한국의류학회지 (Journal of the Korean Society of Clothing and Textiles)

  • 제48권5호
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  • Pages.883-899
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  • 2024
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  • 1225-1151(pISSN)
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  • 2234-0793(eISSN)
한국의류학회 (The Korean Society of Clothing and Textiles)
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텍스트 마이닝을 통한 패션 기업의 ESG 정보 유형화

Text-mining to Explore ESG Disclosure in the Fashion Industry

  • 김민정 ;
  • 김소정 (경희대학교 의상학과) ;
  • 이유나 (경희대학교 의상학과) ;
  • 정소진 (경희대학교 의상학과)
  • Min Jung Kim (Dept. of Hospitality and Retail Management, Texas Tech University) ;
  • Sojeong Kim (Dept. of Clothing & Textiles, Kyung Hee University) ;
  • Yu-na Lee (Dept. of Clothing & Textiles, Kyung Hee University) ;
  • Sojin Jung (Dept. of Clothing & Textiles, Kyung Hee University)
  • 투고 : 2024.02.15
  • 심사 : 2024.07.15
  • 발행 : 2024.10.31
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초록

The aim of this study was to investigate fashion firms' environmental, social, and governance (ESG) information disclosure. A total of 25 fashion firms (e.g., Adidas, Burberry Group, Nike, Ralph Lauren Corp.) were selected, including eight luxury brands and eight athleisure brands. Thus, three groups were formed for analysis: the entire group (N = 25), luxury brands (N = 8), and athleisure brands (N = 8). Based on the ESG information disclosed on the firms' official web pages, 1128 valid words were extracted. The top keywords for each brand group were identified based on the frequency and term frequency-inverse document frequency (TF-IDF), and semantic network analysis and convergence of iterated correlations (CONCOR) analysis were performed. The results revealed that several keywords and clusters emerged with respect to unique attributes of the fashion industry, and they also revealed inconsistent ESG clusters according to brand type. The findings have significant academic and managerial implications.

키워드

과제정보

이 연구는 2024학년도 경희대학교 교비 연구비 지원에 의한 결과임(KHU-20241059).

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