<abstract xmlns="http://www.w3.org/1999/xhtml">

<bold>Research purpose.</bold> Identify the main textile exporters in the global world that would have the greatest impact on the development of geared textiles.
<bold>Design / Methodology / Approach.</bold> TOPSIS analysis has been applied as the most widely used efficiency measurement technique. The six criteria in the current research have been selected to describe the leading players in textiles globally and are available in a public database. In addition to the TOPSIS analysis, a clustering method has been employed to identify distinct groups among the countries under examination. Through this clustering analysis, countries with similar characteristics and practices.
<bold>Findings.</bold> The analysis of the textile and clothing industry has revealed the top ten economies that make the most significant contributions to global textile production. Through a comprehensive assessment based on predetermined criteria, these economies have been closely scrutinised, resulting in the European Union securing the leading position, followed by Malaysia in second place and China in the third. The leading position of the European Union can be attributed to its robust economic infrastructure, strong policy frameworks promoting sustainability, and a growing commitment to circular economy principles within the textile sector. Malaysia's second-place position may be influenced by its strategic investments in the textile industry, favourable business environment, and initiatives to foster sustainable practices. China's third-place ranking can be attributed to its substantial textile manufacturing capacity, extensive supply chains, and efforts to integrate circular economy principles into its textile production. The research findings indicate that several factors influence the rankings, including the level of economic development, technological advancements, population size, availability of cheap labour, and the influence of fashion trends, among others.
<bold>Originality / Value / Practical implications.</bold> The circular textile industry is a relatively new field, with the European Commission announcing the EU Strategy for Sustainable and Circular Textiles in 2022. This strategic initiative aims to propel the development and adoption of circular textile practices throughout the European Union, setting a benchmark for other regions to follow. It is important to underline that the study was carried out on a global scale in order to assess the world's main textile exporters. In order to assess the progress of circular textiles, we employ the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. This approach allows us to rank and assess countries based on their implementation of strategies and initiatives for developing a circular textile industry. Furthermore, we utilise a clustering method to identify distinct groups or patterns within the data, enabling a deeper understanding of the similarities and differences among countries in their circular textile. This clustering analysis helps identify clusters of countries that exhibit similar characteristics or practices, facilitating the identification of best practices, knowledge sharing, and collaboration among countries within each cluster. The findings of this study hold significant value and practical implications for policymakers, industry stakeholders, and researchers.
</abstract>

Research purpose. Identify the main textile exporters in the global world that would have the greatest impact on the development of geared textiles.
Design / Methodology / Approach. TOPSIS analysis has been applied as the most widely used efficiency measurement technique. The six criteria in the current research have been selected to describe the leading players in textiles globally and are available in a public database. In addition to the TOPSIS analysis, a clustering method has been employed to identify distinct groups among the countries under examination. Through this clustering analysis, countries with similar characteristics and practices.
Findings. The analysis of the textile and clothing industry has revealed the top ten economies that make the most significant contributions to global textile production. Through a comprehensive assessment based on predetermined criteria, these economies have been closely scrutinised, resulting in the European Union securing the leading position, followed by Malaysia in second place and China in the third. The leading position of the European Union can be attributed to its robust economic infrastructure, strong policy frameworks promoting sustainability, and a growing commitment to circular economy principles within the textile sector. Malaysia's second-place position may be influenced by its strategic investments in the textile industry, favourable business environment, and initiatives to foster sustainable practices. China's third-place ranking can be attributed to its substantial textile manufacturing capacity, extensive supply chains, and efforts to integrate circular economy principles into its textile production. The research findings indicate that several factors influence the rankings, including the level of economic development, technological advancements, population size, availability of cheap labour, and the influence of fashion trends, among others.
Originality / Value / Practical implications. The circular textile industry is a relatively new field, with the European Commission announcing the EU Strategy for Sustainable and Circular Textiles in 2022. This strategic initiative aims to propel the development and adoption of circular textile practices throughout the European Union, setting a benchmark for other regions to follow. It is important to underline that the study was carried out on a global scale in order to assess the world's main textile exporters. In order to assess the progress of circular textiles, we employ the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. This approach allows us to rank and assess countries based on their implementation of strategies and initiatives for developing a circular textile industry. Furthermore, we utilise a clustering method to identify distinct groups or patterns within the data, enabling a deeper understanding of the similarities and differences among countries in their circular textile. This clustering analysis helps identify clusters of countries that exhibit similar characteristics or practices, facilitating the identification of best practices, knowledge sharing, and collaboration among countries within each cluster. The findings of this study hold significant value and practical implications for policymakers, industry stakeholders, and researchers.

Assessing Circular Textile Industry Development

Vilnius Gediminas Technical University - VILNIUS TECH

Economics and Culture

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Assessing Circular Textile Industry Development"}

Research purpose. Identify the main textile exporters in the global world that would have the greatest impact on the development of geared textiles.
Design /...

Assessing Circular Textile Industry Development

Published Online: Jun 28, 2023

Page range: 55 - 67

Received: Mar 21, 2023

Accepted: May 31, 2023

DOI: https://doi.org/10.2478/jec-2023-0005

Keywords
Circular textile industry, TOPSIS method, Clustering method

© 2023 Ingrida Silobrit et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Assessing Circular Textile Industry Development

Published Online: Jun 28, 2023

Page range: 55 - 67

Received: Mar 21, 2023

Accepted: May 31, 2023

DOI: https://doi.org/10.2478/jec-2023-0005

KeywordsCircular textile industry, TOPSIS method, Clustering method

© 2023 Ingrida Silobrit et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Circular textile industry, TOPSIS method, Clustering method