacity. This produced a recurrent paradox throughout the review: the upstream tiers in greatest need of transparent documentation are also the tiers least likely to adopt the required infrastructure voluntarily.

A complementary literature on enabling conditions emerged alongside the barrier evidence. Permissioned governance models were widely favored because they offered privacy controls, role-based access, and enterprise-oriented performance more compatible with brand-supplier relationships than open public chains (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​h​e​n​ ​e​t​ ​a​l​.​,​ ​2​0​2​1; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Interoperability standards, especially GS1-style approaches, were repeatedly recommended as a way to standardize identifiers and improve data exchange across supply-chain nodes (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5).

IoT, RFID, QR, and NFC tools were also central enablers because they reduce reliance on manual data entry and strengthen the link between physical product flows and digital records (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; P​a​l​ ​&​ ​Y​a​s​a​r​,​ ​2​0​2​1; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​h​a​k​i​r​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Studies that combined blockchain with ERP or MIS layers argued that such integration improved not only traceability but also managerial usability, audit preparation, analytics, and sustainability reporting (A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Several papers further emphasized focal-firm leadership, stakeholder collaboration, supplier training, and external regulatory pressure as prerequisites for successful implementation (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​u​c​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). In other words, the enabling conditions were not purely technical; they also depended on governance capacity, shared incentives, and institutional pressure.

Regulatory context appeared especially important. European studies linked blockchain adoption to emerging digital product passport requirements, sustainability reporting obligations, and circular-economy policy agendas (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Export-oriented supply chains in developing-country contexts responded more to buyer mandates, compliance expectations, and brand-led sustainability programs than to strong domestic regulatory incentives (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5). These differences suggest that implementation pathways vary substantially by region and by the source of coercive or normative pressure.

Environmental sustainability outcomes were the most concrete and best documented. Reported benefits included improved carbon-footprint accounting, better batch-level life-cycle assessment, reduced waste, greater visibility of recycled or circular material flows, and support for product-passport systems (A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). Economic outcomes were also relatively visible, including audit efficiencies, reduced documentation burdens, anti-counterfeiting potential, operational savings, and reputational benefits for brands capable of marketing verified provenance (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; D​h​i​l​l​o​n​,​ ​2​0​2​4; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). By contrast, social outcomes were more often asserted than demonstrated. Many papers presented labor transparency, worker-rights visibility, and ethical-compliance monitoring as major reasons to adopt blockchain, yet direct evidence of improved worker conditions or upstream labor practices remained limited (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​l​v​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​u​c​,​ ​2​0​2​3; H​a​v​r​y​l​i​u​k​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​o​g​o​s​ ​&​ ​F​r​a​g​a​p​a​n​e​,​ ​2​0​2​2; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5).

Stakeholder perspectives were similarly differentiated. Manufacturers and suppliers were primarily concerned with cost, interoperability, workflow disruption, and the burden of digital record generation (A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2; R​a​f​i​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; R​a​m​a​y​a​n​t​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; R​i​z​v​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; S​a​d​u​r​y​a​ ​&​ ​S​e​l​v​a​r​a​n​e​e​,​ ​2​0​2​5). Brands and retailers emphasized provenance claims, consumer trust, supplier-risk management, and regulatory preparedness (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; B​e​n​s​t​e​a​d​ ​e​t​ ​a​l​.​,​ ​2​0​2​4; C​u​c​,​ ​2​0​2​3; G​a​z​z​o​l​a​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; M​a​n​f​r​i​n​o​,​ ​2​0​2​4; M​o​r​e​t​t​o​ ​&​ ​M​a​c​c​h​i​o​n​,​ ​2​0​2​2). Consumer-facing studies suggested that buyers valued authenticated information and trustworthy disclosure, but also indicated that transparency tools must be easy to use and embedded in the purchase experience if they are to influence real behavior (D​h​i​l​l​o​n​,​ ​2​0​2​4; G​u​o​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; S​o​v​t​i​ć​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Across these perspectives, the most convincing pathway was not blockchain alone, but a layered model in which digital capture, permissioned governance, and focal-firm coordination jointly translated ledger functionality into usable transparency. This cross-cutting interpretation is presented schematically in Figure 1.

