Scholarlink

<p>The fashion industry is increasingly scrutinized for its substantial environmental and social impacts, making the transition toward sustainability an urgent global priority. This study presents a comprehensive review of 59 peer-reviewed articles published between 2016 and 2025 that apply Operational Research (OR) techniques to Sustainable Fashion Supply Chains (SFSCs). Drawing on data from the Web of Science, and employing VOSviewer and RStudio, the study integrates bibliometric analysis with a Systematic Literature Review (SLR) guided by the Theory–Context–Characteristics–Methodology (TCCM) framework. The findings reveal a clear upward trajectory in scholarly output, increasing from 2 publications in 2016 to a peak of 13 in 2024. The Journal of Cleaner Production emerged as the most influential source, contributing 10 articles and 343 citations, while the most cited work with 263 citations. Keyword co-occurrence analysis revealed three dominant thematic clusters: <i>(1) Modeling and Strategic Frameworks, (2) Managerial and Operational Optimization, and (3) Design, Green Initiatives, and Supply Chain Impact</i>, with “model”, “optimization”, and “sustainability” appearing as the most frequently occurring terms. The review underscores the growing importance of circular economy models, green supplier selection, reverse logistics, and fuzzy multi-criteria decision-making (MCDM) techniques, alongside the increasing integration of emerging digital technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and blockchain in sustainable fashion operations. By consolidating fragmented research through a structured analytical lens, this study offers valuable insights for both scholars and practitioners, highlighting key trends, methodological advancements, and future research pathways for leveraging Operational Research to advance sustainability in fashion supply chains.</p>

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

Operational research pathways for sustainable fashion supply chains: a comprehensive bibliometric and TCCM review

  • 期刊论文

  • 发表日期：

    2026年2月7日

查看全文
  • Brinda Sree Tamilarasan,
  • R. Kavitha,
  • V. Shiva Sankari

摘要

The fashion industry is increasingly scrutinized for its substantial environmental and social impacts, making the transition toward sustainability an urgent global priority. This study presents a comprehensive review of 59 peer-reviewed articles published between 2016 and 2025 that apply Operational Research (OR) techniques to Sustainable Fashion Supply Chains (SFSCs). Drawing on data from the Web of Science, and employing VOSviewer and RStudio, the study integrates bibliometric analysis with a Systematic Literature Review (SLR) guided by the Theory–Context–Characteristics–Methodology (TCCM) framework. The findings reveal a clear upward trajectory in scholarly output, increasing from 2 publications in 2016 to a peak of 13 in 2024. The Journal of Cleaner Production emerged as the most influential source, contributing 10 articles and 343 citations, while the most cited work with 263 citations. Keyword co-occurrence analysis revealed three dominant thematic clusters: (1) Modeling and Strategic Frameworks, (2) Managerial and Operational Optimization, and (3) Design, Green Initiatives, and Supply Chain Impact, with “model”, “optimization”, and “sustainability” appearing as the most frequently occurring terms. The review underscores the growing importance of circular economy models, green supplier selection, reverse logistics, and fuzzy multi-criteria decision-making (MCDM) techniques, alongside the increasing integration of emerging digital technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and blockchain in sustainable fashion operations. By consolidating fragmented research through a structured analytical lens, this study offers valuable insights for both scholars and practitioners, highlighting key trends, methodological advancements, and future research pathways for leveraging Operational Research to advance sustainability in fashion supply chains.