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Semantic-Driven Internet of Behaviours for Enhancing Supply Chain ESG Capabilities Through Generative AI

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  • Y. P. Tsang

    (The Hong Kong Polytechnic University, Hong Kong)

  • C. H. Wu

    (The Hang Seng University of Hong Kong, Hong Kong)

  • Yue Wang

    (The Education University of Hong Kong, Hong Kong)

  • W. H. Ip

    (The University of Saskatchewan, Canada)

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.

Suggested Citation

  • Y. P. Tsang & C. H. Wu & Yue Wang & W. H. Ip, 2025. "Semantic-Driven Internet of Behaviours for Enhancing Supply Chain ESG Capabilities Through Generative AI," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global Scientific Publishing, vol. 21(1), pages 1-33, January.
    • Handle: RePEc:igg:jswis0:v:21:y:2025:i:1:p:1-33
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