Scholarlink

The primary aim of this study is to identify the prevailing topics and themes within the current body of sustainable manufacturing (SM) research. To this end, a collection of SM research works was curated from the Web of Science database to serve as the raw data for analysis. The Latent Dirichlet AllocationLatent dirichlet allocation (LDA) method was employed to extract latent topics from the abstracts of the SM literature. The topic modeling results highlight an imbalance, with social aspects being underrepresented compared to the economic and environmental dimensions. Consequently, this study suggests that there is a need for more interdisciplinary research efforts or projects to forge stronger links between the economic dimension and other SM parameters.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Text Mining in Sustainable Manufacturing for Topic Modeling

  • 章节

  • 发表日期：

    2025年

查看全文
  • Wai Sze Yip,
  • Suet To,
  • Hongting Zhou,
  • Jingzheng Ren

摘要

The primary aim of this study is to identify the prevailing topics and themes within the current body of sustainable manufacturing (SM) research. To this end, a collection of SM research works was curated from the Web of Science database to serve as the raw data for analysis. The Latent Dirichlet AllocationLatent dirichlet allocation (LDA) method was employed to extract latent topics from the abstracts of the SM literature. The topic modeling results highlight an imbalance, with social aspects being underrepresented compared to the economic and environmental dimensions. Consequently, this study suggests that there is a need for more interdisciplinary research efforts or projects to forge stronger links between the economic dimension and other SM parameters.