The revised synthesis highlights a central disagreement in the literature. Optimistic studies present blockchain as a trust-building infrastructure that can make provenance, audit trails, and sustainability claims more credible. More skeptical studies emphasize that blockchain does not remove cost asymmetries, supplier reluctance, data-quality risks, or buyer power in fragmented apparel chains. This disagreement is itself an important finding: blockchain's value is not determined by ledger design alone, but by implementation conditions, governance arrangements, and the distribution of incentives across tiers.

Across the included studies, blockchain enabled transparency through three mechanisms with different levels of evidentiary strength. First, the strongest evidence concerned tamper-resistant audit trails and provenance continuity. Case and pilot studies showed that time-stamped records could support fiber-origin verification, audit readiness, product authentication, and batch-level environmental assessment (A​h​m​e​d​ ​&​ ​M​a​c​C​a​r​t​h​y​,​ ​2​0​2​1; C​a​r​r​i​è​r​e​s​ ​e​t​ ​a​l​.​,​ ​2​0​2​2; C​h​o​w​d​h​u​r​y​,​ ​2​0​2​5; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5). Second, moderate evidence supported real-time or near-real-time data sharing when blockchain was combined with IoT, RFID, QR/NFC identifiers, ERP/MIS systems, or digital product-passport infrastructure (A​b​r​e​u​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; A​k​t​e​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; F​a​r​i​d​i​ ​e​t​ ​a​l​.​,​ ​2​0​2​3; K​a​r​i​m​ ​&​ ​T​a​l​u​k​d​e​r​,​ ​2​0​2​4; T​a​b​a​s​s​u​m​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; T​a​k​k​a​r​ ​e​t​ ​a​l​.​,​ ​2​0​2​5; W​a​n​g​ ​e​t​ ​a​l​.​,​ ​2​0​2​4). These studies suggest that the ledger becomes useful when it is embedded in a broader data-capture stack rather than used in isolation. Third, the weakest evidence concerned accountability for social sustainability. Several papers argued that blockchain could document labor compliance, but few directly measured worker-level outcomes, wage effects, working conditions, or grievance resolution. Thus, the mechanisms are uneven: provenance and environmental-accounting mechanisms are comparatively stronger, while social-accountability mechanisms remain underdeveloped.

A key limitation of blockchain-based transparency is that ledger immutability does not guarantee truth at the point of data entry. A false record on an immutable ledger may become a permanent and auditable falsehood. This issue is particularly important in fashion supply chains, where upstream records may still be entered manually, supplier declarations may be strategically incomplete, and subcontracting relationships may be hidden. H​i​n​d​a​r​t​o​ ​e​t​ ​a​l​.​ ​(​2​0​2​4​) are useful in this respect because their qualitative evidence points to the need for provenance verification beyond the ledger itself. Future systems should therefore combine blockchain with trusted oracles, physical verification, sensor-based capture, third-party certification, and audit protocols at the point where material, labor, or environmental data are first generated.

The barriers identified in Section 3.4 should not be understood as merely technical. Transaction-cost logic helps explain why upstream suppliers have weak incentives to adopt costly transparency tools when most reputational and regulatory benefits accrue to brands or retailers. Small suppliers must pay for tagging, software integration, staff training, and documentation routines, but they may not receive higher margins or longer contracts in return. At the same time, buyer-driven supply chains can make transparency a compliance requirement rather than a jointly financed governance infrastructure. This creates a systemic barrier: the actors whose data are most needed for credible transparency are often those with the least bargaining power and the weakest capacity to digitize their operations.

The review found a clear imbalance across sustainability dimensions. Environmental and economic outcomes were more commonly measured through carbon accounting, waste tracking, audit time, cost savings, or compliance readiness. Social outcomes were more frequently invoked as a rationale than evaluated as an outcome. This may reflect several factors: blockchain is technically better suited to tracking objects, batches, certificates, and events than lived labor conditions; worker-level data are politically sensitive and difficult to collect; and brand-led transparency programs may prioritize externally reportable product information over worker voice. Future research should measure social outcomes directly, for example by linking blockchain-enabled compliance records with anonymized worker survey data, grievance-channel use, corrective-action completion, training records, wage-payment verification, or occupational-safety indicators.

