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Exploring Global Fashion Sustainability Practices through Dictionary-Based Text Mining
Clothing and Textiles Research Journal ( IF 2.4 ) Pub Date : 2021-03-05 , DOI: 10.1177/0887302x21998268
Muzhen Li 1 , Li Zhao 1
Affiliation  

Nowadays, more fashion companies have started to adopt various sustainability practices and communicate these practices through their annual public CSR reports. In this study, we aim to provide a holistic perspective of fashion companies’ sustainable development and investigate the sustainability practices of global fashion companies. A total of 181 CSR reports from 29 fashion companies were collected. A Dictionary approach text classification method, combined with Latent Dirichlet Allocation (LDA), a computer-assisted topic modeling algorithm, was implemented to detect and summarize the themes and keywords of detailed practices disclosed in CSR reports. The findings identified 12 main sustainability practices themes based on the triple bottom line theory and the moral responsibility of corporate sustainability theory. In general, waste management and human rights are the most frequently mentioned themes. The findings also suggest that global fashion companies adopted different sustainability strategies based on their product categories and competitive advantages.



中文翻译:

通过基于字典的文本挖掘探索全球时尚可持续发展实践

如今,越来越多的时装公司已开始采用各种可持续性做法,并通过其年度公共CSR报告传达这些做法。在本研究中,我们旨在提供时装公司可持续发展的整体视角,并研究全球时装公司的可持续发展实践。收集了来自29家时装公司的181份CSR报告。实施字典方法文本分类方法,结合计算机辅助主题建模算法Latent Dirichlet Allocation(LDA),以检测和总结CSR报告中披露的详细实践的主题和关键字。调查结果确定了基于三重底线理论和企业可持续性理论的道德责任的12个主要可持续性实践主题。一般来说,废物管理和人权是最常被提及的主题。调查结果还表明,全球时装公司根据其产品类别和竞争优势采取了不同的可持续发展战略。

更新日期:2021-03-05
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