Application of Social Network Analysis to Visualization and Description of Industrial Clusters: A Case of the Textile Industry

Шерешева, Марина; Valitova, Lilia; Sharko, Elena; Buzulukova, Ekaterina

doi:10.3390/jrfm15030129

Cited by 3 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Among these strategies, the integration of CE design tools was found to be the most influential (Maliha et al, 2023). Another study analysed the network of companies in the textile industry using the clustering method, focusing on the textile companies with the highest connections (Sheresheva et al, 2022). Additionally, the research highlighted the challenges faced by the largest textile exporters, China and the European Union, emphasising the sustainability of textile reuse and recycling compared to incineration and landfill, with a particular emphasis on the benefits of reuse (Juanga-Labayen et al, 2022).…”

Section: Casementioning

confidence: 99%

Assessing Circular Textile Industry Development

Silobrit,

Jureviciene

2023

Economics and Culture

View full text Add to dashboard Cite

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.

show abstract

Section: Casementioning

confidence: 99%

Assessing Circular Textile Industry Development

Silobrit,

Jureviciene

2023

Economics and Culture

View full text Add to dashboard Cite

show abstract

“…В практическом применении между различными методами идентификации нет разницы, различаются только уровень исследования, применимый объект и направленность исследования. Из-за сложности промышленных кластеров при выборе метода идентификации следует учитывать характеристики промышленных кластеров, потребности в исследованиях и условия получения данных (Валитова и др., 2021;Sheresheva et al, 2022).…”

Section: методология исследованияunclassified

Life Cycle Analysis of Textile Clusters: The Example of Chinese Textile Enterprises in Zhejiang Province

Junzhi

2023

Naučnye issledovaniâ èkonomičeskogo fakulʹteta

View full text Add to dashboard Cite

As modern economy develops, the subjects of market competition are shifting from competition among individual enterprises to production and sales chains of enterprises and other forms of sustainable network interaction. Currently, more significant competition is manifested at the level of industrial clusters. The aim of this article is to study the model of the life cycle of textile industry clusters. The author examines the main schools of the theory of the life cycle of industrial clusters and chooses the theory of five stages of the life cycle of industrial clusters proposed by T. Andersson as the theoretical basis for this article. The textile industry cluster in the Chinese province of Zhejiang, where the largest number of textile enterprises in China is concentrated, was chosen as the object of research. Using the method of identifying the location coefficient based on the public databases of the Chinese Bureau of Statistics and the Bureau of Statistics of Zhejiang Province from 2002 to 2022 to determine the textile industry clusters in Zhejiang Province, the author found that the results calculated by the method of identifying the location coefficient correspond exactly to the five-stage development model of the Andersson cluster. From 2017 to 2020, the development of industrial clusters entered the stage of transformation, and the pace of development slowed down. Facing the risk of recession, with the help of external forces such as government support for industrial policy and internal forces such as technological and market innovations, the textile industry cluster in Zhejiang Province successfully transformed and entered a new life cycle.

show abstract

Application of the Business Ecosystem Approach to the Transformation of Business Models in Industry

Hrytsevich,

Tahir

2024

Advances in E-Business Research

View full text Add to dashboard Cite

Traditional industries that have dominated the market for decades are now facing new competitors that are changing the boundaries of industries and business models. These competitors are taking leadership positions due to the growth of digital technologies. One of the possible ways of successful functioning in the digital world can be the use of the concept of business ecosystems (BES), namely the introduction of a business ecosystem approach (BEA) to the formation of a new strategy for managing traditional business models. The article aims to reveal the relevance of the development of the BES concept and the use of BEA as a transitional element to the modern transformation of traditional industries. In this article, the author presents key conclusions on the refinement and use of criteria characterizing the functioning of business ecosystems for the organization of transformational processes, considering digitalization and intercompany integration. The author examines the example of the transformation of the light industry (textile and clothing) in the Republic of Belarus.

show abstract

Application of Social Network Analysis to Visualization and Description of Industrial Clusters: A Case of the Textile Industry

Cited by 3 publications

References 36 publications

Assessing Circular Textile Industry Development

Assessing Circular Textile Industry Development

Life Cycle Analysis of Textile Clusters: The Example of Chinese Textile Enterprises in Zhejiang Province

Application of the Business Ecosystem Approach to the Transformation of Business Models in Industry

Contact Info

Product

Resources

About