The maturity gap exists because environmental and economic outcomes can often be represented by product-, batch-, or process-level records, whereas social sustainability depends on worker-level experience, power relations, confidentiality, and enforcement capacity that are harder to capture through ledger data alone.

The findings suggest three policy-relevant implications. First, digital product passport schemes should not track only materials, carbon, and circularity attributes. If labor-related fields are absent, such passports may improve product traceability while doing little for labor rights. Minimum labor-related data fields could include verified production site, certification status, training records, grievance-channel availability, and corrective-action status. Second, policymakers should pair transparency mandates with supplier-support mechanisms, including interoperable standards, shared identifiers, subsidized onboarding, and low-burden data-capture tools for small and medium-sized suppliers. Third, regulations should require source-data assurance, not merely ledger storage, because immutable records are valuable only when the underlying input data are credible.

For managers, the review suggests that blockchain projects should be scoped around specific transparency problems rather than around the technology itself. Projects aimed at batch traceability, certification integrity, audit readiness, or product-passport reporting are more likely to produce measurable value than broad claims of end-to-end transparency unsupported by data-capture infrastructure. For researchers, the most urgent need is not only more longitudinal research in general, but sharper studies of where transparency breaks down: upstream supplier costs, worker-level data availability, source-data fraud, and comparisons between blockchain and non-blockchain alternatives such as shared audit platforms or interoperable ERP systems.

The resulting evidence map can be summarized as follows: mature evidence clusters around provenance, audit readiness, environmental accounting, and product authentication; intermediate evidence concerns IoT- and product-passport-enabled data sharing; and least-developed evidence concerns worker-level social outcomes, supplier-side incentives, and comparisons with non-blockchain traceability systems. Future research should therefore prioritize longitudinal, multi-tier studies that test whether blockchain adds value beyond interoperable non-blockchain systems and whether transparency gains translate into measurable supplier and worker outcomes.

This review has limitations. First, the review was built from a retained corpus that preserved the screened set and extraction content but not auditable raw database-by-database retrieval counts; this limits the precision with which the identification stage can be reconstructed. Second, the included literature was heterogeneous in design, maturity, and reporting quality, limiting direct comparability. Third, some papers addressed textile or apparel contexts more broadly rather than fast fashion narrowly defined. The revised synthesis therefore distinguishes direct fast-fashion/apparel evidence from transferable textile evidence. Fourth, because the review was scoped to primary studies and did not undertake formal critical appraisal, the synthesis emphasizes mapping and interpretation rather than weighted causal inference. These limitations define the evidentiary boundary within which the current conclusions should be read.

Blockchain has become a prominent technological response to the transparency deficit of fast-fashion supply chains, but the present review shows that primary evidence remains concentrated in prototypes, conceptual system designs, and a relatively small number of pilots and case studies. Across 31 primary studies, blockchain most consistently contributed to traceability and provenance documentation when implemented through permissioned, or invite-only, architectures integrated with IoT, smart contracts, enterprise systems, or product-passport tools. Reported benefits included faster audits, improved batch-level visibility, waste reduction, and stronger sustainability reporting, while persistent barriers included cost, interoperability, fragmented governance, weak upstream digital capacity, and source-data credibility risks. The evidence therefore supports a qualified conclusion: blockchain is neither an unsubstantiated technological promise nor a self-sufficient solution. Its value for fast fashion lies in enabling trustworthy coordination across supply-chain actors, but only when technical design, incentives, governance, and source-data verification are aligned well enough to make transparency operational rather than merely promised.

Taken together, these findings support broader sustainability transitions by showing that digital transparency can connect environmental accounting, economic coordination, and social accountability only when governance standards and policy incentives align the interests of brands, suppliers, regulators, and consumers.

Three gaps remain especially important: (1) direct evidence that blockchain improves labor rights, wages, safety, or worker voice remains minimal; (2) upstream supplier costs and incentives are still usually examined from brand or system-designer perspectives rather than from supplier perspectives; and (3) the incremental value of blockchain over well-governed non-blockchain traceability systems has rarely been tested. These gaps should guide the next generation of empirical research.