Generative AI usage and sustainable supply chain performance: A practice-based view

The emergence of generative AI presents numerous potential solutions to address challenges in sustainable supply chain management (SCM). However, not all firms can effectively master the methods of using generative AI and realize potential benefits. To address this dilemma, the authors adopt a practice-based view (PBV) to examine generative AI usage’s effect on sustainable supply chain performance (SSCP). Analyzing survey data from 213 Chinese manufacturing firms, they identify a positive relationship between generative AI usage and SSCP. Moreover, two types of sustainable supply chain practices—green supply chain collaboration (GSCC) and circular economy implementation (CEI)——emerge as serial mediators connecting this relationship. They contribute to existing AI-enabled SCM research by elucidating the potential mediation mechanisms underlying the link between generative AI usage and SSCP. They also offer insightful implications for firms adapting to new norms in global SCM.

• Record URL:
  • https://doi.org/10.1016/j.tre.2024.103761
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1366554524003521
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Abstract reprinted with permission of Elsevier.
• Authors:
  • Li, Lixu
  • Zhu, Wenwen
  • Chen, Lujie
  • Liu, Yaoqi
• Publication Date: 2024-12

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References;
• Pagination: 103761
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 192
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Artificial intelligence; Industries; Performance; Supply chain management; Sustainable development
• Geographic Terms: China
• Subject Areas: Administration and Management; Data and Information Technology; Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01931705
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 23 2024 9:07AM