Semantic-driven internet of behaviours for enhancing supply chain ESG capabilities through generative AI

Y. P. TSANG, C. H. WU, Yue WANG, W. H. IP

Research output: Contribution to journalArticlespeer-review

Abstract

Pursuing sustainable development goals requires enterprises to enhance their environmental, social, and governance (ESG) capabilities. In logistics and supply chain management, where small and medium enterprises dominate, integrating ESG practices is challenging and often favors larger companies with established frameworks. This study introduces an ESG recommendation system based on generative artificial intelligence (GERS) to provide accessible, tailored ESG guidance. Leveraging large language models and an ESG knowledge base, GERS offers actionable recommendations, particularly benefiting small and medium enterprises. Evaluated through a case study with a Hong Kong Logistics Association ESG assessment programme, expert panels confirmed the quality of its recommendations. Results demonstrate the GERS’s ability to generate ESG improvement plans, enhancing capabilities efficiently. This research highlights the transformative potential of generative artificial intelligence in fostering sustainability, showcasing its role in creating adaptive, context-aware services that drive collaborative learning and sustainable practices in supply chains. Copyright © 2025 IGI Global. All rights reserved.

Original languageEnglish
Pages (from-to)1-33
JournalInternational Journal on Semantic Web and Information Systems
Volume21
Issue number1
Early online dateJan 2025
DOIs
Publication statusPublished - 2025

Citation

Tsang, Y. P., Wu, C. H., Wang, Y., & Ip, W. H. (2025). Semantic-driven internet of behaviours for enhancing supply chain ESG capabilities through generative AI. International Journal on Semantic Web and Information Systems, 21(1), 1-33. https://doi.org/10.4018/IJSWIS.385572

Keywords

  • GenAI
  • Large language model
  • Sustainable development goals
  • Recommendation system
  • Sustainability

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