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Cited by 357

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Circular Economy — Challenges for the Textile and Clothing Industry

Open access
Koszewska, Małgorzata·2018·Autex Research Journal

Abstract

The circular economy model has recently gained a lot of attention worldwide from scientists, business people and authorities. The importance of the transition towards a more circular economy has also been noticed in the European Union. The new regulations provide the enabling framework for the circular economy to flourish. At the same time, although there is no standardized approach to creating a circular economy, while defining appropriate policies, care must be taken that they are suitable for particular industries. The limits of the present linear economy model (take-make-waste) are extremely apparent when examining the textile and clothing industry. The transition to a circular economy requires significant changes in both production and consumption models. This article uses a literature review and industry examples to identify and evaluate challenges faced by the clothing and textile industry in adapting to the circular economy model.

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Metadata

Authors
Koszewska, M.
Venue
Autex Research Journal
Published
2018-12-01
Volume
18
Issue
4
Pages
337-347
ISSN
  • 1470-9589 (ISSN-L)
  • 2300-0929
OpenAlex
W2883531657
Cited by
357
References
4
FWCI
36.45
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Circular Economy — Challenges for the Textile and Clothing Industry. https://app.cochat.ai/papers/10.1515/aut-2018-0023
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Koszewska, M. (2018). Circular Economy — Challenges for the Textile and Clothing Industry. Autex Research Journal. https://doi.org/10.1515/aut-2018-0023

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.